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  description: Internationally leading information system on all aspects of enzymes,
    including function, structure, involvement in diseases, application, engineering,
    and molecular properties. The database includes hundreds of milllions of enzyme
    data and is compiled from manual literature annotation, data integration from
    other databases and predicted enzyme functions and locations.
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    type:
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    type:
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    url: http://www.brenda-enzymes.org/introduction.php
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  - note: null
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    url: https://www.brenda-enzymes.org/faq.php
  download: []
  editPermission:
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    - juh22
    - lje
    type: group
  elixirCommunity: []
  elixirNode:
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  elixirPlatform:
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  - Tools
  - Interoperability
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Organism name
        uri: http://edamontology.org/data_2909
      format: []
    - data:
        term: Compound name
        uri: http://edamontology.org/data_0990
      format: []
    - data:
        term: Gene name
        uri: http://edamontology.org/data_2299
      format: []
    - data:
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      format: []
    - data:
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      format: []
    - data:
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      format: []
    - data:
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      format: []
    - data:
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      format: []
    - data:
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      format: []
    - data:
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    - data:
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      format: []
    - data:
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      format: []
    - data:
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      format: []
    - data:
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      format: []
    - data:
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      format: []
    - data:
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      format: []
    note: null
    operation:
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    - term: Sequence similarity search
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    - term: Visualisation
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    - term: Text mining
      uri: http://edamontology.org/operation_0306
    - term: Genome feature comparison
      uri: http://edamontology.org/operation_3194
    - term: Structure visualisation
      uri: http://edamontology.org/operation_0570
    - term: Genome visualisation
      uri: http://edamontology.org/operation_3208
    - term: Literature search
      uri: http://edamontology.org/operation_0305
    - term: Sequence database search
      uri: http://edamontology.org/operation_0338
    - term: Pathway or network visualisation
      uri: http://edamontology.org/operation_3083
    - term: Structural similarity search
      uri: http://edamontology.org/operation_0360
    - term: Transmembrane protein prediction
      uri: http://edamontology.org/operation_0269
    - term: Transmembrane protein visualisation
      uri: http://edamontology.org/operation_2241
    output:
    - data:
        term: UniProt ID
        uri: http://edamontology.org/data_2291
      format: []
    - data:
        term: PDB ID
        uri: http://edamontology.org/data_1127
      format: []
    - data:
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        uri: http://edamontology.org/data_3021
      format: []
    - data:
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      format: []
    - data:
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        uri: http://edamontology.org/data_2342
      format: []
    - data:
        term: Pathway or network accession
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      format: []
    - data:
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      format: []
    - data:
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      format: []
    - data:
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        uri: http://edamontology.org/data_1179
      format: []
    - data:
        term: SCOP domain identifier
        uri: http://edamontology.org/data_1039
      format: []
    - data:
        term: CATH identifier
        uri: http://edamontology.org/data_2700
      format: []
    - data:
        term: Enzyme name
        uri: http://edamontology.org/data_1012
      format: []
    - data:
        term: EC number
        uri: http://edamontology.org/data_1011
      format: []
    - data:
        term: Enzyme kinetics data
        uri: http://edamontology.org/data_2024
      format: []
  homepage: http://www.brenda-enzymes.org
  homepage_status: 0
  language: []
  lastUpdate: '2025-01-27T14:31:05.585156Z'
  license: CC-BY-4.0
  link:
  - note: null
    type:
    - Other
    url: https://www.dsmz.de/
  - note: null
    type:
    - Service
    url: https://hub.dsmz.de/#/
  - note: null
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    - Service
    url: https://www.brenda-enzymes.org/
  - note: null
    type:
    - Helpdesk
    url: https://brenda-enzymes.org/support.php
  maturity: Mature
  name: BRENDA
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: matkrull
  publication:
  - doi: 10.1093/nar/gkaa1025
    metadata:
      abstract: The BRENDA enzyme database (https://www.brendaenzymes.org), established
        in 1987, has evolved into the main collection of functional enzyme and metabolism
        data. In 2018, BRENDA was selected as an ELIXIR Core Data Resource. BRENDA
        provides reliable data, continuous curation and updates of classified enzymes,
        and the integration of newly discovered enzymes. The main part contains >5
        million data for ∼90 000 enzymes from ∼13 000 organisms, manually extracted
        from ∼157 000 primary literature references, combined with information of
        text and data mining, data integration, and prediction algorithms. Supplements
        comprise disease-related data, protein sequences, 3D structures, genome annotations,
        lig- and information, taxonomic, bibliographic, and kinetic data. BRENDA offers
        an easy access to enzyme information from quick to advanced searches, text-
        and structured-based queries for enzyme-ligand interactions, word maps, and
        visualization of enzyme data. The BRENDA Pathway Maps are completely revised
        and updated for an enhanced interactive and intuitive usability. The new design
        of the Enzyme Summary Page provides an improved access to each individual
        enzyme. A new protein structure 3D viewer was integrated. The prediction of
        the intracellular localization of eukaryotic enzymes has been implemented.
        The new EnzymeDetector combines BRENDA enzyme annotations with protein and
        genome databases for the detection of eukaryotic and prokaryotic enzymes.
      authors:
      - name: Chang A.
      - name: Jeske L.
      - name: Ulbrich S.
      - name: Hofmann J.
      - name: Koblitz J.
      - name: Schomburg I.
      - name: Neumann-Schaal M.
      - name: Jahn D.
      - name: Schomburg D.
      citationCount: 393
      date: '2021-01-08T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'BRENDA, the ELIXIR core data resource in 2021: New developments and
        updates'
    note: null
    pmcid: PMC7779020
    pmid: '33211880'
    type:
    - Primary
    version: null
  - doi: 10.1093/nar/gky1048
    metadata:
      abstract: The BRENDA enzyme database (www.brenda-enzymes.org), recently appointed
        ELIXIR Core Data Resource, is the main enzyme and enzyme-ligand information
        system. The core database provides a comprehensive overview on enzymes. A
        collection of 4.3 million data for ∼84 000 enzymes manually evaluated and
        extracted from ∼140 000 primary literature references is combined with information
        obtained by text and data mining, data integration and prediction algorithms.
        Supplements comprise disease-related data, protein sequences, 3D structures,
        predicted enzyme locations and genome annotations. Major developments are
        a revised ligand summary page and the structure search now including a similarity
        and isomer search. BKMS-react, an integrated database containing known enzyme-catalyzed
        reactions, is supplemented with further reactions and improved access to pathway
        connections. In addition to existing enzyme word maps with graphical information
        of enzyme specific terms, plant word maps have been developed. They show a
        graphical overview of terms, e.g. enzyme or plant pathogen information, connected
        to specific plants. An organism summary page showing all relevant information,
        e.g. taxonomy and synonyms linked to enzyme data, was implemented. Based on
        a decision by the IUBMB enzyme task force the enzyme class EC 7 has been established
        for 'translocases-, enzymes that catalyze a transport of ions or metabolites
        across cellular membranes.
      authors:
      - name: Jeske L.
      - name: Placzek S.
      - name: Schomburg I.
      - name: Chang A.
      - name: Schomburg D.
      citationCount: 296
      date: '2019-01-08T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'BRENDA in 2019: A European ELIXIR core data resource'
    note: null
    pmcid: PMC6323942
    pmid: '30395242'
    type: []
    version: null
  - doi: 10.1016/j.jbiotec.2017.04.020
    metadata:
      abstract: Enzymes, representing the largest and by far most complex group of
        proteins, play an essential role in all processes of life, including metabolism,
        gene expression, cell division, the immune system, and others. Their function,
        also connected to most diseases or stress control makes them interesting targets
        for research and applications in biotechnology, medical treatments, or diagnosis.
        Their functional parameters and other properties are collected, integrated,
        and made available to the scientific community in the BRaunschweig ENzyme
        DAtabase (BRENDA). In the last 30 years BRENDA has developed into one of the
        most highly used biological databases worldwide. The data contents, the process
        of data acquisition, data integration and control, the ways to access the
        data, and visualizations provided by the website are described and discussed.
      authors:
      - name: Schomburg I.
      - name: Jeske L.
      - name: Ulbrich M.
      - name: Placzek S.
      - name: Chang A.
      - name: Schomburg D.
      citationCount: 133
      date: '2017-11-10T00:00:00Z'
      journal: Journal of Biotechnology
      title: The BRENDA enzyme information system–From a database to an expert system
    note: null
    pmcid: null
    pmid: '28438579'
    type: []
    version: null
  - doi: 10.1093/nar/gku1068
    metadata:
      abstract: The BRENDA enzyme information system (http://www.brenda-enzymes.org/)
        has developed into an elaborate system of enzyme and enzyme-ligand information
        obtained from different sources, combined with flexible query systems and
        evaluation tools. The information is obtained by manual extraction from primary
        literature, text and data mining, data integration, and prediction algorithms.
        Approximately 300 million data include enzyme function and molecular data
        from more than 30 000 organisms. The manually derived core contains 3 million
        data from 77 000 enzymes annotated from 135 000 literature references. Each
        entry is connected to the literature reference and the source organism. They
        are complemented by information on occurrence, enzyme/disease relationships
        from text mining, sequences and 3D structures from other databases, and predicted
        enzyme location and genome annotation. Functional and structural data of more
        than 190 000 enzyme ligands are stored in BRENDA. New features improving the
        functionality and analysis tools were implemented. The human anatomy atlas
        CAVEman is linked to the BRENDA Tissue Ontology terms providing a connection
        between anatomical and functional enzyme data. Word Maps for enzymes obtained
        from PubMed.
      authors:
      - name: Chang A.
      - name: Schomburg I.
      - name: Placzek S.
      - name: Jeske L.
      - name: Ulbrich M.
      - name: Xiao M.
      - name: Sensen C.W.
      - name: Schomburg D.
      citationCount: 161
      date: '2015-01-28T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'BRENDA in 2015: Exciting developments in its 25th year of existence'
    note: null
    pmcid: PMC4383907
    pmid: '25378310'
    type:
    - Other
    version: null
  - doi: 10.1093/nar/gkn820
    metadata:
      abstract: The BRENDA (BRaunschweig ENzyme DAtabase) (http://www.brenda-enzymes.org)
        represents the largest freely available information system containing a huge
        amount of biochemical and molecular information on all classified enzymes
        as well as software tools for querying the database and calculating molecular
        properties. The database covers information on classification and nomenclature,
        reaction and specificity, functional parameters, occurrence, enzyme structure
        and stability, mutants and enzyme engineering, preparation and isolation,
        the application of enzymes, and ligand-related data. The data in BRENDA are
        manually curated from more than 79 000 primary literature references. Each
        entry is clearly linked to a literature reference, the origin organism and,
        where available, to the protein sequence of the enzyme protein. A new search
        option provides the access to protein-specific data. FRENDA (Full Reference
        ENzyme DAta) and AMENDA (Automatic Mining of ENzyme DAta) are additional databases
        created by continuously improved text-mining procedures. These databases ought
        to provide a complete survey on enzyme data of the literature collection of
        PubMed. The web service via a SOAP (Simple Object Access Protocol) interface
        for access to the BRENDA data has been further enhanced. © 2008 The Author(s).
      authors:
      - name: Chang A.
      - name: Scheer M.
      - name: Grote A.
      - name: Schomburg I.
      - name: Schomburg D.
      citationCount: 314
      date: '2009-01-09T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'BRENDA, AMENDA and FRENDA the enzyme information system: New content
        and tools in 2009'
    note: null
    pmcid: PMC2686525
    pmid: '18984617'
    type:
    - Other
    version: null
  - doi: 10.1093/nar/gkq1089
    metadata:
      abstract: The BRENDA (BRaunschweig ENzyme Database, http://www.brenda-enzymes.org)
        enzyme information system is the main collection of enzyme functional and
        property data for the scientific community. The majority of the data are manually
        extracted from the primary literature. The content covers information on function,
        structure, occurrence, preparation and application of enzymes as well as properties
        of mutants and engineered variants. The number of manually annotated references
        increased by 30% to more than 100 000, the number of ligand structures by
        45% to almost 100 000. New query, analysis and data management tools were
        implemented to improve data processing, data presentation, data input and
        data access. BRENDA now provides new viewing options such as the display of
        the statistics of functional parameters and the 3D view of protein sequence
        and structure features. Furthermore a ligand summary shows comprehensive information
        on the BRENDA ligands. The enzymes are linked to their respective pathways
        and can be viewed in pathway maps. The disease text mining part is strongly
        enhanced. It is possible to submit new, not yet classified enzymes to BRENDA,
        which then are reviewed and classified by the International Union of Biochemistry
        and Molecular Biology. A new SBML output format of BRENDA kinetic data allows
        the construction of organism-specific metabolic models. © The Author(s) 2010.
      authors:
      - name: Scheer M.
      - name: Grote A.
      - name: Chang A.
      - name: Schomburg I.
      - name: Munaretto C.
      - name: Rother M.
      - name: Sohngen C.
      - name: Stelzer M.
      - name: Thiele J.
      - name: Schomburg D.
      citationCount: 353
      date: '2011-01-01T00:00:00Z'
      journal: Nucleic Acids Research
      title: BRENDA, the enzyme information system in 2011
    note: null
    pmcid: PMC3013686
    pmid: '21062828'
    type:
    - Other
    version: null
  - doi: 10.1186/1471-2105-12-329
    metadata:
      abstract: 'Background: BRENDA (BRaunschweig ENzyme DAtabase, http://www.brenda-enzymes.org)
        is a major resource for enzyme related information. First and foremost, it
        provides data which are manually curated from the primary literature. DRENDA
        (Disease RElated ENzyme information DAtabase) complements BRENDA with a focus
        on the automatic search and categorization of enzyme and disease related information
        from title and abstracts of primary publications. In a two-step procedure
        DRENDA makes use of text mining and machine learning methods.Results: Currently
        enzyme and disease related references are biannually updated as part of the
        standard BRENDA update. 910,897 relations of EC-numbers and diseases were
        extracted from titles or abstracts and are included in the second release
        in 2010. The enzyme and disease entity recognition has been successfully enhanced
        by a further relation classification via machine learning. The classification
        step has been evaluated by a 5-fold cross validation and achieves an F1 score
        between 0.802 ± 0.032 and 0.738 ± 0.033 depending on the categories and pre-processing
        procedures. In the eventual DRENDA content every category reaches a classification
        specificity of at least 96.7% and a precision that ranges from 86-98% in the
        highest confidence level, and 64-83% for the smallest confidence level associated
        with higher recall.Conclusions: The DRENDA processing chain analyses PubMed,
        locates references with disease-related information on enzymes and categorises
        their focus according to the categories causal interaction, therapeutic application,
        diagnostic usage and ongoing research. The categorisation gives an impression
        on the focus of the located references. Thus, the relation categorisation
        can facilitate orientation within the rapidly growing number of references
        with impact on diseases and enzymes. The DRENDA information is available as
        additional information in BRENDA. © 2011 Söhngen et al; licensee BioMed Central
        Ltd.'
      authors:
      - name: Sohngen C.
      - name: Chang A.
      - name: Schomburg D.
      citationCount: 16
      date: '2011-08-09T00:00:00Z'
      journal: BMC Bioinformatics
      title: Development of a classification scheme for disease-related enzyme information
    note: null
    pmcid: PMC3166944
    pmid: '21827651'
    type:
    - Other
    version: null
  - doi: 10.1093/nar/gkh081
    metadata: null
    note: null
    pmcid: PMC308815
    pmid: '14681450'
    type:
    - Other
    version: null
  - doi: 10.1093/nar/gks1049
    metadata:
      abstract: The BRENDA (BRaunschweig ENzyme DAtabase) enzyme portal (http://www.brenda-enzymes.org)
        is the main information system of functional biochemical and molecular enzyme
        data and provides access to seven interconnected databases. BRENDA contains
        2.7 million manually annotated data on enzyme occurrence, function, kinetics
        and molecular properties. Each entry is connected to a reference and the source
        organism. Enzyme ligands are stored with their structures and can be accessed
        via their names, synonyms or via a structure search. FRENDA (Full Reference
        ENzyme DAta) and AMENDA (Automatic Mining of ENzyme DAta) are based on text
        mining methods and represent a complete survey of PubMed abstracts with information
        on enzymes in different organisms, tissues or organelles. The supplemental
        database DRENDA provides more than 910000 new EC number-disease relations
        in more than 510 000 references from automatic search and a classification
        of enzyme-disease-related information. KENDA (Kinetic ENzyme DAta), a new
        amendment extracts and displays kinetic values from PubMed abstracts. The
        integration of the EnzymeDetector offers an automatic comparison, evaluation
        and prediction of enzyme function annotations for prokaryotic genomes. The
        biochemical reaction database BKM-react contains non-redundant enzyme-catalysed
        and spontaneous reactions and was developed to facilitate and accelerate the
        construction of biochemical models. © The Author(s) 2012.
      authors:
      - name: Schomburg I.
      - name: Chang A.
      - name: Placzek S.
      - name: Sohngen C.
      - name: Rother M.
      - name: Lang M.
      - name: Munaretto C.
      - name: Ulas S.
      - name: Stelzer M.
      - name: Grote A.
      - name: Scheer M.
      - name: Schomburg D.
      citationCount: 347
      date: '2013-01-01T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'BRENDA in 2013: Integrated reactions, kinetic data, enzyme function
        data, improved disease classification: New options and contents in BRENDA'
    note: null
    pmcid: PMC3531171
    pmid: '23203881'
    type:
    - Other
    version: null
  - doi: 10.1016/s0968-0004(01)02027-8
    metadata:
      abstract: BRENDA (BRaunschweig ENzyme DAtabase), founded in 1987 by Dietmar
        Schomburg, is a comprehensive protein function database, containing enzymatic
        and metabolic information extracted from the primary literature. Presently,
        the database holds data on more than 40 000 enzymes and 4460 different organisms,
        and includes information about enzyme -ligand relationships with numerous
        chemical compounds. The collection of molecular and biochemical information
        in BRENDA provides a fundamental resource for research in biotechnology, pharmacology,
        medicinal diagnostics, enzyme mechanics, and metabolism. BRENDA is accessible
        free of charge to the academic community at http://www.brenda.uni-koeln.de/;
        commercial users need a license available from http://www.science-factory.com/.
      authors:
      - name: Schomburg I.
      - name: Chang A.
      - name: Hofmann O.
      - name: Ebeling C.
      - name: Ehrentreich F.
      - name: Schomburg D.
      citationCount: 159
      date: '2002-01-01T00:00:00Z'
      journal: Trends in Biochemical Sciences
      title: 'BRENDA: A resource for enzyme data and metabolic information'
    note: null
    pmcid: null
    pmid: '11796225'
    type:
    - Other
    version: null
  - doi: 10.1093/nar/gkl972
    metadata:
      abstract: The BRENDA (BRaunschweig ENzyme DAtabase) enzyme information system
        (http://www.brenda.uni-koeln.de) is the largest publicly available enzyme
        information system worldwide. The major parts of its contents are manually
        extracted from primary literature. It is not restricted to specific groups
        of enzymes, but includes information on all identified enzymes irrespective
        of the enzyme's source. The range of data encompasses functional, structural,
        sequence, localisation, disease-related, isolation, stability information
        on enzyme and ligand-related data. Each single entry is linked to the enzyme
        source and to a literature reference. Recently the data repository was complemented
        by text-mining data in AMENDA (Automatic Mining of ENzyme DAta) and FRENDA
        (Full Reference ENzyme DAta). A genome browser, membrane protein prediction
        and full-text search capacities were added. The newly implemented web service
        provides instant access to the data for programmers via a SOAP (Simple Object
        Access Protocol) interface. The BRENDA data can be downloaded in the form
        of a text file from the beginning of 2007. © 2007 Oxford University Press.
      authors:
      - name: Barthelmes J.
      - name: Ebeling C.
      - name: Chang A.
      - name: Schomburg I.
      - name: Schomburg D.
      citationCount: 137
      date: '2007-01-01T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'BRENDA, AMENDA and FRENDA: The enzyme information system in 2007'
    note: null
    pmcid: PMC1899097
    pmid: '17202167'
    type:
    - Other
    version: null
  - doi: 10.1093/nar/30.1.47
    metadata:
      abstract: BRENDA is a comprehensive relational database on functional and molecular
        information of enzymes, based on primary literature. The database contains
        information extracted and evaluated from approximately 46 000 references,
        holding data of at least 40 000 different enzymes from more than 6900 different
        organisms, classified in approximately 3900 EC numbers. BRENDA is an important
        tool for biochemical and medical research covering information on properties
        of all classified enzymes, including data on the occurrence, catalyzed reaction,
        kinetics, substrates/products, inhibitors, cofactors, activators, structure
        and stability. All data are connected to literature references which in turn
        are linked to PubMed. The data and information provide a fundamental tool
        for research of enzyme mechanisms, metabolic pathways, the evolution of metabolism
        and, furthermore, for medicinal diagnostics and pharmaceutical research. The
        database is a resource for data of enzymes, classified according to the EC
        system of the IUBMB Enzyme Nomenclature Committee, and the entries are cross-referenced
        to other databases, i.e. organism classification, protein sequence, protein
        structure and literature references. BRENDA provides an academic web access
        at http://www.brenda.uni-koeln.de.
      authors:
      - name: Schomburg I.
      - name: Chang A.
      - name: Schomburg D.
      citationCount: 384
      date: '2002-01-01T00:00:00Z'
      journal: Nucleic Acids Research
      title: BRENDA, enzyme data and metabolic information
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        2010.
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      - name: Chang A.
      - name: Schomburg I.
      - name: Grote A.
      - name: Scheer M.
      - name: Ebeling C.
      - name: Schomburg D.
      citationCount: 141
      date: '2011-01-01T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'The BRENDA Tissue Ontology (BTO): The first all-integrating ontology
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  description: Web application and service for visualizing small- to medium-scale
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      abstract: GRNsight is a web application and service for visualizing models of
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        GRNsight is best-suited for visualizing networks of fewer than 35 nodes and
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        GRNsight serves as an example of following and teaching best practices for
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      - name: Dionisio J.D.N.
      - name: Fitzpatrick B.G.
      - name: Anguiano N.A.
      - name: Varshneya A.
      - name: Southwick B.J.
      - name: Samdarshi M.
      citationCount: 2
      date: '2016-01-01T00:00:00Z'
      journal: PeerJ Computer Science
      title: 'GRNsight: A web application and service for visualizing models of small-to
        medium-scale gene regulatory networks'
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    note: null
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      - term: PHYLIP format
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      - term: PDF
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    pmcid: null
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  - term: Sequence sites, features and motifs
    uri: http://edamontology.org/topic_0160
  - term: Phylogenetics
    uri: http://edamontology.org/topic_3293
  - term: Sequencing
    uri: http://edamontology.org/topic_3168
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- accessibility: null
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  description: Common Access to Biological Resources and Information - A collection
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    note: SRS Standard Interface search
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  toolType:
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  validated: 1
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- accessibility: null
  additionDate: '2016-09-06T06:04:02Z'
  biotoolsCURIE: biotools:aquaria
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  description: Simplifying the generation of insight from protein structures through
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    type: Binaries
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    input:
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    - data:
        term: Organism identifier
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      format:
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        uri: http://edamontology.org/format_2330
    note: You can find sequences based on a keyword search. For the identified sequence,
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      between sequence and structure). accession number, ID or part of the name or
      alias from UniProt Organism names used in UniProt; Homo sapiens used by default
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    output: []
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    input:
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      format:
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    note: 'web service to get matching structures with alignment data for a given
      protein sequence Uniprot accession of query protein glued into the query URL:
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    operation:
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      format:
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        uri: http://edamontology.org/format_3464
  homepage: http://aquaria.ws
  homepage_status: 0
  language:
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  - Java
  lastUpdate: '2024-11-25T15:45:50.420021Z'
  license: GPL-2.0
  link:
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    type:
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    url: https://github.com/ODonoghueLab/Aquaria
  maturity: Mature
  name: Aquaria
  operatingSystem:
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  otherID: []
  owner: RostLab
  publication:
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    metadata: null
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    type:
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  relation: []
  toolType:
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  topic:
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    uri: http://edamontology.org/topic_3510
  - term: Protein structure analysis
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  validated: 1
  version:
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- accessibility: null
  additionDate: '2015-10-01T21:33:09Z'
  biotoolsCURIE: biotools:loctree3
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  description: Prediction of protein subcellular localization in 18 classes for eukaryota,
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  description: 'General workbench for analyzing regulatory sequence regions and discovering
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  description: Web-based computations on DNA melting, thus predicting the localized
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  description: This library is ideal for those seeking an overview of a complex subject
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  description: Provides a central data access hub for large collections of epigenomic
    data. It organizes the data from different sources using controlled vocabularies
    and ontologies. The data is stored in our server, where the users can access the
    data programmatically or by our web interface. It contains a set of commands designed
    to perform operations on the epigenomic data. Users can execute all operations
    in a pipeline fashion in the server and transfer only meaningful data.
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  - Python
  - C++
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  publication:
  - doi: 10.1093/nar/gkw211
    metadata:
      abstract: 'Large amounts of epigenomic data are generated under the umbrella
        of the International Human Epigenome Consortium, which aims to establish 1000
        reference epigenomes within the next fewyears. These data have the potential
        to unravel the complexity of epigenomic regulation. However, their effective
        use is hindered by the lack of flexible and easy-to-use methods for data retrieval.
        Extracting region sets of interest is a cumbersome task that involves several
        manual steps: identifying the relevant experiments, downloading the corresponding
        data files and filtering the region sets of interest. Here we present the
        DeepBlue Epigenomic Data Server, which streamlines epigenomic data analysis
        as well as software development. DeepBlue provides a comprehensive programmatic
        interface for finding, selecting, filtering, summarizing and downloading region
        sets. It contains data from four major epigenome projects, namely ENCODE,
        ROADMAP, BLUEPRINT and DEEP. DeepBlue comes with a user manual, examples and
        a well-documented application programming interface (API). The latter is accessed
        via the XML-RPC protocol supported by many programming languages. To demonstrate
        usage of the API and to enable convenient data retrieval for non-programmers,
        we offer an optional web interface. DeepBlue can be openly accessed at http://deepblue.mpi-inf.mpg.de.'
      authors:
      - name: Albrecht F.
      - name: List M.
      - name: Bock C.
      - name: Lengauer T.
      citationCount: 55
      date: '2016-07-08T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'DeepBlue epigenomic data server: programmatic data retrieval and analysis
        of epigenome region sets'
    note: null
    pmcid: PMC4987868
    pmid: '27084938'
    type:
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  relation: []
  toolType:
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  topic:
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  validated: 1
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- accessibility: null
  additionDate: '2016-06-29T11:13:00Z'
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    name: Division of Medicinal Chemistry (Vrije Universiteit Amsterdam)
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    name: European Commission seventh Framework Programme FP7-HEALTH-2013-INNOVATION-1,
      PDE4NPD (no. 602666)
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  description: The database revolves around the protein structure of catalytic PDE
    domains and the way PDE inhibitors can interact with them. It contains a systematic
    analysis of all phosphodiesterase (PDE) catalytic domain crystal structures present
    in the Protein Data Bank (PDB) with a focus on PDE-ligand interactions.
  documentation:
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    type:
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    - General
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        uri: http://edamontology.org/data_2886
      format:
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        uri: http://edamontology.org/format_2554
    note: Structures of catalytic kinase domains Sequences of catalytic kinase domains
      (UniProt)
    operation:
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    - term: Residue interaction calculation
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    - term: Protein property calculation
      uri: http://edamontology.org/operation_0250
    - term: 3D profile generation
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    - term: Structure analysis
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    - term: Data retrieval
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    - term: Structure classification
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    - term: Sequence visualisation
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      format: []
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      format: []
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      format: []
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      format: []
    - data:
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      format: []
  homepage: http://pdestrian.vu-compmedchem.nl
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  language: []
  lastUpdate: '2024-11-25T14:26:17.670147Z'
  license: null
  link: []
  maturity: Mature
  name: PDEStrIAn
  operatingSystem:
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  owner: a.j.kooistra@vu.nl
  publication:
  - doi: 10.1021/acs.jmedchem.5b01813
    metadata:
      abstract: A systematic analysis is presented of the 220 phosphodiesterase (PDE)
        catalytic domain crystal structures present in the Protein Data Bank (PDB)
        with a focus on PDE-ligand interactions. The consistent structural alignment
        of 57 PDE ligand binding site residues enables the systematic analysis of
        PDE-ligand interaction fingerprints (IFPs), the identification of subtype-specific
        PDE-ligand interaction features, and the classification of ligands according
        to their binding modes. We illustrate how systematic mining of this phosphodiesterase
        structure and ligand interaction annotated (PDEStrIAn) database provides new
        insights into how conserved and selective PDE interaction hot spots can accommodate
        the large diversity of chemical scaffolds in PDE ligands. A substructure analysis
        of the cocrystallized PDE ligands in combination with those in the ChEMBL
        database provides a toolbox for scaffold hopping and ligand design. These
        analyses lead to an improved understanding of the structural requirements
        of PDE binding that will be useful in future drug discovery studies.
      authors:
      - name: Jansen C.
      - name: Kooistra A.J.
      - name: Kanev G.K.
      - name: Leurs R.
      - name: De Esch I.J.P.
      - name: De Graaf C.
      citationCount: 56
      date: '2016-08-11T00:00:00Z'
      journal: Journal of Medicinal Chemistry
      title: 'PDEStrIAn: A Phosphodiesterase Structure and Ligand Interaction Annotated
        Database As a Tool for Structure-Based Drug Design'
    note: null
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    type:
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  relation: []
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  - term: Cheminformatics
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  - term: Computational chemistry
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  - term: Medicine
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  - term: Molecular interactions, pathways and networks
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  - term: Protein interactions
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  - term: Protein sites, features and motifs
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  - term: Protein structure analysis
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  - term: Small molecules
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  - term: Structural biology
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  - term: Structural genomics
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  validated: 1
  version: []
- accessibility: null
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  description: Resource to explore known and predicted interactions of chemicals and
    proteins. Chemicals are linked to other chemicals and proteins by evidence derived
    from experiments, databases and the literature.
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    - General
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      format:
      - term: InChIKey
        uri: http://edamontology.org/format_1199
      - term: SMILES
        uri: http://edamontology.org/format_1196
      - term: xls
        uri: http://edamontology.org/format_3468
    - data:
        term: Protein name
        uri: http://edamontology.org/data_1009
      format:
      - term: Textual format
        uri: http://edamontology.org/format_2330
    - data:
        term: Compound name
        uri: http://edamontology.org/data_0990
      format:
      - term: Textual format
        uri: http://edamontology.org/format_2330
    - data:
        term: Protein sequence
        uri: http://edamontology.org/data_2976
      format:
      - term: FASTA-like
        uri: http://edamontology.org/format_2546
    note: STITCH is a database of protein – chemical interactions that integrates
      many sources of experimental and manually curated evidence with text-mining
      information and interaction predictions. Its key function is to provide users
      with predictions about the interactions that their entities of interest (proteins
      or small molecules) may be making with other such entities, and to visualise
      where a set of entities of interest can be found within the STITCH network.
      Direct traceable links to the original sources on which interactions are described
      in the network, make it easy for users to trace the provenance of the data.
    operation:
    - term: Database search
      uri: http://edamontology.org/operation_2421
    - term: Pathway or network visualisation
      uri: http://edamontology.org/operation_3083
    - term: Pathway or network analysis
      uri: http://edamontology.org/operation_2497
    - term: Prediction and recognition
      uri: http://edamontology.org/operation_2423
    output:
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      format:
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      - term: Image format
        uri: http://edamontology.org/format_3547
    - data:
        term: Database cross-mapping
        uri: http://edamontology.org/data_0954
      format:
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        term: Evidence
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      format:
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  homepage: http://stitch.embl.de/
  homepage_status: 0
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  lastUpdate: '2024-11-25T14:25:13.779770Z'
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  link: []
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  name: STITCH
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  owner: hdhub
  publication:
  - doi: 10.1093/nar/gkm795
    metadata:
      abstract: The knowledge about interactions between proteins and small molecules
        is essential for the understanding of molecular and cellular functions. However,
        information on such interactions is widely dispersed across numerous databases
        and the literature. To facilitate access to this data, STITCH ('search tool
        for interactions of chemicals') integrates information about interactions
        from metabolic pathways, crystal structures, binding experiments and drug-target
        relationships. Inferred information from phenotypic effects, text mining and
        chemical structure similarity is used to predict relations between chemicals.
        STITCH further allows exploring the network of chemical relations, also in
        the context of associated binding proteins. Each proposed interaction can
        be traced back to the original data sources. Our database contains interaction
        information for over 68 000 different chemicals, including 2200 drugs, and
        connects them to 1.5 million genes across 373 genomes and their interactions
        contained in the STRING database. STITCH is available at http://stitch.embl.de/.
        © 2007 The Author(s).
      authors:
      - name: Kuhn M.
      - name: von Mering C.
      - name: Campillos M.
      - name: Jensen L.J.
      - name: Bork P.
      citationCount: 754
      date: '2008-01-01T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'STITCH: Interaction networks of chemicals and proteins'
    note: null
    pmcid: PMC2238848
    pmid: '18084021'
    type:
    - Primary
    version: null
  - doi: 10.1093/nar/gkp937
    metadata:
      abstract: Over the last years, the publicly available knowledge on interactions
        between small molecules and proteins has been steadily increasing. To create
        a network of interactions, STITCH aims to integrate the data dispersed over
        the literature and various databases of biological pathways, drug-target relationships
        and binding affinities. In STITCH 2, the number of relevant interactions is
        increased by incorporation of BindingDB, PharmGKB and the Comparative Toxicogenomics
        Database. The resulting network can be explored interactively or used as the
        basis for large-scale analyses. To facilitate links to other chemical databases,
        we adopt InChIKeys that allow identification of chemicals with a short, checksum-like
        string. STITCH 2.0 connects proteins from 630 organisms to over 74 000 different
        chemicals, including 2200 drugs. STITCH can be accessed at http://stitch.embl.de/.
        © The Author(s) 2009. Published by Oxford University Press.
      authors:
      - name: Kuhn M.
      - name: Szklarczyk D.
      - name: Franceschini A.
      - name: Campillos M.
      - name: Von Mering C.
      - name: Jensen L.J.
      - name: Beyer A.
      - name: Bork P.
      citationCount: 231
      date: '2009-11-06T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'STITCH 2: An interaction network database for small molecules and proteins'
    note: null
    pmcid: PMC2808890
    pmid: '19897548'
    type:
    - Other
    version: null
  - doi: 10.1093/nar/gkt1207
    metadata:
      abstract: STITCH is a database of protein-chemical interactions that integrates
        many sources of experimental and manually curated evidence with text-mining
        information and interaction predictions. Available at http://stitch.embl.de,
        the resulting interaction network includes 390 000 chemicals and 3.6 million
        proteins from 1133 organisms. Compared with the previous version, the number
        of high-confidence protein-chemical interactions in human has increased by
        45%, to 367 000. In this version, we added features for users to upload their
        own data to STITCH in the form of internal identifiers, chemical structures
        or quantitative data. For example, a user can now upload a spreadsheet with
        screening hits to easily check which interactions are already known. To increase
        the coverage of STITCH, we expanded the text mining to include full-text articles
        and added a prediction method based on chemical structures. We further changed
        our scheme for transferring interactions between species to rely on orthology
        rather than protein similarity. This improves the performance within protein
        families, where scores are now transferred only to orthologous proteins, but
        not to paralogous proteins. STITCH can be accessed with a web-interface, an
        API and downloadable files. © 2013 The Author(s). Published by Oxford University
        Press.
      authors:
      - name: Kuhn M.
      - name: Szklarczyk D.
      - name: Pletscher-Frankild S.
      - name: Blicher T.H.
      - name: Von Mering C.
      - name: Jensen L.J.
      - name: Bork P.
      citationCount: 413
      date: '2014-01-01T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'STITCH 4: Integration of protein-chemical interactions with user data'
    note: null
    pmcid: PMC3964996
    pmid: '24293645'
    type:
    - Other
    version: null
  - doi: 10.1093/nar/gkr1011
    metadata:
      abstract: To facilitate the study of interactions between proteins and chemicals,
        we have created STITCH, an aggregated database of interactions connecting
        over 300 000 chemicals and 2.6 million proteins from 1133 organisms. Compared
        to the previous version, the number of chemicals with interactions and the
        number of high-confidence interactions both increase 4-fold. The database
        can be accessed interactively through a web interface, displaying interactions
        in an integrated network view. It is also available for computational studies
        through downloadable files and an API. As an extension in the current version,
        we offer the option to switch between two levels of detail, namely whether
        stereoisomers of a given compound are shown as a merged entity or as separate
        entities. Separate display of stereoisomers is necessary, for example, for
        carbohydrates and chiral drugs. Combining the isomers increases the coverage,
        as interaction databases and publications found through text mining will often
        refer to compounds without specifying the stereoisomer. The database is accessible
        at http://stitch.embl.de/. © The Author(s) 2011.
      authors:
      - name: Kuhn M.
      - name: Szklarczyk D.
      - name: Franceschini A.
      - name: Von Mering C.
      - name: Jensen L.J.
      - name: Bork P.
      citationCount: 250
      date: '2012-01-01T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'STITCH 3: Zooming in on protein-chemical interactions'
    note: null
    pmcid: PMC3245073
    pmid: '22075997'
    type:
    - Other
    version: null
  relation: []
  toolType:
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  - Web application
  - Database portal
  topic:
  - term: Chemistry
    uri: http://edamontology.org/topic_3314
  - term: Biomedical science
    uri: http://edamontology.org/topic_3344
  - term: Molecular interactions, pathways and networks
    uri: http://edamontology.org/topic_0602
  validated: 1
  version: []
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  additionDate: '2016-03-02T08:53:57Z'
  biotoolsCURIE: biotools:atlasgeneticsoncology
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  description: The Atlas of Genetics and Cytogenetics in Oncology and Haematology
    is a peer-reviewed internet journal/encyclopaedia/database focused on genes implicated
    in cancer, cytogenetics and clinical entities in cancer and cancer-prone hereditary
    diseases. The main goal of the Atlas is to provide review articles that describe
    complementary topics, namely, genes, genetic abnormalities, histopathology, clinical
    diagnoses and a large iconography.
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    note: Query and retrieval of articles on human Genes, Leukemia, Tumors, Cancer
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    operation:
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  homepage: http://atlasgeneticsoncology.org
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  name: AGCOH
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  publication:
  - doi: 10.1093/nar/gks1082
    metadata:
      abstract: The Atlas of Genetics and Cytogenetics in Oncology and Haematology
        (http://AtlasGeneticsOncology. org) is a peer-reviewed internet journal/encyclopaedia/database
        focused on genes implicated in cancer, cytogenetics and clinical entities
        in cancer and cancer-prone hereditary diseases. The main goal of the Atlas
        is to provide review articles that describe complementary topics, namely,
        genes, genetic abnormalities, histopathology, clinical diagnoses and a large
        iconography. This description, which was historically based on karyotypic
        abnormalities and in situ hybridization (fluorescence in situ hybridization)
        techniques, now benefits from comparative genomic hybridization and massive
        sequencing, uncovering a tremendous amount of genetic rearrangements. As the
        Atlas combines different types of information (genes, genetic abnormalities,
        histopathology, clinical diagnoses and external links), its content is currently
        unique. The Atlas is a cognitive tool for fundamental and clinical research
        and has developed into an encyclopaedic work. In clinical practice, it contributes
        to the cytogenetic diagnosis and may guide treatment decision making, particularly
        regarding rare diseases (because they are numerous and are frequently encountered).
        Readers as well as the authors of the Atlasare researchers and/orclinicians.
        © The Author(s) 2012.
      authors:
      - name: Huret J.-L.
      - name: Ahmad M.
      - name: Arsaban M.
      - name: Bernheim A.
      - name: Cigna J.
      - name: Desangles F.
      - name: Guignard J.-C.
      - name: Jacquemot-Perbal M.-C.
      - name: Labarussias M.
      - name: Leberre V.
      - name: Malo A.
      - name: Morel-Pair C.
      - name: Mossafa H.
      - name: Potier J.-C.
      - name: Texier G.
      - name: Viguie F.
      - name: Wan-Senon S.Y.C.
      - name: Zasadzinski A.
      - name: Dessen P.
      citationCount: 144
      date: '2013-01-01T00:00:00Z'
      journal: Nucleic Acids Research
      title: Atlas of genetics and cytogenetics in oncology and haematology in 2013
    note: null
    pmcid: PMC3531131
    pmid: '23161685'
    type:
    - Primary
    version: null
  - doi: 10.1093/nar/gkg126
    metadata:
      abstract: The 'Atlas of Genetics and Cytogenetics in Oncology and Haematology'
        (http://www.infobiogen.fr/services/chromcancer) contains concise and updated
        cards on genes involved in cancer, cytogenetics and clinical entities in oncology,
        and cancer-prone diseases, a portal towards genetics/cancer, and teaching
        materials in genetics. This database is made for and by researchers and clinicians,
        who are encouraged to contribute. The Atlas is part of the genome project
        and it participates in research on cancer epidemiology.
      authors:
      - name: Huret J.-L.
      - name: Dessen P.
      - name: Bernheim A.
      citationCount: 46
      date: '2003-01-01T00:00:00Z'
      journal: Nucleic Acids Research
      title: Atlas of Genetics and Cytogenetics in Oncology and Haematology, year
        2003
    note: null
    pmcid: PMC165573
    pmid: '12520000'
    type:
    - Other
    version: null
  relation: []
  toolType:
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  topic:
  - term: Biology
    uri: http://edamontology.org/topic_3070
  - term: Medicine
    uri: http://edamontology.org/topic_3303
  validated: 1
  version: []
- accessibility: null
  additionDate: '2016-05-24T10:54:36Z'
  biotoolsCURIE: biotools:gwips-viz
  biotoolsID: gwips-viz
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  cost: Free of charge
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    name: Michel AM, Fox G, M Kiran A, De Bo C, O'Connor PB, Heaphy SM
    note: null
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    name: School of Biochemistry & Cell Biology, University College Cork
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  - email: gwipsviz@gmail.com
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  description: Specialized ribosome profiling (ribo-seq) browser providing free access
    to the genomic alignments of ribo-seq reads in conjunction with mRNA-seq controls
    along with relevant annotation tracks. Based on the UCSC Genome Browser, the tool’s
    ribo-seq tracks for various organisms allows for cross-species comparison of orthologous
    genes while the separate tracks for each ribo-seq study enables cross-study comparisons.
  documentation:
  - note: null
    type:
    - Citation instructions
    url: http://gwips.ucc.ie/index.html
  - note: null
    type:
    - General
    url: http://gwips.ucc.ie/Forum/
  download: []
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  function:
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    input: []
    note: null
    operation:
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      uri: http://edamontology.org/operation_0337
    - term: Gene expression analysis
      uri: http://edamontology.org/operation_2495
    output: []
  homepage: http://gwips.ucc.ie
  homepage_status: 0
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  lastUpdate: '2024-11-25T14:23:59.431472Z'
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  maturity: Mature
  name: GWIPS-viz
  operatingSystem:
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  owner: A.Michel@ucc.ie
  publication:
  - doi: 10.1093/nar/gkt1035
    metadata:
      abstract: 'We describe the development of GWIPS-viz (http://gwips.ucc.ie), an
        online genome browser for viewing ribosome profiling data. Ribosome profiling
        (ribo-seq) is a recently developed technique that provides genome-wide information
        on protein synthesis (GWIPS) in vivo. It is based on the deep sequencing of
        ribosome-protected messenger RNA (mRNA) fragments, which allows the ribosome
        density along all mRNA transcripts present in the cell to be quantified. Since
        its inception, ribo-seq has been carried out in a number of eukaryotic and
        prokaryotic organisms. Owing to the increasing interest in ribo-seq, there
        is a pertinent demand for a dedicated ribo-seq genome browser. GWIPS-viz is
        based on The University of California Santa Cruz (UCSC) Genome Browser. Ribo-seq
        tracks, coupled with mRNA-seq tracks, are currently available for several
        genomes: human, mouse, zebrafish, nematode, yeast, bacteria (Escherichia coli
        K12, Bacillus subtilis), human cytomegalovirus and bacteriophage lambda. Our
        objective is to continue incorporating published ribo-seq data sets so that
        the wider community can readily view ribosome profiling information from multiple
        studies without the need to carry out computational processing. © 2013 The
        Author(s). Published by Oxford University Press.'
      authors:
      - name: Michel A.M.
      - name: Fox G.
      - name: M. Kiran A.
      - name: De Bo C.
      - name: O'Connor P.B.F.
      - name: Heaphy S.M.
      - name: Mullan J.P.A.
      - name: Donohue C.A.
      - name: Higgins D.G.
      - name: Baranov P.V.
      citationCount: 178
      date: '2014-01-01T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'GWIPS-viz: Development of a ribo-seq genome browser'
    note: null
    pmcid: PMC3965066
    pmid: '24185699'
    type:
    - Primary
    version: null
  - doi: 10.1002/pmic.201400603
    metadata:
      abstract: The boundaries of protein coding sequences are more difficult to define
        at the 5′ end than at the 3′ end due to potential multiple translation initiation
        sites (TISs). Even in the presence of phylogenetic data, the use of sequence
        information only may not be sufficient for the accurate identification of
        TISs. Traditional proteomics approaches may also fail because the N-termini
        of newly synthesized proteins are often processed. Thus ribosome profiling
        (ribo-seq), producing a snapshot of the ribosome distribution across the entire
        transcriptome, is an attractive experimental technique for the purpose of
        TIS location exploration. The GWIPS-viz (Genome Wide Information on Protein
        Synthesis visualized) browser (http://gwips.ucc.ie) provides free access to
        the genomic alignments of ribo-seq data and corresponding mRNA-seq data along
        with relevant annotation tracks. In this brief, we illustrate how GWIPS-viz
        can be used to explore the ribosome occupancy at the 5′ ends of protein coding
        genes to assess the activity of AUG and non-AUG TISs responsible for the synthesis
        of proteoforms with alternative or heterogeneous N-termini. The presence of
        ribo-seq tracks for various organisms allows for cross-species comparison
        of orthologous genes and the availability of datasets from multiple laboratories
        permits the assessment of the technical reproducibility of the ribosome densities.
      authors:
      - name: Michel A.M.
      - name: Ahern A.M.
      - name: Donohue C.A.
      - name: Baranov P.V.
      citationCount: 18
      date: '2015-07-01T00:00:00Z'
      journal: Proteomics
      title: GWIPS-viz as a tool for exploring ribosome profiling evidence supporting
        the synthesis of alternative proteoforms
    note: null
    pmcid: PMC4832365
    pmid: '25736862'
    type:
    - Other
    version: null
  relation: []
  toolType:
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  topic:
  - term: Gene expression
    uri: http://edamontology.org/topic_0203
  validated: 1
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  biotoolsCURIE: biotools:guildify
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  credit:
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    name: Emre Guney
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    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Javier Garcia-Garcia
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  description: Uses network-topology based prioritization algorithms in GUILD to score
    relevance of gene products with respect to given keywords. First, BIANA knowledge
    base containing data integrated from publicly available major data repositories
    is queried for gene products associated with the keywords. These gene products
    are fed to a species-specific interaction network as seed proteins. Finally, a
    score of relevance for each gene product in the network is calculated by the prioritization
    algorithm.
  documentation:
  - note: null
    type:
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    note: 'Gene prioritization of genes associated with phenotype and diseases Starting
      seeds: genes associated with a disease

      or

      Keyword(s) of a phenotype or disease Network of associated proteins and drugs'
    operation:
    - term: Enrichment analysis
      uri: http://edamontology.org/operation_3501
    output:
    - data:
        term: Pathway or network
        uri: http://edamontology.org/data_2600
      format:
      - term: sif
        uri: http://edamontology.org/format_3619
  homepage: http://sbi.imim.es/web/GUILDify.php
  homepage_status: 0
  language: []
  lastUpdate: '2024-11-25T14:23:54.691568Z'
  license: null
  link: []
  maturity: null
  name: GUILDify
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: baldo.oliva@upf.edu
  publication:
  - doi: 10.1093/bioinformatics/btu092
    metadata:
      abstract: Determining genetic factors underlying various phenotypes is hindered
        by the involvement of multiple genes acting cooperatively. Over the past years,
        disease-gene prioritization has been central to identify genes implicated
        in human disorders. Special attention has been paid on using physical interactions
        between the proteins encoded by the genes to link them with diseases. Such
        methods exploit the guilt-by-association principle in the protein interaction
        network to uncover novel disease-gene associations. These methods rely on
        the proximity of a gene in the network to the genes associated with a phenotype
        and require a set of initial associations. Here, we present GUILDify, an easy-to-use
        web server for the phenotypic characterization of genes. GUILDify offers a
        prioritization approach based on the protein-protein interaction network where
        the initial phenotype-gene associations are retrieved via free text search
        on biological databases. GUILDify web server does not restrict the prioritization
        to any predefined phenotype, supports multiple species and accepts user-specified
        genes. It also prioritizes drugs based on the ranking of their targets, unleashing
        opportunities for repurposing drugs for novel therapies. © 2014 The Author.
        Published by Oxford University Press. All rights reserved.
      authors:
      - name: Guney E.
      - name: Garcia-Garcia J.
      - name: Oliva B.
      citationCount: 34
      date: '2014-06-15T00:00:00Z'
      journal: Bioinformatics
      title: 'GUILDify: A web server for phenotypic characterization of genes through
        biological data integration and network-based prioritization algorithms'
    note: null
    pmcid: null
    pmid: '24532728'
    type:
    - Other
    version: null
  - doi: 10.1371/journal.pone.0043557
    metadata:
      abstract: Complex genetic disorders often involve products of multiple genes
        acting cooperatively. Hence, the pathophenotype is the outcome of the perturbations
        in the underlying pathways, where gene products cooperate through various
        mechanisms such as protein-protein interactions. Pinpointing the decisive
        elements of such disease pathways is still challenging. Over the last years,
        computational approaches exploiting interaction network topology have been
        successfully applied to prioritize individual genes involved in diseases.
        Although linkage intervals provide a list of disease-gene candidates, recent
        genome-wide studies demonstrate that genes not associated with any known linkage
        interval may also contribute to the disease phenotype. Network based prioritization
        methods help highlighting such associations. Still, there is a need for robust
        methods that capture the interplay among disease-associated genes mediated
        by the topology of the network. Here, we propose a genome-wide network-based
        prioritization framework named GUILD. This framework implements four network-based
        disease-gene prioritization algorithms. We analyze the performance of these
        algorithms in dozens of disease phenotypes. The algorithms in GUILD are compared
        to state-of-the-art network topology based algorithms for prioritization of
        genes. As a proof of principle, we investigate top-ranking genes in Alzheimer's
        disease (AD), diabetes and AIDS using disease-gene associations from various
        sources. We show that GUILD is able to significantly highlight disease-gene
        associations that are not used a priori. Our findings suggest that GUILD helps
        to identify genes implicated in the pathology of human disorders independent
        of the loci associated with the disorders. © 2012 Guney, Oliva.
      authors:
      - name: Guney E.
      - name: Oliva B.
      citationCount: 90
      date: '2012-09-21T00:00:00Z'
      journal: PLoS ONE
      title: Exploiting Protein-Protein Interaction Networks for Genome-Wide Disease-Gene
        Prioritization
    note: null
    pmcid: PMC3448640
    pmid: '23028459'
    type:
    - Other
    version: null
  relation: []
  toolType:
  - Web API
  topic:
  - term: Systems medicine
    uri: http://edamontology.org/topic_3396
  validated: 1
  version:
  - '1.0'
- accessibility: null
  additionDate: '2016-03-17T14:52:04Z'
  biotoolsCURIE: biotools:ray
  biotoolsID: ray
  collectionID:
  - Debian Med
  - CWL
  - Animal and Crop Genomics
  - CloudBioLinux
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: null
    fundrefid: null
    gridid: null
    name: Sébastien Boisvert
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Jacques Corbeil
    note: null
    orcidid: null
    rorid: null
    typeEntity: null
    typeRole:
    - Contributor
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Élénie Godzaridis
    note: null
    orcidid: null
    rorid: null
    typeEntity: null
    typeRole:
    - Contributor
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: François Laviolette
    note: null
    orcidid: null
    rorid: null
    typeEntity: null
    typeRole:
    - Contributor
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Frédéric Raymond
    note: null
    orcidid: null
    rorid: null
    typeEntity: null
    typeRole:
    - Contributor
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Infectious Diseases Research Center, CHUQ Research Center
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
    - Provider
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: 1065, av. de la Médecine, Québec (Québec), G1V 0A6, Canada
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
    - Provider
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Faculty of Medicine, Laval University, 1050, av. de la Médecine, Québec
      (Québec), G1V 0A6, Canada
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
    - Provider
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Department of Molecular Medicine, Faculty of Medicine, Laval University
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
    - Provider
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Canadian Institutes of Health Research (CIHR), and other
    note: null
    orcidid: null
    rorid: null
    typeEntity: Funding agency
    typeRole:
    - Contributor
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: NTNU
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
    - Provider
    url: null
  - email: sharma.animesh@gmail.com
    fundrefid: null
    gridid: null
    name: Animesh Sharma
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  description: De novoassembly of single genomes and metagenomes. Also analyses microbe
    abundance and performs taxonomic profiling as well as making gene ontology profiling.
    It can also compare genomic content between samples.
  documentation:
  - note: null
    type:
    - General
    url: http://sebhtml.github.io/Ray.web/manual.html
  download:
  - note: null
    type: Source code
    url: http://sebhtml.github.io/Ray.web/download.html
    version: null
  - note: null
    type: Binaries
    url: http://sebhtml.github.io/Ray.web/download.html
    version: null
  editPermission:
    authors:
    - animalandcropgenomics
    type: group
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Sequence assembly
      uri: http://edamontology.org/operation_0310
    output: []
  homepage: http://denovoassembler.sourceforge.net
  homepage_status: 0
  language:
  - C++
  lastUpdate: '2024-11-25T14:23:12.573072Z'
  license: GPL-3.0
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/sebhtml/ray
  - note: null
    type:
    - Mirror
    url: http://sebhtml.github.io/Ray.web
  maturity: Mature
  name: Ray
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: NTNU
  publication:
  - doi: 10.1186/gb-2012-13-12-r122
    metadata:
      abstract: Voluminous parallel sequencing datasets, especially metagenomic experiments,
        require distributed computing for de novo assembly and taxonomic profiling.
        Ray Meta is a massively distributed metagenome assembler that is coupled with
        Ray Communities, which profiles microbiomes based on uniquely-colored k-mers.
        It can accurately assemble and profile a three billion read metagenomic experiment
        representing 1,000 bacterial genomes of uneven proportions in 15 hours with
        1,024 processor cores, using only 1.5 GB per core. The software will facilitate
        the processing of large and complex datasets, and will help in generating
        biological insights for specific environments. Ray Meta is open source and
        available at http://denovoassembler.sf.net.
      authors:
      - name: Boisvert S.
      - name: Raymond F.
      - name: Godzaridis E.
      - name: Laviolette F.
      - name: Corbeil J.
      citationCount: 463
      date: '2012-12-22T00:00:00Z'
      journal: Genome Biology
      title: 'Ray Meta: Scalable de novo metagenome assembly and profiling'
    note: null
    pmcid: PMC4056372
    pmid: '23259615'
    type:
    - Primary
    version: null
  - doi: 10.1089/cmb.2009.0238
    metadata:
      abstract: 'An accurate genome sequence of a desired species is now a pre-requisite
        for genome research. An important step in obtaining a high-quality genome
        sequence is to correctly assemble short reads into longer sequences accurately
        representing contiguous genomic regions. Current sequencing technologies continue
        to offer increases in throughput, and corresponding reductions in cost and
        time. Unfortunately, the benefit of obtaining a large number of reads is complicated
        by sequencing errors, with different biases being observed with each platform.
        Although software are available to assemble reads for each individual system,
        no procedure has been proposed for high-quality simultaneous assembly based
        on reads from a mix of different technologies. In this paper, we describe
        a parallel short-read assembler, called Ray, which has been developed to assemble
        reads obtained from a combination of sequencing platforms. We compared its
        performance to other assemblers on simulated and real datasets. We used a
        combination of Roche/454 and Illumina reads to assemble three different genomes.
        We showed that mixing sequencing technologies systematically reduces the number
        of contigs and the number of errors. Because of its open nature, this new
        tool will hopefully serve as a basis to develop an assembler that can be of
        universal utilization (availability: http://deNovoAssembler.sf.Net/). For
        online Supplementary Material, see www.liebertonline.com. Copyright 2010,
        Mary Ann Liebert, Inc.'
      authors:
      - name: Boisvert S.
      - name: Laviolette F.
      - name: Corbeil J.
      citationCount: 425
      date: '2010-11-01T00:00:00Z'
      journal: Journal of Computational Biology
      title: 'Ray: Simultaneous assembly of reads from a mix of high-throughput sequencing
        technologies'
    note: null
    pmcid: PMC3119603
    pmid: '20958248'
    type:
    - Other
    version: null
  relation: []
  toolType:
  - Command-line tool
  topic:
  - term: Biology
    uri: http://edamontology.org/topic_3070
  validated: 1
  version:
  - 2.3.1
- accessibility: null
  additionDate: '2016-08-26T11:55:20Z'
  biotoolsCURIE: biotools:ols
  biotoolsID: ols
  collectionID: []
  confidence_flag: null
  cost: null
  credit:
  - email: null
    fundrefid: null
    gridid: null
    name: Simon Jupp
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: https://www.ebi.ac.uk/~jupp/
  - email: null
    fundrefid: null
    gridid: null
    name: Samples, Phenotypes and Ontologies Team
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: http://www.ebi.ac.uk/about/spot-team
  - email: null
    fundrefid: null
    gridid: null
    name: EMBL-EBI
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
    - Provider
    url: http://www.ebi.ac.uk
  - email: null
    fundrefid: null
    gridid: null
    name: Elixir
    note: null
    orcidid: null
    rorid: null
    typeEntity: Consortium
    typeRole: []
    url: https://www.elixir-europe.org
  - email: null
    fundrefid: null
    gridid: null
    name: CORBEL
    note: null
    orcidid: null
    rorid: null
    typeEntity: Funding agency
    typeRole:
    - Contributor
    url: http://www.corbel-project.eu/home.html
  - email: null
    fundrefid: null
    gridid: null
    name: DIACHRON
    note: null
    orcidid: null
    rorid: null
    typeEntity: Funding agency
    typeRole:
    - Contributor
    url: http://www.diachron-fp7.eu
  - email: null
    fundrefid: null
    gridid: null
    name: EMBL-EBI
    note: null
    orcidid: null
    rorid: null
    typeEntity: Funding agency
    typeRole:
    - Contributor
    url: http://www.ebi.ac.uk
  - email: null
    fundrefid: null
    gridid: null
    name: BioMedBridges
    note: null
    orcidid: null
    rorid: null
    typeEntity: Consortium
    typeRole:
    - Documentor
    url: http://www.biomedbridges.eu
  - email: null
    fundrefid: null
    gridid: null
    name: ebi.ac.uk
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
    - Provider
    url: http://www.ebi.ac.uk
  - email: null
    fundrefid: null
    gridid: null
    name: OLS GitHub
    note: null
    orcidid: null
    rorid: null
    typeEntity: null
    typeRole:
    - Support
    url: https://github.com/EBISPOT/OLS
  - email: ols-support@ebi.ac.uk
    fundrefid: null
    gridid: null
    name: null
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: null
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: https://github.com/EBISPOT/OLS
  description: Repository for biomedical ontologies that aims to provide a single
    point of access to the latest ontology versions. Users can browse the ontologies
    through the web interface and programatic access is provided via a RESTful API.
  documentation:
  - note: null
    type:
    - Terms of use
    url: http://www.ebi.ac.uk/about/terms-of-use
  - note: null
    type:
    - General
    url: http://www.ebi.ac.uk/ols/docs/
  download: []
  editPermission:
    authors: []
    type: private
  elixirCommunity: []
  elixirNode:
  - EMBL
  elixirPlatform:
  - Interoperability
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Ontology visualisation
      uri: http://edamontology.org/operation_3559
    - term: ID mapping
      uri: http://edamontology.org/operation_3282
    output: []
  homepage: http://www.ebi.ac.uk/ols/
  homepage_status: 0
  language:
  - JavaScript
  - Java
  lastUpdate: '2024-11-25T14:20:55.319933Z'
  license: Apache-2.0
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/EBISPOT/OLS/
  maturity: Mature
  name: Ontology Lookup Service
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: jupp@ebi.ac.uk
  publication:
  - doi: 10.1186/1471-2105-7-97
    metadata:
      abstract: 'Background: With the vast amounts of biomedical data being generated
        by high-throughput analysis methods, controlled vocabularies and ontologies
        are becoming increasingly important to annotate units of information for ease
        of search and retrieval. Each scientific community tends to create its own
        locally available ontology. The interfaces to query these ontologies tend
        to vary from group to group. We saw the need for a centralized location to
        perform controlled vocabulary queries that would offer both a lightweight
        web-accessible user interface as well as a consistent, unified SOAP interface
        for automated queries. Results: The Ontology Lookup Service (OLS) was created
        to integrate publicly available biomedical ontologies into a single database.
        All modified ontologies are updated daily. A list of currently loaded ontologies
        is available online. The database can be queried to obtain information on
        a single term or to browse a complete ontology using AJAX. Auto-completion
        provides a user-friendly search mechanism. An AJAX-based ontology viewer is
        available to browse a complete ontology or subsets of it. A programmatic interface
        is available to query the webservice using SOAP. The service is described
        by a WSDL descriptor file available online. A sample Java client to connect
        to the webservice using SOAP is available for download from SourceForge. All
        OLS source code is publicly available under the open source Apache Licence.
        Conclusion: The OLS provides a user-friendly single entry point for publicly
        available ontologies in the Open Biomedical Ontology (OBO) format. It can
        be accessed interactively or programmatically at http://www.ebi.ac.uk/ontology-lookup/.
        © 2006 Côté et al; licensee BioMed Central Ltd.'
      authors:
      - name: Cote R.G.
      - name: Jones P.
      - name: Apweiler R.
      - name: Hermjakob H.
      citationCount: 175
      date: '2006-02-28T00:00:00Z'
      journal: BMC Bioinformatics
      title: The Ontology Lookup Service, a lightweight cross-platform tool for controlled
        vocabulary queries
    note: null
    pmcid: PMC1420335
    pmid: '16507094'
    type: []
    version: null
  - doi: 10.1093/nar/gkn252
    metadata:
      abstract: The Ontology Lookup Service (OLS) (http://www.ebi.ac.uk/ols) provides
        interactive and programmatic interfaces to query, browse and navigate an ever
        increasing number of biomedical ontologies and controlled vocabularies. The
        volume of data available for querying has more than quadrupled since it went
        into production and OLS functionality has been integrated into several high-usage
        databases and data entry tools. Improvements have been made to both OLS query
        interfaces, based on user feedback and requirements, to improve usability
        and service interoperability and provide novel ways to perform queries.
      authors:
      - name: Cote R.G.
      - name: Jones P.
      - name: Martens L.
      - name: Apweiler R.
      - name: Hermjakob H.
      citationCount: 70
      date: '2008-01-01T00:00:00Z'
      journal: Nucleic acids research
      title: 'The Ontology Lookup Service: more data and better tools for controlled
        vocabulary queries.'
    note: null
    pmcid: PMC2447739
    pmid: '18467421'
    type: []
    version: null
  - doi: 10.1093/nar/gkq331
    metadata:
      abstract: The Ontology Lookup Service (OLS; http://www.ebi.ac.uk/ols) has been
        providing several means to query, browse and navigate biomedical ontologies
        and controlled vocabularies since it first went into production 4 years ago,
        and usage statistics indicate that it has become a heavily accessed service
        with millions of hits monthly. The volume of data available for querying has
        increased 7-fold since its inception. OLS functionality has been integrated
        into several high-usage databases and data entry tools. Improvements in the
        data model and loaders, as well as interface enhancements have made the OLS
        easier to use and capture more annotations from the source data. In addition,
        newly released software packages now provide easy means to fully integrate
        OLS functionality in external applications. © The Author(s) 2010. Published
        by Oxford University Press.
      authors:
      - name: Cote R.
      - name: Reisinger F.
      - name: Martens L.
      - name: Barsnes H.
      - name: Vizcaino J.A.
      - name: Hermjakob H.
      citationCount: 102
      date: '2010-05-11T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'The Ontology Lookup Service: Bigger and better'
    note: null
    pmcid: PMC2896109
    pmid: '20460452'
    type: []
    version: null
  relation: []
  toolType:
  - Web API
  - Web application
  topic:
  - term: Ontology and terminology
    uri: http://edamontology.org/topic_0089
  validated: 1
  version:
  - '3'
- accessibility: null
  additionDate: '2015-12-02T16:31:52Z'
  biotoolsCURIE: biotools:norsnet
  biotoolsID: norsnet
  collectionID:
  - Rostlab tools
  - PredictProtein
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: null
    fundrefid: null
    gridid: null
    name: Avner Schlessinger
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Burkhard Rost
    note: null
    orcidid: null
    rorid: null
    typeEntity: null
    typeRole:
    - Contributor
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Jinfeng Liu
    note: null
    orcidid: http://orcid.org/0000-0002-0343-8222
    rorid: null
    typeEntity: null
    typeRole:
    - Contributor
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: University of California San Diego
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
    - Provider
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Columbia University
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
    - Provider
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Grant 2R01-LM07329-01 from the National Library of Medicine
    note: null
    orcidid: null
    rorid: null
    typeEntity: Funding agency
    typeRole:
    - Contributor
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: RostLab
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
    - Provider
    url: null
  - email: help@predictprotein.org
    fundrefid: null
    gridid: null
    name: null
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  description: Identification unstructured loops from sequence.
  documentation:
  - note: null
    type:
    - General
    url: https://rostlab.org/owiki/index.php/Norsnet
  download:
  - note: null
    type: Source code
    url: https://rostlab.org/owiki/index.php/Packages
    version: null
  - note: null
    type: Binaries
    url: https://rostlab.org/owiki/index.php/Packages
    version: null
  editPermission:
    authors: []
    type: private
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Protein sequence record
        uri: http://edamontology.org/data_2886
      format: []
    note: 'NORSnet is a neural network based method that focuses on the identification
      of unstructured loops.


      NORSnet was trained to distinguish between very long contiguous segments with
      non-regular secondary structure (NORS regions) and well-folded proteins. NORSnet
      was trained on predicted information rather than on experimental data. Therefore,
      it was optimized on a large data, which is not biased by today''s experimental
      means of capturing disorder. Thus, NORSnet reached into regions in sequence
      space that are not covered by the specialized disorder predictors. One disadvantage
      of this approach is that it is not optimal for the identification of the "average"
      disordered region. Protein amino-acid sequence in fasta format'
    operation:
    - term: Protein secondary structure prediction (coils)
      uri: http://edamontology.org/operation_0470
    output:
    - data:
        term: Protein report
        uri: http://edamontology.org/data_0896
      format:
      - term: TSV
        uri: http://edamontology.org/format_3475
  homepage: http://ppopen.informatik.tu-muenchen.de/
  homepage_status: 0
  language: []
  lastUpdate: '2024-11-25T14:18:37.601604Z'
  license: GPL-2.0
  link:
  - note: null
    type:
    - Repository
    url: https://rostlab.org/owiki/index.php/Packages
  maturity: null
  name: NorsNet
  operatingSystem:
  - Linux
  otherID: []
  owner: RostLab
  publication:
  - doi: 10.1371/journal.pcbi.0030140
    metadata:
      abstract: 'Natively unstructured or disordered protein regions may increase
        the functional complexity of an organism; they are particularly abundant in
        eukaryotes and often evade structure determination. Many computational methods
        predict unstructured regions by training on outliers in otherwise well-ordered
        structures. Here, we introduce an approach that uses a neural network in a
        very different and novel way. We hypothesize that very long contiguous segments
        with nonregular secondary structure (NORS regions) differ significantly from
        regular, well-structured loops, and that a method detecting such features
        could predict natively unstructured regions. Training our new method, NORSnet,
        on predicted information rather than on experimental data yielded three major
        advantages: it removed the overlap between testing and training, it systematically
        covered entire proteomes, and it explicitly focused on one particular aspect
        of unstructured regions with a simple structural interpretation, namely that
        they are loops. Our hypothesis was correct: well-structured and unstructured
        loops differ so substantially that NORSnet succeeded in their distinction.
        Benchmarks on previously used and new experimental data of unstructured regions
        revealed that NORSnet performed very well. Although it was not the best single
        prediction method, NORSnet was sufficiently accurate to flag unstructured
        regions in proteins that were previously not annotated. In one application,
        NORSnet revealed previously undetected unstructured regions in putative targets
        for structural genomics and may thereby contribute to increasing structural
        coverage of large eukaryotic families. NORSnet found unstructured regions
        more often in domain boundaries than expected at random. In another application,
        we estimated that 50%-70% of all worm proteins observed to have more than
        seven protein-protein interaction partners have unstructured regions. The
        comparative analysis between NORSnet and DISOPRED2 suggested that long unstructured
        loops are a major part of unstructured regions in molecular networks. © 2007
        Schlessinger et al.'
      authors:
      - name: Schlessinger A.
      - name: Liu J.
      - name: Rost B.
      citationCount: 85
      date: '2007-01-01T00:00:00Z'
      journal: PLoS Computational Biology
      title: Natively unstructured loops differ from other loops
    note: null
    pmcid: PMC1924875
    pmid: '17658943'
    type:
    - Primary
    version: null
  relation: []
  toolType:
  - Command-line tool
  - Web application
  topic:
  - term: Protein structure analysis
    uri: http://edamontology.org/topic_2814
  validated: 1
  version:
  - 1.0.16
- accessibility: null
  additionDate: '2015-12-02T18:10:26Z'
  biotoolsCURIE: biotools:peffect
  biotoolsID: peffect
  collectionID:
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  - Rostlab tools
  confidence_flag: null
  cost: Free of charge
  credit:
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    fundrefid: null
    gridid: null
    name: Tatyana Goldberg
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Yana Bromberg
    note: null
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    rorid: null
    typeEntity: null
    typeRole:
    - Contributor
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Burkhard Rost
    note: null
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    rorid: null
    typeEntity: null
    typeRole:
    - Contributor
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Technical University of Munich
    note: null
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    rorid: null
    typeEntity: Institute
    typeRole:
    - Provider
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Rutgers University
    note: null
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    rorid: null
    typeEntity: Institute
    typeRole:
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    url: null
  - email: null
    fundrefid: null
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    name: Alexander von Humboldt foundation through the German Federal Ministry for
      Education and Research
    note: null
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    rorid: null
    typeEntity: Funding agency
    typeRole:
    - Contributor
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Ernst Ludwig Ehrlich Studienwerk
    note: null
    orcidid: null
    rorid: null
    typeEntity: Funding agency
    typeRole:
    - Contributor
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: RostLab
    note: null
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    typeEntity: Institute
    typeRole:
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    url: null
  - email: localization@rostlab.org
    fundrefid: null
    gridid: null
    name: Support
    note: null
    orcidid: null
    rorid: null
    typeEntity: null
    typeRole:
    - Support
    url: null
  - email: localization@rostlab.org
    fundrefid: null
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    name: null
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  description: Prediction of type III effector proteins from protein sequence.
  documentation:
  - note: null
    type:
    - General
    url: https://rostlab.org/owiki/index.php/PEffect
  download:
  - note: null
    type: Source code
    url: https://rostlab.org/owiki/index.php/Packages
    version: null
  - note: null
    type: Binaries
    url: https://rostlab.org/owiki/index.php/Packages
    version: null
  editPermission:
    authors: []
    type: private
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  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Protein sequence (raw)
        uri: http://edamontology.org/data_2974
      format:
      - term: FASTA-like (text)
        uri: http://edamontology.org/format_2200
    note: Prediction of gram-negative bacterial type III effector proteins
    operation:
    - term: Protein function prediction
      uri: http://edamontology.org/operation_1777
    output:
    - data:
        term: Sequence features
        uri: http://edamontology.org/data_1255
      format:
      - term: TSV
        uri: http://edamontology.org/format_3475
  homepage: https://rostlab.org/services/peffect/
  homepage_status: 0
  language:
  - Java
  - Perl
  lastUpdate: '2024-11-25T14:17:40.306486Z'
  license: GPL-2.0
  link:
  - note: null
    type:
    - Repository
    url: https://rostlab.org/owiki/index.php/Packages
  maturity: Mature
  name: pEffect
  operatingSystem:
  - Linux
  otherID: []
  owner: RostLab
  publication:
  - doi: 10.1038/srep34516
    metadata:
      abstract: Type III secretion system is a key bacterial symbiosis and pathogenicity
        mechanism responsible for a variety of infectious diseases, ranging from food-borne
        illnesses to the bubonic plague. In many Gram-negative bacteria, the type
        III secretion system transports effector proteins into host cells, converting
        resources to bacterial advantage. Here we introduce a computational method
        that identifies type III effectors by combining homology-based inference with
        de novo predictions, reaching up to 3-fold higher performance than existing
        tools. Our work reveals that signals for recognition and transport of effectors
        are distributed over the entire protein sequence instead of being confined
        to the N-terminus, as was previously thought. Our scan of hundreds of prokaryotic
        genomes identified previously unknown effectors, suggesting that type III
        secretion may have evolved prior to the archaea/bacteria split. Crucially,
        our method performs well for short sequence fragments, facilitating evaluation
        of microbial communities and rapid identification of bacterial pathogenicity-no
        genome assembly required.
      authors:
      - name: Goldberg T.
      - name: Rost B.
      - name: Bromberg Y.
      citationCount: 33
      date: '2016-10-07T00:00:00Z'
      journal: Scientific Reports
      title: Computational prediction shines light on type III secretion origins
    note: null
    pmcid: PMC5054392
    pmid: '27713481'
    type:
    - Primary
    version: null
  relation: []
  toolType:
  - Command-line tool
  topic:
  - term: Protein sites, features and motifs
    uri: http://edamontology.org/topic_3510
  - term: Sequence analysis
    uri: http://edamontology.org/topic_0080
  validated: 1
  version:
  - 0.0.1
- accessibility: null
  additionDate: '2016-09-02T01:22:58Z'
  biotoolsCURIE: biotools:croppal
  biotoolsID: croppal
  collectionID:
  - Proteomics
  confidence_flag: null
  cost: null
  credit:
  - email: null
    fundrefid: null
    gridid: null
    name: ARC Centre of Excellence in Plant Energy Biology
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
    - Provider
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: The University of Western Australia
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
    - Provider
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Australian National Data Service
    note: null
    orcidid: null
    rorid: null
    typeEntity: Funding agency
    typeRole:
    - Contributor
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: unimelb.edu.au
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
    - Provider
    url: null
  - email: null
    fundrefid: null
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    name: Australia
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: http://www.plantenergy.uwa.edu.au/
  description: A data portal to access the compendium of data on crop protein subcellular
    locations.
  documentation:
  - note: null
    type:
    - Terms of use
    url: http://crop-pal.org/
  - note: null
    type:
    - General
    url: http://crop-pal.org/Tutorialv1.2.pdf
  download: []
  editPermission:
    authors:
    - proteomics.bio.tools
    type: group
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  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Protein subcellular localisation prediction
      uri: http://edamontology.org/operation_2489
    - term: Data retrieval
      uri: http://edamontology.org/operation_2422
    - term: Peptide database search
      uri: http://edamontology.org/operation_3646
    output: []
  homepage: http://crop-pal.org/
  homepage_status: 0
  language: []
  lastUpdate: '2024-11-25T14:16:23.433559Z'
  license: CC-BY-4.0
  link: []
  maturity: null
  name: cropPAL
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: griffinp@unimelb.edu.au
  publication:
  - doi: 10.1093/pcp/pcv170
    metadata:
      abstract: Barley, wheat, rice and maize provide the bulk of human nutrition
        and have extensive industrial use as agricultural products. The genomes of
        these crops each contains >40,000 genes encoding proteins; however, the major
        genome databases for these species lack annotation information of protein
        subcellular location for >80% of these gene products. We address this gap,
        by constructing the compendium of crop protein subcellular locations called
        crop Proteins with Annotated Locations (cropPAL). Subcellular location is
        most commonly determined by fluorescent protein tagging of live cells or mass
        spectrometry detection in subcellular purifications, but can also be predicted
        from amino acid sequence or protein expression patterns. The cropPAL database
        collates 556 published studies, from >300 research institutes in >30 countries
        that have been previously published, as well as compiling eight precomputed
        subcellular predictions for all Hordeum vulgare, Triticum aestivum, Oryza
        sativa and Zea mays protein sequences. The data collection including metadata
        for proteins and published studies can be accessed through a search portal
        http://crop-PAL.org. The subcellular localization information housed in cropPAL
        helps to depict plant cells as compartmentalized protein networks that can
        be investigated for improving crop yield and quality, and developing new biotechnological
        solutions to agricultural challenges.
      authors:
      - name: Hooper C.M.
      - name: Castleden I.R.
      - name: Aryamanesh N.
      - name: Jacoby R.P.
      - name: Millar A.H.
      citationCount: 44
      date: '2016-01-01T00:00:00Z'
      journal: Plant and Cell Physiology
      title: 'Finding the subcellular location of barley, wheat, rice and maize proteins:
        The compendium of crop proteins with annotated locations (cropPAL)'
    note: null
    pmcid: null
    pmid: '26556651'
    type:
    - Primary
    version: null
  relation: []
  toolType:
  - Database portal
  topic:
  - term: Proteomics
    uri: http://edamontology.org/topic_0121
  - term: Plant biology
    uri: http://edamontology.org/topic_0780
  validated: 1
  version: []
- accessibility: null
  additionDate: '2015-11-25T19:40:48Z'
  biotoolsCURIE: biotools:swicz
  biotoolsID: swicz
  collectionID:
  - Czech Republic
  - ELIXIR-CZ
  - Proteomics
  confidence_flag: null
  cost: Free of charge (with restrictions)
  credit:
  - email: null
    fundrefid: null
    gridid: null
    name: Ivan Janda
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Jiří­ Vohradský
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Jan Bobek
    note: null
    orcidid: null
    rorid: null
    typeEntity: null
    typeRole:
    - Contributor
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Urs Jenal
    note: null
    orcidid: null
    rorid: null
    typeEntity: null
    typeRole:
    - Contributor
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Karel Mikulik
    note: null
    orcidid: null
    rorid: null
    typeEntity: null
    typeRole:
    - Contributor
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Marek Basler
    note: null
    orcidid: null
    rorid: null
    typeEntity: null
    typeRole:
    - Contributor
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Bjorn Grunenfelder
    note: null
    orcidid: null
    rorid: null
    typeEntity: null
    typeRole:
    - Contributor
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Institute of Microbiology, Prague, Czech Republic
    note: null
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    typeEntity: Institute
    typeRole:
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    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Biozentrum, Univ. Basel, Switzerland
    note: null
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    typeEntity: Institute
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    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: ELIXIR-CZ
    note: null
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    rorid: null
    typeEntity: Consortium
    typeRole: []
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Czech Science Foundation
    note: null
    orcidid: null
    rorid: null
    typeEntity: Funding agency
    typeRole:
    - Contributor
    url: null
  - email: null
    fundrefid: null
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    name: ELIXIR-CZ
    note: null
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    rorid: null
    typeEntity: Institute
    typeRole:
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    url: null
  - email: vohr@biomed.cas.cz
    fundrefid: null
    gridid: null
    name: Jiří­ Vohradský
    note: null
    orcidid: null
    rorid: null
    typeEntity: null
    typeRole:
    - Support
    url: null
  - email: vohr@biomed.cas.cz
    fundrefid: null
    gridid: null
    name: Jiří Vohradský
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  description: A proteomics web database.
  documentation:
  - note: null
    type:
    - Terms of use
    - Citation instructions
    url: http://proteom.biomed.cas.cz
  - note: null
    type:
    - General
    url: http://proteom.biomed.cas.cz/strepto_new/experimental_strep.php
  download:
  - note: null
    type: Source code
    url: http://proteom.biomed.cas.cz
    version: null
  - note: null
    type: Binaries
    url: http://proteom.biomed.cas.cz
    version: null
  editPermission:
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    type: group
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  elixirPlatform:
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  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: Database of proteomic time series data for streptomyces, caulobacter and
      neiseria Interactive form interlinked with other resources as NCBI, SwissProt,
      KEGG
    operation:
    - term: Database search
      uri: http://edamontology.org/operation_2421
    output:
    - data:
        term: Experiment report
        uri: http://edamontology.org/data_2531
      format:
      - term: HTML
        uri: http://edamontology.org/format_2331
  homepage: http://proteom.biomed.cas.cz/
  homepage_status: 0
  language:
  - PHP
  lastUpdate: '2024-11-25T14:10:47.731263Z'
  license: null
  link:
  - note: null
    type:
    - Repository
    url: http://proteom.biomed.cas.cz
  maturity: Mature
  name: SWICZ
  operatingSystem:
  - Windows
  otherID: []
  owner: ELIXIR-CZ
  publication:
  - doi: 10.1002/pmic.200300559
    metadata:
      abstract: Here we present the Swiss-Czech Proteomics Server (SWICZ), which hosts
        the proteomic database summarizing information about the cell cycle of the
        aquatic bacterium Caulobacter crescentus. The database provides a searchable
        tool for easy access of global protein synthesis and protein stability data
        as examined during the C. crescentus cell cycle. Protein synthesis data collected
        from five different cell cycle stages were determined for each protein spot
        as a relative value of the total amount of [35S]methionine incorporation.
        Protein stability of pulse-labeled extracts were measured during a chase period
        equivalent to one cell cycle unit. Quantitative information for individual
        proteins together with descriptive data such as protein identities, apparent
        molecular masses and isoelectric points, were combined with information on
        protein function, genomic context, and the cell cycle stage, and were then
        assembled in a relational data-base with a world wide web interface (http://proteom.biomed.cas.cz),
        which allows the database records to be searched and displays the recovered
        information. A total of 1250 protein spots were reproducibly detected on two-dimensional
        gel electropherograms, 295 of which were identified by mass spectroscopy.
        The database is accessible either through clickable two-dimensional gel electrophoretic
        maps or by means of a set of dedicated search engines. Basic characterization
        of the experimental procedures, data processing, and a comprehensive description
        of the web site are presented. In its current state, the SWICZ proteome database
        provides a platform for the incorporation of new data emerging from extended
        functional studies on the C. crescentus proteome.
      authors:
      - name: Vohradsky J.
      - name: Janda I.
      - name: Grunenfelder B.
      - name: Berndt P.
      - name: Roder D.
      - name: Langen H.
      - name: Weiser J.
      - name: Jenal U.
      citationCount: 11
      date: '2003-10-01T00:00:00Z'
      journal: Proteomics
      title: Proteome of Caulobacter crescentus cell cycle publicly accessible on
        SWICZ server
    note: null
    pmcid: null
    pmid: '14625849'
    type:
    - Other
    version: null
  - doi: 10.1002/pmic.200500206
    metadata:
      abstract: Gene expression databases, acquired by proteomics and transcriptomics,
        describe physiological and developmental programs at the systems level. Here
        we analyze proteosynthetic profiles in a bacterium undergoing defined metabolic
        changes. Streptomyces coelicolor cultured in a defined liquid medium displays
        four distinct patterns of gene expression associated with growth on glutamate,
        diauxic transition, and growth on maltose and ammonia that terminates by starvation
        for nitrogen and entry into stationary phase. Principal component and fuzzy
        duster analyses of the proteome database of 935 protein spot profiles revealed
        principal kinetic patterns. Online linkage of the proteome database (SWICZ)
        to a protein-function database (KEGG) revealed limited correlations between
        expression profiles and metabolic pathway activities. Proteins belonging to
        principal metabolic pathways defined characteristic kinetic profiles correlated
        with the physiological state of the culture. These analyses supported the
        concept that metabolic flux was regulated not by individual enzymes but rather
        by groups of enzymes whose synthesis responded to changes in nutritional conditions.
        Higher-level regulation is reflected by the distribution of all kinetic profiles
        into only nine groups. The observation that enzymes representing principal
        metabolic pathways displayed their own distinctive average kinetic profiles
        suggested that expression of a "high-flux backbone" may dominate regulation
        of metabolic flux. © 2006 Wiley-VCH Verlag GmbH & Co. KGaA.
      authors:
      - name: Vohradsky J.
      - name: Thompson C.J.
      citationCount: 11
      date: '2006-02-01T00:00:00Z'
      journal: Proteomics
      title: Systems level analysis of protein synthesis patterns associated with
        bacterial growth and metabolic transitions
    note: null
    pmcid: null
    pmid: '16400688'
    type:
    - Other
    version: null
  relation: []
  toolType:
  - Database portal
  topic:
  - term: Protein expression
    uri: http://edamontology.org/topic_0108
  - term: Proteomics experiment
    uri: http://edamontology.org/topic_3520
  validated: 1
  version: []
- accessibility: null
  additionDate: '2019-12-13T14:58:07Z'
  biotoolsCURIE: biotools:Cocoa_Genome_Hub
  biotoolsID: Cocoa_Genome_Hub
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  - elixir-fr-sdp-2019
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: xavier.argout@cirad.fr
    fundrefid: null
    gridid: null
    name: Argout
    note: null
    orcidid: https://orcid.org/0000-0002-0100-5511
    rorid: null
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    typeRole:
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    url: null
  - email: gaetan.droc@cirad.fr
    fundrefid: null
    gridid: null
    name: Droc
    note: null
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    rorid: null
    typeEntity: Person
    typeRole:
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    url: null
  - email: claire.lanaud@cirad.fr
    fundrefid: null
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    name: Lanaud
    note: null
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    typeEntity: Person
    typeRole:
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    url: null
  - email: null
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    gridid: null
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    typeRole:
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  - email: null
    fundrefid: null
    gridid: null
    name: ANR
    note: null
    orcidid: null
    rorid: null
    typeEntity: Funding agency
    typeRole: []
    url: null
  description: The Cocoa Genome Hub is an integrated web-based database providing
    centralized access to the cocoa reference genome sequences and genomic resources.
  documentation:
  - note: null
    type:
    - API documentation
    url: http://api.tripal.info/api/tripal/3.x
  - note: null
    type:
    - Terms of use
    url: https://cocoa-genome-hub.southgreen.fr/content/terms-service
  download: []
  editPermission:
    authors: []
    type: private
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  elixirNode:
  - France
  elixirPlatform:
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  - Tools
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
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      uri: http://edamontology.org/operation_3184
    - term: Ontology visualisation
      uri: http://edamontology.org/operation_3559
    - term: Sequence alignment
      uri: http://edamontology.org/operation_0292
    output: []
  homepage: https://cocoa-genome-hub.southgreen.fr/
  homepage_status: 0
  language:
  - PHP
  - JavaScript
  lastUpdate: '2024-11-25T14:00:43.154205Z'
  license: GPL-2.0
  link:
  - note: null
    type:
    - Helpdesk
    url: https://cocoa-genome-hub.southgreen.fr/contact
  maturity: Mature
  name: Cocoa Genome Hub
  operatingSystem:
  - Linux
  otherID: []
  owner: gdroc
  publication:
  - doi: 10.1186/s12864-017-4120-9
    metadata:
      abstract: 'Background: Theobroma cacao L., native to the Amazonian basin of
        South America, is an economically important fruit tree crop for tropical countries
        as a source of chocolate. The first draft genome of the species, from a Criollo
        cultivar, was published in 2011. Although a useful resource, some improvements
        are possible, including identifying misassemblies, reducing the number of
        scaffolds and gaps, and anchoring un-anchored sequences to the 10 chromosomes.
        Methods: We used a NGS-based approach to significantly improve the assembly
        of the Belizian Criollo B97-61/B2 genome. We combined four Illumina large
        insert size mate paired libraries with 52x of Pacific Biosciences long reads
        to correct misassembled regions and reduced the number of scaffolds. We then
        used genotyping by sequencing (GBS) methods to increase the proportion of
        the assembly anchored to chromosomes. Results: The scaffold number decreased
        from 4,792 in assembly V1 to 554 in V2 while the scaffold N50 size has increased
        from 0.47 Mb in V1 to 6.5 Mb in V2. A total of 96.7% of the assembly was anchored
        to the 10 chromosomes compared to 66.8% in the previous version. Unknown sites
        (Ns) were reduced from 10.8% to 5.7%. In addition, we updated the functional
        annotations and performed a new RefSeq structural annotation based on RNAseq
        evidence. Conclusion:Theobroma cacao Criollo genome version 2 will be a valuable
        resource for the investigation of complex traits at the genomic level and
        for future comparative genomics and genetics studies in cacao tree. New functional
        tools and annotations are available on the Cocoa Genome Hub ( http://cocoa-genome-hub.southgreen.fr
        ).'
      authors:
      - name: Argout X.
      - name: Martin G.
      - name: Droc G.
      - name: Fouet O.
      - name: Labadie K.
      - name: Rivals E.
      - name: Aury J.M.
      - name: Lanaud C.
      citationCount: 65
      date: '2017-09-15T00:00:00Z'
      journal: BMC Genomics
      title: 'The cacao Criollo genome v2.0: An improved version of the genome for
        genetic and functional genomic studies'
    note: null
    pmcid: PMC5603072
    pmid: '28915793'
    type:
    - Primary
    version: null
  - doi: 10.1038/ng.736
    metadata:
      abstract: We sequenced and assembled the draft genome of Theobroma cacao, an
        economically important tropical-fruit tree crop that is the source of chocolate.
        This assembly corresponds to 76% of the estimated genome size and contains
        almost all previously described genes, with 82% of these genes anchored on
        the 10 T. cacao chromosomes. Analysis of this sequence information highlighted
        specific expansion of some gene families during evolution, for example, flavonoid-related
        genes. It also provides a major source of candidate genes for T. cacao improvement.
        Based on the inferred paleohistory of the T. cacao genome, we propose an evolutionary
        scenario whereby the ten T. cacao chromosomes were shaped from an ancestor
        through eleven chromosome fusions. © 2011 Nature America, Inc. All rights
        reserved.
      authors:
      - name: Argout X.
      - name: Salse J.
      - name: Aury J.-M.
      - name: Guiltinan M.J.
      - name: Droc G.
      - name: Gouzy J.
      - name: Allegre M.
      - name: Chaparro C.
      - name: Legavre T.
      - name: Maximova S.N.
      - name: Abrouk M.
      - name: Murat F.
      - name: Fouet O.
      - name: Poulain J.
      - name: Ruiz M.
      - name: Roguet Y.
      - name: Rodier-Goud M.
      - name: Barbosa-Neto J.F.
      - name: Sabot F.
      - name: Kudrna D.
      - name: Ammiraju J.S.S.
      - name: Schuster S.C.
      - name: Carlson J.E.
      - name: Sallet E.
      - name: Schiex T.
      - name: Dievart A.
      - name: Kramer M.
      - name: Gelley L.
      - name: Shi Z.
      - name: Berard A.
      - name: Viot C.
      - name: Boccara M.
      - name: Risterucci A.M.
      - name: Guignon V.
      - name: Sabau X.
      - name: Axtell M.J.
      - name: Ma Z.
      - name: Zhang Y.
      - name: Brown S.
      - name: Bourge M.
      - name: Golser W.
      - name: Song X.
      - name: Clement D.
      - name: Rivallan R.
      - name: Tahi M.
      - name: Akaza J.M.
      - name: Pitollat B.
      - name: Gramacho K.
      - name: D'Hont A.
      - name: Brunel D.
      - name: Infante D.
      - name: Kebe I.
      - name: Costet P.
      - name: Wing R.
      - name: McCombie W.R.
      - name: Guiderdoni E.
      - name: Quetier F.
      - name: Panaud O.
      - name: Wincker P.
      - name: Bocs S.
      - name: Lanaud C.
      citationCount: 578
      date: '2011-01-01T00:00:00Z'
      journal: Nature Genetics
      title: The genome of Theobroma cacao
    note: null
    pmcid: null
    pmid: '21186351'
    type: []
    version: null
  relation:
  - biotoolsID: southgreen
    type: includedIn
  - biotoolsID: tripal
    type: uses
  - biotoolsID: jbrowse
    type: uses
  toolType:
  - Database portal
  topic:
  - term: Model organisms
    uri: http://edamontology.org/topic_0621
  - term: Transcriptomics
    uri: http://edamontology.org/topic_3308
  - term: Agricultural science
    uri: http://edamontology.org/topic_3810
  - term: Gene expression
    uri: http://edamontology.org/topic_0203
  validated: 0
  version: []
- accessibility: null
  additionDate: '2015-11-09T10:32:46Z'
  biotoolsCURIE: biotools:repeat_explorer
  biotoolsID: repeat_explorer
  collectionID:
  - Czech Republic
  - ELIXIR-CZ
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: null
    fundrefid: null
    gridid: null
    name: Jiri Macas
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Pavel Neumann
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Petr Novak
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Biology Centre, CAS, Czech Republic
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
    - Provider
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: ELIXIR-CZ
    note: null
    orcidid: null
    rorid: null
    typeEntity: Consortium
    typeRole: []
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Czech Academy of Sciences
    note: null
    orcidid: null
    rorid: null
    typeEntity: Funding agency
    typeRole:
    - Contributor
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: ELIXIR-CZ
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
    - Provider
    url: null
  - email: petr@umbr.cas.cz
    fundrefid: null
    gridid: null
    name: Petr Novak
    note: null
    orcidid: null
    rorid: null
    typeEntity: null
    typeRole:
    - Support
    url: null
  - email: petr@umbr.cas.cz
    fundrefid: null
    gridid: null
    name: Petr Novak
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  description: RepeatExplorer is a computational pipeline designed to identify and
    characterize repetitive DNA elements in next-generation sequencing data from plant
    and animal genomes. It employs graph-based clustering of sequence reads to identify
    repetitive elements and several additional programs that aid in their annotation
    and quantification.
  documentation:
  - note: null
    type:
    - Terms of use
    - Citation instructions
    - General
    - User manual
    url: http://repeatexplorer.org
  download:
  - note: null
    type: Source code
    url: https://bitbucket.org/petrnovak/repex_tarean
    version: null
  - note: null
    type: Binaries
    url: https://bitbucket.org/petrnovak/repex_tarean
    version: null
  - note: Galaxy toolshed package
    type: Software package
    url: https://toolshed.g2.bx.psu.edu/view/petr-novak/repeatexplorer2
    version: null
  editPermission:
    authors:
    - kavonrtep
    type: group
  elixirCommunity: []
  elixirNode:
  - Czech Republic
  elixirPlatform:
  - Tools
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Nucleic acid sequence
        uri: http://edamontology.org/data_2977
      format:
      - term: FASTQ
        uri: http://edamontology.org/format_1930
      - term: FASTA
        uri: http://edamontology.org/format_1929
    note: Computational pipeline for discovery and characterization of repetitive
      sequences in eukaryotic genomes. The pipeline uses high-throughput genome sequencing
      data as an input and performs graph-based clustering analysis of sequence read
      similarities to identify repetitive elements within analyzed samples User-provided
      shotgun  sequencing data Characterization of repetitive sequences
    operation:
    - term: Repeat sequence detection
      uri: http://edamontology.org/operation_0379
    - term: Genome annotation
      uri: http://edamontology.org/operation_0362
    output:
    - data:
        term: Sequence search results
        uri: http://edamontology.org/data_0857
      format:
      - term: FASTA-HTML
        uri: http://edamontology.org/format_2310
  homepage: http://repeatexplorer.org
  homepage_status: 0
  language:
  - R
  - Perl
  - Python
  lastUpdate: '2024-11-25T13:58:59.436240Z'
  license: GPL-3.0
  link:
  - note: null
    type:
    - Repository
    url: https://bitbucket.org/petrnovak/repex_tarean
  - note: null
    type:
    - Galaxy service
    url: https://repeatexplorer-elixir.cerit-sc.cz/
  maturity: Mature
  name: RepeatExplorer
  operatingSystem:
  - Linux
  otherID: []
  owner: ELIXIR-CZ
  publication:
  - doi: 10.1186/1471-2105-11-378
    metadata:
      abstract: 'Background: The investigation of plant genome structure and evolution
        requires comprehensive characterization of repetitive sequences that make
        up the majority of higher plant nuclear DNA. Since genome-wide characterization
        of repetitive elements is complicated by their high abundance and diversity,
        novel approaches based on massively-parallel sequencing are being adapted
        to facilitate the analysis. It has recently been demonstrated that the low-pass
        genome sequencing provided by a single 454 sequencing reaction is sufficient
        to capture information about all major repeat families, thus providing the
        opportunity for efficient repeat investigation in a wide range of species.
        However, the development of appropriate data mining tools is required in order
        to fully utilize this sequencing data for repeat characterization.Results:
        We adapted a graph-based approach for similarity-based partitioning of whole
        genome 454 sequence reads in order to build clusters made of the reads derived
        from individual repeat families. The information about cluster sizes was utilized
        for assessing the proportion and composition of repeats in the genomes of
        two model species, Pisum sativum and Glycine max, differing in genome size
        and 454 sequencing coverage. Moreover, statistical analysis and visual inspection
        of the topology of the cluster graphs using a newly developed program tool,
        SeqGrapheR, were shown to be helpful in distinguishing basic types of repeats
        and investigating sequence variability within repeat families.Conclusions:
        Repetitive regions of plant genomes can be efficiently characterized by the
        presented graph-based analysis and the graph representation of repeats can
        be further used to assess the variability and evolutionary divergence of repeat
        families, discover and characterize novel elements, and aid in subsequent
        assembly of their consensus sequences. © 2010 Novák et al; licensee BioMed
        Central Ltd.'
      authors:
      - name: Novak P.
      - name: Neumann P.
      - name: Macas J.
      citationCount: 346
      date: '2010-07-15T00:00:00Z'
      journal: BMC Bioinformatics
      title: Graph-based clustering and characterization of repetitive sequences in
        next-generation sequencing data
    note: null
    pmcid: PMC2912890
    pmid: '20633259'
    type:
    - Primary
    version: null
  - doi: 10.1093/bioinformatics/btt054
    metadata:
      abstract: 'Motivation: Repetitive DNA makes up large portions of plant and animal
        nuclear genomes, yet it remains the least-characterized genome component in
        most species studied so far. Although the recent availability of high-throughput
        sequencing data provides necessary resources for in-depth investigation of
        genomic repeats, its utility is hampered by the lack of specialized bioinformatics
        tools and appropriate computational resources that would enable large-scale
        repeat analysis to be run by biologically oriented researchers.Results: Here
        we present RepeatExplorer, a collection of software tools for characterization
        of repetitive elements, which is accessible via web interface. A key component
        of the server is the computational pipeline using a graph-based sequence clustering
        algorithm to facilitate de novo repeat identification without the need for
        reference databases of known elements. Because the algorithm uses short sequences
        randomly sampled from the genome as input, it is ideal for analyzing next-generation
        sequence reads. Additional tools are provided to aid in classification of
        identified repeats, investigate phylogenetic relationships of retroelements
        and perform comparative analysis of repeat composition between multiple species.
        The server allows to analyze several million sequence reads, which typically
        results in identification of most high and medium copy repeats in higher plant
        genomes.Implementation and availability: RepeatExplorer was implemented within
        the Galaxy environment and set up on a public server at http://repeatexplorer.umbr.cas.cz/.
        Source code and instructions for local installation are available at http://w3lamc.umbr.cas.cz/
        lamc/resources.php.Contact: © 2013 The Author 2013. Published by Oxford University
        Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
        © The Author 2013.'
      authors:
      - name: Novak P.
      - name: Neumann P.
      - name: Pech J.
      - name: Steinhaisl J.
      - name: MacAs J.
      citationCount: 523
      date: '2013-03-01T00:00:00Z'
      journal: Bioinformatics
      title: 'RepeatExplorer: A Galaxy-based web server for genome-wide characterization
        of eukaryotic repetitive elements from next-generation sequence reads'
    note: null
    pmcid: null
    pmid: '23376349'
    type: []
    version: null
  relation: []
  toolType:
  - Command-line tool
  - Web application
  topic:
  - term: DNA polymorphism
    uri: http://edamontology.org/topic_2885
  - term: Mobile genetic elements
    uri: http://edamontology.org/topic_0798
  validated: 1
  version:
  - 2.3.7 (Galaxy server)
  - 0.3.7 (command line)
- accessibility: Open access
  additionDate: '2017-03-30T13:34:34Z'
  biotoolsCURIE: biotools:jphyloio
  biotoolsID: jphyloio
  collectionID: []
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: null
    fundrefid: null
    gridid: null
    name: Ben C. Stöver
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: http://bioinfweb.info/People/Stoever
  - email: wiechers@bioinfweb.info
    fundrefid: null
    gridid: null
    name: Sarah Wiechers
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: null
  - email: kaimueller@uni-muenster.de
    fundrefid: null
    gridid: null
    name: Kai F. Müller
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Contributor
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: bioinfweb
    note: null
    orcidid: null
    rorid: null
    typeEntity: Project
    typeRole:
    - Maintainer
    url: http://bioinfweb.info/
  - email: null
    fundrefid: null
    gridid: null
    name: DFG (German Research Foundation)
    note: null
    orcidid: null
    rorid: null
    typeEntity: Funding agency
    typeRole: []
    url: http://www.dfg.de/
  - email: null
    fundrefid: null
    gridid: null
    name: Ben C. Stöver
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: http://bioinfweb.info/People/Stoever
  description: An open source Java library for reading and writing various tree and
    alignment formats. Application developers are able to implement format-independent
    data processing by including event based readers via the abstract strategy pattern.
    All readers are designed to deal with large amounts of data (alignments with many
    and/or very long sequences, large trees) without using a great amount of resources
    (CPU or RAM).
  documentation:
  - note: null
    type:
    - General
    url: http://bioinfweb.info/JPhyloIO/Documentation
  - note: null
    type:
    - API documentation
    url: http://bioinfweb.info/JPhyloIO/Documentation/API/Latest/
  - note: null
    type:
    - Training material
    url: http://bioinfweb.info/JPhyloIO/Documentation/Demos
  - note: null
    type:
    - Terms of use
    url: http://bioinfweb.info/JPhyloIO/License
  download:
  - note: null
    type: Software package
    url: http://bioinfweb.info/JPhyloIO/Download
    version: null
  - note: null
    type: Software package
    url: http://bioinfweb.info/JPhyloIO/Download
    version: null
  - note: null
    type: API specification
    url: http://bioinfweb.info/JPhyloIO/Download
    version: null
  editPermission:
    authors:
    - BenStoever
    type: group
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Taxonomy
        uri: http://edamontology.org/data_3028
      format:
      - term: Nexus format
        uri: http://edamontology.org/format_1912
      - term: phyloXML
        uri: http://edamontology.org/format_3159
      - term: NeXML
        uri: http://edamontology.org/format_3160
    - data:
        term: Phylogenetic tree
        uri: http://edamontology.org/data_0872
      format:
      - term: XML
        uri: http://edamontology.org/format_2332
      - term: Nexus format
        uri: http://edamontology.org/format_1912
      - term: phyloXML
        uri: http://edamontology.org/format_3159
      - term: newick
        uri: http://edamontology.org/format_1910
      - term: NeXML
        uri: http://edamontology.org/format_3160
    - data:
        term: Alignment
        uri: http://edamontology.org/data_1916
      format:
      - term: Nexus format
        uri: http://edamontology.org/format_1912
      - term: mega
        uri: http://edamontology.org/format_1991
      - term: FASTA
        uri: http://edamontology.org/format_1929
      - term: XML
        uri: http://edamontology.org/format_2332
      - term: NeXML
        uri: http://edamontology.org/format_3160
      - term: PHYLIP format
        uri: http://edamontology.org/format_1997
    note: 'Input of type "XML" for phylogenetic trees refers to "XTG" (http://bioinfweb.info/xmlns/xtg
      )

      Input of type XML for alignment refers to "PDE" the alignment formats of PhyDE
      (http://phyde.de/ )'
    operation:
    - term: Loading
      uri: http://edamontology.org/operation_1812
    - term: Data handling
      uri: http://edamontology.org/operation_2409
    - term: Format detection
      uri: http://edamontology.org/operation_3357
    output:
    - data:
        term: Taxonomy
        uri: http://edamontology.org/data_3028
      format:
      - term: Nexus format
        uri: http://edamontology.org/format_1912
      - term: phyloXML
        uri: http://edamontology.org/format_3159
      - term: NeXML
        uri: http://edamontology.org/format_3160
    - data:
        term: Alignment
        uri: http://edamontology.org/data_1916
      format:
      - term: Nexus format
        uri: http://edamontology.org/format_1912
      - term: NeXML
        uri: http://edamontology.org/format_3160
      - term: PHYLIP format
        uri: http://edamontology.org/format_1997
      - term: FASTA
        uri: http://edamontology.org/format_1929
    - data:
        term: Phylogenetic tree
        uri: http://edamontology.org/data_0872
      format:
      - term: Nexus format
        uri: http://edamontology.org/format_1912
      - term: phyloXML
        uri: http://edamontology.org/format_3159
      - term: newick
        uri: http://edamontology.org/format_1910
      - term: NeXML
        uri: http://edamontology.org/format_3160
  homepage: http://bioinfweb.info/JPhyloIO/
  homepage_status: 0
  language:
  - Java
  lastUpdate: '2024-11-25T13:48:04.710657Z'
  license: LGPL-3.0
  link:
  - note: null
    type:
    - Social media
    url: https://twitter.com/bioinfweb
  - note: null
    type:
    - Repository
    url: https://github.com/bioinfweb/JPhyloIO
  - note: null
    type:
    - Repository
    url: http://bioinfweb.info/Code/sventon/repos/JPhyloIO/list/
  maturity: Emerging
  name: JPhyloIO
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: cbs_admin
  publication:
  - doi: 10.1093/database/bav094
    metadata:
      abstract: 'We present the model and implementation of a workflow that blazes
        a trail in systematic biology for the re-usability of character data (data
        on any kind of characters of phenoand genotypes of organisms) and their additivity
        from specimen to taxon level. We take into account that any taxon characterization
        is based on a limited set of sampled individuals and characters, and that
        consequently any new individual and any new character may affect the recognition
        of biological entities and/or the subsequent delimitation and characterization
        of a taxon. Taxon concepts thus frequently change during the knowledge generation
        process in systematic biology. Structured character data are therefore not
        only needed for the knowledge generation process but also for easily adapting
        characterizations of taxa. We aim to facilitate the construction and reproducibility
        of taxon characterizations from structured character data of changing sample
        sets by establishing a stable and unambiguous association between each sampled
        individual and the data processed from it. Our workflow implementation uses
        the European Distributed Institute of Taxonomy Platform, a comprehensive taxonomic
        data management and publication environment to: (i) establish a reproducible
        connection between sampled individuals and all samples derived from them;
        (ii) stably link sample-based character data with the metadata of the respective
        samples; (iii) record and store structured specimen-based character data in
        formats allowing data exchange; (iv) reversibly assign sample metadata and
        character datasets to taxa in an editable classification and display them
        and (v) organize data exchange via standard exchange formats and enable the
        link between the character datasets and samples in research collections, ensuring
        high visibility and instant reusability of the data. The workflow implemented
        will contribute to organizing the interface between phylogenetic analysis
        and revisionary taxonomic or monographic work.'
      authors:
      - name: Kilian N.
      - name: Henning T.
      - name: Plitzner P.
      - name: Muller A.
      - name: Guntsch A.
      - name: Stover B.C.
      - name: Muller K.F.
      - name: Berendsohn W.G.
      - name: Borsch T.
      citationCount: 18
      date: '2015-01-01T00:00:00Z'
      journal: Database
      title: Sample data processing in an additive and reproducible taxonomic workflow
        by using character data persistently linked to preserved individual specimens
    note: null
    pmcid: PMC4589695
    pmid: '26424081'
    type:
    - Other
    version: null
  relation: []
  toolType:
  - Library
  topic:
  - term: Biology
    uri: http://edamontology.org/topic_3070
  - term: Phylogenetics
    uri: http://edamontology.org/topic_3293
  - term: Computational biology
    uri: http://edamontology.org/topic_3307
  validated: 1
  version:
  - 0.5.4
- accessibility: Open access
  additionDate: '2016-02-18T22:34:41Z'
  biotoolsCURIE: biotools:open_phacts_api
  biotoolsID: open_phacts_api
  collectionID: []
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: null
    fundrefid: null
    gridid: null
    name: Open PHACTS Foundation
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
    - Provider
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: OpenLink Software
    note: null
    orcidid: null
    rorid: null
    typeEntity: Consortium
    typeRole: []
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Innovative Medicines Initiative (IMI)
    note: null
    orcidid: null
    rorid: null
    typeEntity: Funding agency
    typeRole:
    - Contributor
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: cs.manchester.ac.uk
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
    - Provider
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Open PHACTS contact
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: https://dev.openphacts.org/contact
  - email: support@openphacts.org
    fundrefid: null
    gridid: null
    name: Open PHACTS support portal
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: http://support.openphacts.org/support/home
  description: Open PHACTS Discovery Platform brings together data from multiple publicly
    available sources of pharmacological and physicochemical information, in order
    to streamline research and drug discovery processes. The data is integrated into
    a consolidated triple store, which can be accessed via applications or workflow
    tools which make use of the Open PHACTS API.
  documentation:
  - note: null
    type:
    - Terms of use
    url: https://www.openphacts.org/2/sci/data.html
  - note: null
    type:
    - Citation instructions
    url: https://dev.openphacts.org/contact
  - note: null
    type:
    - General
    url: https://dev.openphacts.org/docs/2.0
  download:
  - note: null
    type: Source code
    url: http://data.openphacts.org/
    version: null
  - note: Docker Compose setup
    type: Container file
    url: https://github.com/openphacts/ops-docker
    version: null
  editPermission:
    authors: []
    type: private
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Database search
      uri: http://edamontology.org/operation_2421
    - term: Data retrieval
      uri: http://edamontology.org/operation_2422
    - term: Structural similarity search
      uri: http://edamontology.org/operation_0360
    output: []
  homepage: https://dev.openphacts.org/docs/2.1
  homepage_status: 0
  language: []
  lastUpdate: '2024-11-25T13:46:36.750725Z'
  license: CC-BY-3.0
  link:
  - note: null
    type:
    - Repository
    url: http://github.com/openphacts/
  - note: null
    type:
    - Helpdesk
    url: http://support.openphacts.org/support/home
  maturity: Mature
  name: Open PHACTS API
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: soiland-reyes@cs.manchester.ac
  publication:
  - doi: 10.3233/SW-2012-0088
    metadata:
      abstract: The discovery of new medicines requires pharmacologists to interact
        with a number of information sources ranging from tabular data to scientific
        papers, and other specialized formats. In this application report, we describe
        a linked data platform for integrating multiple pharmacology datasets that
        form the basis for several drug discovery applications. The functionality
        offered by the platform has been drawn from a collection of prioritised drug
        discovery business questions created as part of the Open PHACTS project, a
        collaboration of research institutions and major pharmaceutical companies.
        We describe the architecture of the platform focusing on seven design decisions
        that drove its development with the aim of informing others developing similar
        software in this or other domains. The utility of the platform is demonstrated
        by the variety of drug discovery applications being built to access the integrated
        data. An alpha version of the OPS platform is currently available to the Open
        PHACTS consortium and a first public release will be made in late 2012, see
        http://www.openphacts.org/ for details. © 2014 - IOS Press and the authors.
      authors:
      - name: Gray A.J.G.
      - name: Groth P.
      - name: Loizou A.
      - name: Askjaer S.
      - name: Brenninkmeijer C.
      - name: Burger K.
      - name: Chichester C.
      - name: Evelo C.T.
      - name: Goble C.
      - name: Harland L.
      - name: Pettifer S.
      - name: Thompson M.
      - name: Waagmeester A.
      - name: Williams A.J.
      citationCount: 49
      date: '2014-01-01T00:00:00Z'
      journal: Semantic Web
      title: 'Applying linked data approaches to pharmacology: Architectural decisions
        and implementation'
    note: null
    pmcid: null
    pmid: null
    type:
    - Other
    version: null
  - doi: 10.1016/j.drudis.2012.05.016
    metadata:
      abstract: Open PHACTS is a public-private partnership between academia, publishers,
        small and medium sized enterprises and pharmaceutical companies. The goal
        of the project is to deliver and sustain an 'open pharmacological space' using
        and enhancing state-of-the-art semantic web standards and technologies. It
        is focused on practical and robust applications to solve specific questions
        in drug discovery research. OPS is intended to facilitate improvements in
        drug discovery in academia and industry and to support open innovation and
        in-house non-public drug discovery research. This paper lays out the challenges
        and how the Open PHACTS project is hoping to address these challenges technically
        and socially. © 2012 Elsevier Ltd.
      authors:
      - name: Williams A.J.
      - name: Harland L.
      - name: Groth P.
      - name: Pettifer S.
      - name: Chichester C.
      - name: Willighagen E.L.
      - name: Evelo C.T.
      - name: Blomberg N.
      - name: Ecker G.
      - name: Goble C.
      - name: Mons B.
      citationCount: 260
      date: '2012-11-01T00:00:00Z'
      journal: Drug Discovery Today
      title: 'Open PHACTS: Semantic interoperability for drug discovery'
    note: null
    pmcid: null
    pmid: '22683805'
    type:
    - Other
    version: null
  relation: []
  toolType:
  - Web API
  topic:
  - term: Compound libraries and screening
    uri: http://edamontology.org/topic_3343
  - term: Computational chemistry
    uri: http://edamontology.org/topic_3332
  - term: Drug discovery
    uri: http://edamontology.org/topic_3336
  validated: 1
  version:
  - '2.1'
- accessibility: Open access
  additionDate: '2019-10-30T13:51:32Z'
  biotoolsCURIE: biotools:Banana_Genome_Hub
  biotoolsID: Banana_Genome_Hub
  collectionID:
  - Genome Hub
  - elixir-fr-sdp-2019
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: gaetan.droc@cirad.fr
    fundrefid: null
    gridid: null
    name: Gaëtan Droc
    note: null
    orcidid: https://orcid.org/0000-0003-1849-1269
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: null
  - email: m.rouard@cgiar.org
    fundrefid: null
    gridid: null
    name: Mathieu Rouard
    note: null
    orcidid: https://orcid.org/0000-0003-1849-1269
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: CIRAD
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
    - Maintainer
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Bioversity International
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole: []
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: ANR
    note: null
    orcidid: null
    rorid: null
    typeEntity: Funding agency
    typeRole: []
    url: null
  description: A Next-Generation Information System for Musa genomics
  documentation:
  - note: null
    type:
    - Terms of use
    url: https://banana-genome-hub.southgreen.fr/termofservices
  - note: null
    type:
    - API documentation
    url: http://api.tripal.info/api/tripal/2.x
  - note: null
    type:
    - General
    url: https://banana-genome-hub.southgreen.fr/documentation
  download:
  - note: null
    type: Biological data
    url: https://banana-genome-hub.southgreen.fr/download
    version: null
  editPermission:
    authors:
    - gdroc
    - mrouard
    type: group
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  elixirNode:
  - France
  elixirPlatform:
  - Tools
  - Data
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Keyword
        uri: http://edamontology.org/data_0968
      format:
      - term: Textual format
        uri: http://edamontology.org/format_2330
    - data:
        term: Sequence
        uri: http://edamontology.org/data_2044
      format:
      - term: Textual format
        uri: http://edamontology.org/format_2330
    note: null
    operation:
    - term: Sequence analysis
      uri: http://edamontology.org/operation_2403
    - term: Genome visualisation
      uri: http://edamontology.org/operation_3208
    - term: Sequence database search
      uri: http://edamontology.org/operation_0338
    output:
    - data:
        term: Sequence alignment
        uri: http://edamontology.org/data_0863
      format: []
    - data:
        term: Sequence
        uri: http://edamontology.org/data_2044
      format: []
  homepage: https://banana-genome-hub.southgreen.fr/
  homepage_status: 0
  language:
  - PHP
  - JavaScript
  lastUpdate: '2024-11-24T20:59:38.690746Z'
  license: GPL-2.0
  link:
  - note: null
    type:
    - Helpdesk
    - Mailing list
    url: https://banana-genome-hub.southgreen.fr/contact
  - note: null
    type:
    - Issue tracker
    url: https://github.com/SouthGreenPlatform/genomehubs
  maturity: Mature
  name: Banana Genome Hub
  operatingSystem: []
  otherID: []
  owner: admin
  publication:
  - doi: 10.1093/database/bat035
    metadata:
      abstract: Banana is one of the world's favorite fruits and one of the most important
        crops for developing countries. The banana reference genome sequence (Musa
        acuminata) was recently released. Given the taxonomic position of Musa, the
        completed genomic sequence has particular comparative value to provide fresh
        insights about the evolution of the monocotyledons. The study of the banana
        genome has been enhanced by a number of tools and resources that allows harnessing
        its sequence. First, we set up essential tools such as a Community Annotation
        System, phylogenomics resources and metabolic pathways. Then, to support post-genomic
        efforts, we improved banana existing systems (e.g. web front end, query builder),
        we integrated available Musa data into generic systems (e.g. markers and genetic
        maps, synteny blocks), we have made interoperable with the banana hub, other
        existing systems containing Musa data (e.g. transcriptomics, rice reference
        genome, workflow manager) and finally, we generated new results from sequence
        analyses (e.g. SNP and polymorphism analysis). Several uses cases illustrate
        how the Banana Genome Hub can be used to study gene families. Overall, with
        this collaborative effort, we discuss the importance of the interoperability
        toward data integration between existing information systems. © The Author(s)
        2013. Published by Oxford University Press.
      authors:
      - name: Droc G.
      - name: Lariviere D.
      - name: Guignon V.
      - name: Yahiaoui N.
      - name: This D.
      - name: Garsmeur O.
      - name: Dereeper A.
      - name: Hamelin C.
      - name: Argout X.
      - name: Dufayard J.-F.
      - name: Lengelle J.
      - name: Baurens F.-C.
      - name: Cenci A.
      - name: Pitollat B.
      - name: D'Hont A.
      - name: Ruiz M.
      - name: Rouard M.
      - name: Bocs S.
      citationCount: 140
      date: '2013-12-01T00:00:00Z'
      journal: Database
      title: The banana genome hub
    note: null
    pmcid: PMC3662865
    pmid: '23707967'
    type: []
    version: null
  - doi: 10.1038/nature11241
    metadata:
      abstract: Bananas (Musa spp.), including dessert and cooking types, are giant
        perennial monocotyledonous herbs of the order Zingiberales, a sister group
        to the well-studied Poales, which include cereals. Bananas are vital for food
        security in many tropical and subtropical countries and the most popular fruit
        in industrialized countries. The Musa domestication process started some 7,000
        years ago in Southeast Asia. It involved hybridizations between diverse species
        and subspecies, fostered by human migrations, and selection of diploid and
        triploid seedless, parthenocarpic hybrids thereafter widely dispersed by vegetative
        propagation. Half of the current production relies on somaclones derived from
        a single triploid genotype (Cavendish). Pests and diseases have gradually
        become adapted, representing an imminent danger for global banana production.
        Here we describe the draft sequence of the 523-megabase genome of a Musa acuminata
        doubled-haploid genotype, providing a crucial stepping-stone for genetic improvement
        of banana. We detected three rounds of whole-genome duplications in the Musa
        lineage, independently of those previously described in the Poales lineage
        and the one we detected in the Arecales lineage. This first monocotyledon
        high-continuity whole-genome sequence reported outside Poales represents an
        essential bridge for comparative genome analysis in plants. As such, it clarifies
        commelinid-monocotyledon phylogenetic relationships, reveals Poaceae-specific
        features and has led to the discovery of conserved non-coding sequences predating
        monocotyledon-eudicotyledon divergence. © 2012 Macmillan Publishers Limited.
        All rights reserved.
      authors:
      - name: D'hont A.
      - name: Denoeud F.
      - name: Aury J.-M.
      - name: Baurens F.-C.
      - name: Carreel F.
      - name: Garsmeur O.
      - name: Noel B.
      - name: Bocs S.
      - name: Droc G.
      - name: Rouard M.
      - name: Da Silva C.
      - name: Jabbari K.
      - name: Cardi C.
      - name: Poulain J.
      - name: Souquet M.
      - name: Labadie K.
      - name: Jourda C.
      - name: Lengelle J.
      - name: Rodier-Goud M.
      - name: Alberti A.
      - name: Bernard M.
      - name: Correa M.
      - name: Ayyampalayam S.
      - name: Mckain M.R.
      - name: Leebens-Mack J.
      - name: Burgess D.
      - name: Freeling M.
      - name: Mbeguie-A-Mbeguie D.
      - name: Chabannes M.
      - name: Wicker T.
      - name: Panaud O.
      - name: Barbosa J.
      - name: Hribova E.
      - name: Heslop-Harrison P.
      - name: Habas R.
      - name: Rivallan R.
      - name: Francois P.
      - name: Poiron C.
      - name: Kilian A.
      - name: Burthia D.
      - name: Jenny C.
      - name: Bakry F.
      - name: Brown S.
      - name: Guignon V.
      - name: Kema G.
      - name: Dita M.
      - name: Waalwijk C.
      - name: Joseph S.
      - name: Dievart A.
      - name: Jaillon O.
      - name: Leclercq J.
      - name: Argout X.
      - name: Lyons E.
      - name: Almeida A.
      - name: Jeridi M.
      - name: Dolezel J.
      - name: Roux N.
      - name: Risterucci A.-M.
      - name: Weissenbach J.
      - name: Ruiz M.
      - name: Glaszmann J.-C.
      - name: Quetier F.
      - name: Yahiaoui N.
      - name: Wincker P.
      citationCount: 918
      date: '2012-08-09T00:00:00Z'
      journal: Nature
      title: The banana (Musa acuminata) genome and the evolution of monocotyledonous
        plants
    note: null
    pmcid: null
    pmid: '22801500'
    type: []
    version: null
  relation:
  - biotoolsID: southgreen
    type: includedIn
  - biotoolsID: tripal
    type: uses
  toolType:
  - Database portal
  topic:
  - term: Model organisms
    uri: http://edamontology.org/topic_0621
  - term: Genomics
    uri: http://edamontology.org/topic_0622
  - term: Transcriptomics
    uri: http://edamontology.org/topic_3308
  - term: Agricultural science
    uri: http://edamontology.org/topic_3810
  - term: Comparative genomics
    uri: http://edamontology.org/topic_0797
  validated: 0
  version:
  - v2
- accessibility: Open access
  additionDate: '2019-11-05T13:33:45Z'
  biotoolsCURIE: biotools:Ocean_Gene_Atlas
  biotoolsID: Ocean_Gene_Atlas
  collectionID:
  - elixir-fr-sdp-2019
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: oceangeneatlas@mio.osupytheas.fr
    fundrefid: null
    gridid: null
    name: null
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: http://tara-oceans.mio.osupytheas.fr/ocean-gene-atlas/credits
  - email: null
    fundrefid: null
    gridid: null
    name: MIO
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
    - Provider
    url: https://www.mio.osupytheas.fr/
  - email: null
    fundrefid: null
    gridid: null
    name: OCEANOMICS
    note: ANR-11-BTBR-0008
    orcidid: null
    rorid: null
    typeEntity: Funding agency
    typeRole: []
    url: http://www.oceanomics.eu/
  description: 'The Ocean Gene Atlas service provides data mining access to three
    complementary data objects: gene sequence catalogs (ENA), sample environmental
    context (PANGAEA), and gene abundances estimates in samples (computed by mapping
    sequence reads onto gene catalogs).

    User queries are composed of either a sequence (nucleic or protein), or a hidden
    Markov model derived from a multiple sequence alignment. Homologs of the user
    query in the gene catalogs are identified using standard sequence similarity search
    tools (eg BLAST or HMMER), and their read based estimated abundance are displayed
    in interactive maps and plots. A phylogenetic tree is also inferred in order to
    situate the user query within its context of marine environmental homologs as
    well as known homologs from reference sequences.'
  documentation:
  - note: null
    type:
    - User manual
    - API documentation
    url: http://tara-oceans.mio.osupytheas.fr/ocean-gene-atlas/build/pdf/Ocean-Gene-Atlas_User_Manual.pdf
  - note: null
    type:
    - Terms of use
    url: http://tara-oceans.mio.osupytheas.fr/ocean-gene-atlas/termsOfUse
  download: []
  editPermission:
    authors:
    - lescot
    - vernette.c
    type: group
  elixirCommunity: []
  elixirNode:
  - France
  elixirPlatform:
  - Tools
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Nucleic acid sequence
        uri: http://edamontology.org/data_2977
      format:
      - term: JSON
        uri: http://edamontology.org/format_3464
      - term: FASTA
        uri: http://edamontology.org/format_1929
    - data:
        term: Protein sequence
        uri: http://edamontology.org/data_2976
      format:
      - term: JSON
        uri: http://edamontology.org/format_3464
      - term: FASTA
        uri: http://edamontology.org/format_1929
    - data:
        term: Hidden Markov model
        uri: http://edamontology.org/data_1364
      format:
      - term: HMMER format
        uri: http://edamontology.org/format_1370
    - data:
        term: Pfam accession number
        uri: http://edamontology.org/data_1138
      format:
      - term: JSON
        uri: http://edamontology.org/format_3464
      - term: Textual format
        uri: http://edamontology.org/format_2330
    - data:
        term: Gene ID
        uri: http://edamontology.org/data_2295
      format:
      - term: Textual format
        uri: http://edamontology.org/format_2330
    note: null
    operation:
    - term: Quantification
      uri: http://edamontology.org/operation_3799
    - term: Phylogenetic tree visualisation
      uri: http://edamontology.org/operation_0567
    - term: Map drawing
      uri: http://edamontology.org/operation_0573
    - term: Phylogenetic tree reconstruction
      uri: http://edamontology.org/operation_3478
    - term: Sequence alignment
      uri: http://edamontology.org/operation_0292
    output:
    - data:
        term: Sequence alignment
        uri: http://edamontology.org/data_0863
      format:
      - term: FASTA-aln
        uri: http://edamontology.org/format_1984
    - data:
        term: Nucleic acid sequence
        uri: http://edamontology.org/data_2977
      format:
      - term: FASTA
        uri: http://edamontology.org/format_1929
    - data:
        term: Protein sequence
        uri: http://edamontology.org/data_2976
      format:
      - term: FASTA
        uri: http://edamontology.org/format_1929
    - data:
        term: Phylogenetic tree
        uri: http://edamontology.org/data_0872
      format:
      - term: newick
        uri: http://edamontology.org/format_1910
    - data:
        term: Sequence search results
        uri: http://edamontology.org/data_0857
      format:
      - term: BLAST results
        uri: http://edamontology.org/format_1333
    - data:
        term: Ecological data
        uri: http://edamontology.org/data_3736
      format:
      - term: CSV
        uri: http://edamontology.org/format_3752
    - data:
        term: Plot
        uri: http://edamontology.org/data_2884
      format:
      - term: HTML
        uri: http://edamontology.org/format_2331
    - data:
        term: Image
        uri: http://edamontology.org/data_2968
      format:
      - term: PNG
        uri: http://edamontology.org/format_3603
      - term: JPG
        uri: http://edamontology.org/format_3579
      - term: SVG
        uri: http://edamontology.org/format_3604
      - term: PDF
        uri: http://edamontology.org/format_3508
  homepage: http://tara-oceans.mio.osupytheas.fr/ocean-gene-atlas/
  homepage_status: 0
  language:
  - PHP
  - JavaScript
  lastUpdate: '2024-11-24T20:59:34.208631Z'
  license: Not licensed
  link: []
  maturity: Mature
  name: Ocean Gene Atlas
  operatingSystem: []
  otherID: []
  owner: lescot
  publication:
  - doi: 10.1093/nar/gky376
    metadata:
      abstract: 'The Ocean Gene Atlas is a web service to explore the biogeography
        of genes from marine planktonic organisms. It allows users to query protein
        or nucleotide sequences against global ocean reference gene catalogs. With
        just one click, the abundance and location of target sequences are visualized
        on world maps as well as their taxonomic distribution. Interactive results
        panels allow for adjusting cutoffs for alignment quality and displaying the
        abundances of genes in the context of environmental features (temperature,
        nutrients, etc.) measured at the time of sampling. The ease of use enables
        non-bioinformaticians to explore quantitative and contextualized information
        on genes of interest in the global ocean ecosystem. Currently the Ocean Gene
        Atlas is deployed with (i) the Ocean Microbial Reference Gene Catalog (OM-RGC)
        comprising 40 million non-redundant mostly prokaryotic gene sequences associated
        with both Tara Oceans and Global Ocean Sampling (GOS) gene abundances and
        (ii) the Marine Atlas of Tara Ocean Unigenes (MATOU) composed of >116 million
        eukaryote unigenes. Additional datasets will be added upon availability of
        further marine environmental datasets that provide the required complement
        of sequence assemblies, raw reads and contextual environmental parameters.
        Ocean Gene Atlas is a freely-available web service at: http://tara-oceans.mio.osupytheas.fr/ocean-gene-atlas/.'
      authors:
      - name: Villar E.
      - name: Vannier T.
      - name: Vernette C.
      - name: Lescot M.
      - name: Cuenca M.
      - name: Alexandre A.
      - name: Bachelerie P.
      - name: Rosnet T.
      - name: Pelletier E.
      - name: Sunagawa S.
      - name: Hingamp P.
      citationCount: 103
      date: '2018-07-02T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'The Ocean Gene Atlas: Exploring the biogeography of plankton genes online'
    note: null
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    pmid: '29788376'
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    version: null
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  topic:
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  - term: Marine biology
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  - term: Metagenomics
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  - term: Metatranscriptomics
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  validated: 0
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  description: Large MSAs visualization interactively on the web.
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      - term: FASTA-aln
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    note: 'Visualizes multiple sequence alignment, calculates conservation, shows
      sequence logo, applies multiple color schemes A multiple sequence alignment
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      Images are exported in PNG Export sequences in FASTA format Export features
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      NOTE: Actually, all these output types of data should instead be under separate
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      perhaps without an output.'
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    metadata:
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      citationCount: 125
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        alignments'
    note: null
    pmcid: PMC5181560
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    version: null
  relation: []
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  validated: 1
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  description: Provides a direct access to MOLE functionality and enables on-line
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    input:
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        uri: http://edamontology.org/format_1476
    note: Identification of channels, tunnels, voids and pores within PDB structure.
      User-prepared PDB file Either PDB file or structural assemblies Interactive
      visualisation Annotated PDB file with calculated channels
    operation:
    - term: Protein structural motif recognition
      uri: http://edamontology.org/operation_0245
    - term: Surface rendering
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    - term: Structure visualisation
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  language:
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  maturity: Mature
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  publication:
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    metadata:
      abstract: Biomolecular channels play important roles in many biological systems,
        e.g. enzymes, ribosomes and ion channels. This article introduces a web-based
        interactive MOLEonline 2.0 application for the analysis of access/egress paths
        to interior molecular voids. MOLEonline 2.0 enables platform-independent,
        easy-to-use and interactive analyses of (bio)macromolecular channels, tunnels
        and pores. Results are presented in a clear manner, making their interpretation
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        when performing a channel search to direct the search according to their needs.
        The MOLEonline 2.0 application is freely available via the Internet at http://ncbr.muni.cz/mole
        or http://mole.upol.cz. © 2012 The Author(s).
      authors:
      - name: Berka K.
      - name: Hanak O.
      - name: Sehnal D.
      - name: Banas P.
      - name: Navratilova V.
      - name: Jaiswal D.
      - name: Ionescu C.-M.
      - name: Svobodova Varekova R.
      - name: Koca J.
      - name: Otyepka M.
      citationCount: 108
      date: '2012-07-01T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'MOLEonline 2.0: Interactive web-based analysis of biomacromolecular
        channels'
    note: null
    pmcid: PMC3394309
    pmid: '22553366'
    type:
    - Primary
    version: null
  - doi: 10.1093/nar/gky309
    metadata:
      abstract: 'MOLEonline is an interactive, web-based application for the detection
        and characterization of channels (pores and tunnels) within biomacromolecular
        structures. The updated version of MOLEonline overcomes limitations of the
        previous version by incorporating the recently developed LiteMol Viewer visualization
        engine and providing a simple, fully interactive user experience. The application
        enables two modes of calculation: one is dedicated to the analysis of channels
        while the other was specifically designed for transmembrane pores. As the
        application can use both PDB and mmCIF formats, it can be leveraged to analyze
        a wide spectrum of biomacromolecular structures, e.g. stemming from NMR, X-ray
        and cryo-EM techniques. The tool is interconnected with other bioinformatics
        tools (e.g., PDBe, CSA, ChannelsDB, OPM, UniProt) to help both setup and the
        analysis of acquired results. MOLEonline provides unprecedented analytics
        for the detection and structural characterization of channels, as well as
        information about their numerous physicochemical features. Here we present
        the application of MOLE online for structural analyses of α-hemolysin and
        transient receptor potential mucolipin 1 (TRMP1) pores.'
      authors:
      - name: Pravda L.
      - name: Sehnal D.
      - name: Tousek D.
      - name: Navratilova V.
      - name: Bazgier V.
      - name: Berka K.
      - name: Varekova R.S.
      - name: Koca J.
      - name: Otyepka M.
      citationCount: 186
      date: '2018-07-02T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'MOLEonline: A web-based tool for analyzing channels, tunnels and pores
        (2018 update)'
    note: null
    pmcid: PMC6030847
    pmid: '29718451'
    type: []
    version: null
  relation: []
  toolType:
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  topic:
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    uri: http://edamontology.org/topic_0123
  - term: Protein interactions
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  - term: Enzymes
    uri: http://edamontology.org/topic_0821
  - term: Membrane and lipoproteins
    uri: http://edamontology.org/topic_0820
  - term: Protein structural motifs and surfaces
    uri: http://edamontology.org/topic_0166
  validated: 1
  version:
  - '3.0'
- accessibility: null
  additionDate: '2016-02-04T15:55:00Z'
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  description: Open source data warehouse built specifically for the integration and
    analysis of complex biological data. It enables the creation of biological databases
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    note: null
    operation:
    - term: Database search
      uri: http://edamontology.org/operation_2421
    output:
    - data:
        term: Pathway or network
        uri: http://edamontology.org/data_2600
      format:
      - term: Textual format
        uri: http://edamontology.org/format_2330
  homepage: http://www.intermine.org
  homepage_status: 0
  language:
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  - Ruby
  - Java
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  - JavaScript
  - Perl
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  name: InterMine
  operatingSystem:
  - Linux
  - Mac
  otherID: []
  owner: InterMine
  publication:
  - doi: 10.1093/bioinformatics/bts577
    metadata:
      abstract: InterMine is an open-source data warehouse system that facilitates
        the building of databases with complex data integration requirements and a
        need for a fast customizable query facility. Using InterMine, large biological
        databases can be created from a range of heterogeneous data sources, and the
        extensible data model allows for easy integration of new data types. The analysis
        tools include a flexible query builder, genomic region search and a library
        of 'widgets' performing various statistical analyses. The results can be exported
        in many commonly used formats. InterMine is a fully extensible framework where
        developers can add new tools and functionality. Additionally, there is a comprehensive
        set of web services, for which client libraries are provided in five commonly
        used programming languages. © The Author 2012. Published by Oxford University
        Press. All rights reserved.
      authors:
      - name: Smith R.N.
      - name: Aleksic J.
      - name: Butano D.
      - name: Carr A.
      - name: Contrino S.
      - name: Hu F.
      - name: Lyne M.
      - name: Lyne R.
      - name: Kalderimis A.
      - name: Rutherford K.
      - name: Stepan R.
      - name: Sullivan J.
      - name: Wakeling M.
      - name: Watkins X.
      - name: Micklem G.
      citationCount: 202
      date: '2012-12-01T00:00:00Z'
      journal: Bioinformatics
      title: 'InterMine: A flexible data warehouse system for the integration and
        analysis of heterogeneous biological data'
    note: null
    pmcid: PMC3516146
    pmid: '23023984'
    type:
    - Primary
    version: null
  - doi: 10.1093/nar/gku301
    metadata:
      abstract: 'InterMine (www.intermine.org) is a biological data warehousing system
        providing extensive automatically generated and configurable RESTful web services
        that underpin the web interface and can be re-used in many other applications:
        to find and filter data; export it in a flexible and structured way; to upload,
        use, manipulate and analyze lists; to provide services for flexible retrieval
        of sequence segments, and for other statistical and analysis tools. Here we
        describe these features and discuss how they can be used separately or in
        combinations to support integrative and comparative analysis. © 2014 The Author(s).'
      authors:
      - name: Kalderimis A.
      - name: Lyne R.
      - name: Butano D.
      - name: Contrino S.
      - name: Lyne M.
      - name: Heimbach J.
      - name: Hu F.
      - name: Smith R.
      - name: Stepan R.
      - name: Sullivan J.
      - name: Micklem G.
      citationCount: 94
      date: '2014-07-01T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'InterMine: Extensive web services for modern biology'
    note: null
    pmcid: PMC4086141
    pmid: '24753429'
    type:
    - Other
    version: null
  relation: []
  toolType:
  - Command-line tool
  - Web application
  - Web API
  - Database portal
  topic:
  - term: Data integration and warehousing
    uri: http://edamontology.org/topic_3366
  - term: Rare diseases
    uri: http://edamontology.org/topic_3325
  validated: 1
  version:
  - 5.0.0
- accessibility: Open access
  additionDate: '2016-06-30T09:32:44Z'
  biotoolsCURIE: biotools:predictsnp2
  biotoolsID: predictsnp2
  collectionID:
  - Czech Republic
  - Rare Disease
  - ELIXIR-CZ
  confidence_flag: null
  cost: Free of charge (with restrictions)
  credit:
  - email: jaroslav.bendl@gmail.com
    fundrefid: null
    gridid: null
    name: Jaroslav Bendl
    note: null
    orcidid: https://orcid.org/0000-0001-9989-2720
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: null
  - email: stourac.jan@gmail.com
    fundrefid: null
    gridid: null
    name: Jan Stourac
    note: null
    orcidid: https://orcid.org/0000-0003-3139-3700
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    - Support
    url: null
  - email: xmusil46@stud.fit.vutbr.cz
    fundrefid: null
    gridid: null
    name: Milos Musil
    note: null
    orcidid: https://orcid.org/0000-0001-9373-7930
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: null
  - email: brezovsky@mail.muni.cz
    fundrefid: null
    gridid: null
    name: Jan Brezovsky
    note: null
    orcidid: https://orcid.org/0000-0001-9677-5078
    rorid: null
    typeEntity: Person
    typeRole:
    - Contributor
    url: null
  - email: 1441@mail.muni.cz
    fundrefid: null
    gridid: null
    name: Jiri Damborsky
    note: null
    orcidid: https://orcid.org/0000-0002-7848-8216
    rorid: null
    typeEntity: Person
    typeRole:
    - Contributor
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Eric D. Wieben
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Contributor
    url: null
  - email: zendulka@fit.vut.cz
    fundrefid: null
    gridid: null
    name: Jaroslav Zendulka
    note: null
    orcidid: https://orcid.org/0000-0001-8718-7493
    rorid: null
    typeEntity: Person
    typeRole:
    - Contributor
    url: null
  - email: 99207@mail.muni.cz
    fundrefid: null
    gridid: null
    name: Antonin Pavelka
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Loschmidt Laboratories
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
    - Provider
    url: https://loschmidt.chemi.muni.cz/peg/
  - email: null
    fundrefid: null
    gridid: null
    name: Masaryk University, Brno, Czech Republic
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
    - Provider
    url: https://www.muni.cz/
  - email: null
    fundrefid: null
    gridid: null
    name: International Centre for Clinical Research, Brno, Czech Republic
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
    - Provider
    url: https://www.fnusa-icrc.org/en/
  - email: null
    fundrefid: null
    gridid: null
    name: Brno University of Technology, Brno, Czech Republic
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
    - Provider
    url: https://www.vutbr.cz/
  - email: null
    fundrefid: null
    gridid: null
    name: ELIXIR-CZ
    note: null
    orcidid: null
    rorid: null
    typeEntity: Consortium
    typeRole:
    - Provider
    url: https://www.elixir-czech.cz/
  - email: predictsnp@sci.muni.cz
    fundrefid: null
    gridid: null
    name: PredictSNP team
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: European Regional Development Fund
    note: null
    orcidid: null
    rorid: null
    typeEntity: Funding agency
    typeRole:
    - Contributor
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: European Social Fund
    note: null
    orcidid: null
    rorid: null
    typeEntity: Funding agency
    typeRole:
    - Contributor
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Grant Agency of the Czech Republic
    note: null
    orcidid: null
    rorid: null
    typeEntity: Funding agency
    typeRole:
    - Contributor
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Ministry of Education of the Czech Republic
    note: null
    orcidid: null
    rorid: null
    typeEntity: Funding agency
    typeRole:
    - Contributor
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Brno University of Technology
    note: null
    orcidid: null
    rorid: null
    typeEntity: Funding agency
    typeRole:
    - Contributor
    url: null
  description: A consensus classifier that combines five of the top performing tools
    (CADD, DANN, FATHMM, FunSeq2 and GWAVA) for the evaluation of pathogenic effect
    of SNPs within the human genome. The obtained results are provided together with
    annotations extracted from dbSNP, GenBank, Clinvar, OMIM, RegulomeDB, HaploReg,
    UCSC and Ensembl databases.
  documentation:
  - note: null
    type:
    - User manual
    url: https://loschmidt.chemi.muni.cz/predictsnp2/docs/userguide.pdf
  download:
  - note: null
    type: Downloads page
    url: https://loschmidt.chemi.muni.cz/peg/software/predictsnp2-standalone/
    version: '1.0'
  editPermission:
    authors: []
    type: private
  elixirCommunity: []
  elixirNode:
  - Czech Republic
  elixirPlatform:
  - Tools
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Sequence variations
        uri: http://edamontology.org/data_3498
      format:
      - term: GVF
        uri: http://edamontology.org/format_3019
      - term: VCF
        uri: http://edamontology.org/format_3016
    note: VCF file containing scores and PDF file containing scores and database links
    operation:
    - term: Gene functional annotation
      uri: http://edamontology.org/operation_3672
    - term: Variant classification
      uri: http://edamontology.org/operation_3225
    output:
    - data:
        term: Sequence variations
        uri: http://edamontology.org/data_3498
      format:
      - term: VCF
        uri: http://edamontology.org/format_3016
      - term: PDF
        uri: http://edamontology.org/format_3508
  homepage: https://loschmidt.chemi.muni.cz/predictsnp2
  homepage_status: 0
  language:
  - JavaScript
  - Java
  lastUpdate: '2024-11-24T20:23:08.475881Z'
  license: Proprietary
  link: []
  maturity: Mature
  name: PredictSNP2
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: Loschmidt Laboratories
  publication:
  - doi: 10.1371/journal.pcbi.1004962
    metadata:
      abstract: 'An important message taken from human genome sequencing projects
        is that the human population exhibits approximately 99.9% genetic similarity.
        Variations in the remaining parts of the genome determine our identity, trace
        our history and reveal our heritage. The precise delineation of phenotypically
        causal variants plays a key role in providing accurate personalized diagnosis,
        prognosis, and treatment of inherited diseases. Several computational methods
        for achieving such delineation have been reported recently. However, their
        ability to pinpoint potentially deleterious variants is limited by the fact
        that their mechanisms of prediction do not account for the existence of different
        categories of variants. Consequently, their output is biased towards the variant
        categories that are most strongly represented in the variant databases. Moreover,
        most such methods provide numeric scores but not binary predictions of the
        deleteriousness of variants or confidence scores that would be more easily
        understood by users. We have constructed three datasets covering different
        types of disease-related variants, which were divided across five categories:
        (i) regulatory, (ii) splicing, (iii) missense, (iv) synonymous, and (v) nonsense
        variants. These datasets were used to develop category-optimal decision thresholds
        and to evaluate six tools for variant prioritization: CADD, DANN, FATHMM,
        FitCons, FunSeq2 and GWAVA. This evaluation revealed some important advantages
        of the category-based approach. The results obtained with the five best-performing
        tools were then combined into a consensus score. Additional comparative analyses
        showed that in the case of missense variations, protein-based predictors perform
        better than DNA sequence-based predictors. A user-friendly web interface was
        developed that provides easy access to the five tools’ predictions, and their
        consensus scores, in a user-understandable format tailored to the specific
        features of different categories of variations. To enable comprehensive evaluation
        of variants, the predictions are complemented with annotations from eight
        databases. The web server is freely available to the community at http://loschmidt.chemi.muni.cz/predictsnp2.'
      authors:
      - name: Bendl J.
      - name: Musil M.
      - name: Stourac J.
      - name: Zendulka J.
      - name: Damborsky J.
      - name: Brezovsky J.
      citationCount: 143
      date: '2016-05-01T00:00:00Z'
      journal: PLoS Computational Biology
      title: 'PredictSNP2: A Unified Platform for Accurately Evaluating SNP Effects
        by Exploiting the Different Characteristics of Variants in Distinct Genomic
        Regions'
    note: null
    pmcid: PMC4880439
    pmid: '27224906'
    type:
    - Primary
    version: '1.0'
  relation: []
  toolType:
  - Web application
  topic:
  - term: Medical informatics
    uri: http://edamontology.org/topic_3063
  - term: DNA mutation
    uri: http://edamontology.org/topic_2533
  - term: Rare diseases
    uri: http://edamontology.org/topic_3325
  - term: Genomics
    uri: http://edamontology.org/topic_0622
  validated: 1
  version:
  - '1.0'
- accessibility: null
  additionDate: '2018-04-06T08:55:47Z'
  biotoolsCURIE: biotools:caverdock
  biotoolsID: caverdock
  collectionID:
  - CAVER
  - ELIXIR-CZ
  confidence_flag: null
  cost: Free of charge (with restrictions)
  credit:
  - email: fila@mail.muni.cz
    fundrefid: null
    gridid: null
    name: Jiri Filipovic
    note: null
    orcidid: https://orcid.org/0000-0002-5703-9673
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: null
  - email: o.vavra@mail.muni.cz
    fundrefid: null
    gridid: null
    name: Ondrej Vavra
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Contributor
    url: null
  - email: 408420@mail.muni.cz
    fundrefid: null
    gridid: null
    name: Jan Plhak
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: null
  - email: 222755@mail.muni.cz
    fundrefid: null
    gridid: null
    name: David Bednar
    note: null
    orcidid: https://orcid.org/0000-0002-6803-0340
    rorid: null
    typeEntity: Person
    typeRole:
    - Contributor
    url: null
  - email: smar96@gmail.com
    fundrefid: null
    gridid: null
    name: Sergio Marques
    note: null
    orcidid: https://orcid.org/0000-0002-6281-7505
    rorid: null
    typeEntity: Person
    typeRole:
    - Contributor
    url: null
  - email: brezovsky@mail.muni.cz
    fundrefid: null
    gridid: null
    name: Jan Brezovsky
    note: null
    orcidid: https://orcid.org/0000-0001-9677-5078
    rorid: null
    typeEntity: Person
    typeRole:
    - Contributor
    url: null
  - email: stourac.jan@gmail.com
    fundrefid: null
    gridid: null
    name: Jan Stourac
    note: null
    orcidid: https://orcid.org/0000-0003-3139-3700
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    - Support
    url: null
  - email: Ludek.Matyska@muni.cz
    fundrefid: null
    gridid: null
    name: Ludek Matyska
    note: null
    orcidid: https://orcid.org/0000-0001-6399-5453
    rorid: null
    typeEntity: Person
    typeRole:
    - Contributor
    url: null
  - email: 1441@mail.muni.cz
    fundrefid: null
    gridid: null
    name: Jiri Damborsky
    note: null
    orcidid: https://orcid.org/0000-0002-7848-8216
    rorid: null
    typeEntity: Person
    typeRole:
    - Contributor
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Loschmidt Laboratories
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
    - Provider
    url: https://loschmidt.chemi.muni.cz/peg/
  - email: null
    fundrefid: null
    gridid: null
    name: Masaryk University, Brno, Czech Republic
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
    - Provider
    url: https://www.muni.cz/
  - email: null
    fundrefid: null
    gridid: null
    name: International Centre for Clinical Research, Brno, Czech Republic
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
    - Provider
    url: https://www.fnusa-icrc.org/en/
  - email: null
    fundrefid: null
    gridid: null
    name: ELIXIR-CZ
    note: null
    orcidid: null
    rorid: null
    typeEntity: Consortium
    typeRole:
    - Provider
    url: https://www.elixir-czech.cz/
  - email: caver@caver.cz
    fundrefid: null
    gridid: null
    name: CaverDock team
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: European Commission
    note: null
    orcidid: null
    rorid: null
    typeEntity: Funding agency
    typeRole:
    - Contributor
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Czech Science Foundation
    note: null
    orcidid: null
    rorid: null
    typeEntity: Funding agency
    typeRole:
    - Contributor
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Brno City Municipality
    note: null
    orcidid: null
    rorid: null
    typeEntity: Funding agency
    typeRole:
    - Contributor
    url: null
  description: Performs rapid analysis of transport processes in proteins. It models
    the transportation of a ligand from outside environment into the protein active
    or binding site and vice versa. It implements a novel algorithm to produce contiguous
    ligand trajectory and estimation of a binding energy along the pathway. The current
    version uses CAVER for pathway identification and heavily modified Autodock Vina
    as a docking engine.
  documentation:
  - note: version 1.0
    type:
    - User manual
    url: https://www.fi.muni.cz/~xfilipov/caverdock/manual.pdf
  - note: version 1.1
    type:
    - User manual
    url: https://www.fi.muni.cz/~xfilipov/caverdock/manual-1.1.pdf
  download:
  - note: v1.0, Ubuntu 14.04
    type: Binaries
    url: https://www.fi.muni.cz/~xfilipov/caverdock/caverdock-ubuntu-14.04.tar.gz
    version: '1.0'
  - note: v1.0, Ubuntu 16.04
    type: Binaries
    url: https://www.fi.muni.cz/~xfilipov/caverdock/caverdock-ubuntu-16.04.tar.gz
    version: '1.0'
  - note: v1.1, Ubuntu 16.04
    type: Binaries
    url: https://www.fi.muni.cz/~xfilipov/caverdock/caverdock-1.1-ubuntu-16.04.tar.xz
    version: '1.1'
  - note: v1.1, Ubuntu 18.04
    type: Binaries
    url: https://www.fi.muni.cz/~xfilipov/caverdock/caverdock-1.1-ubuntu-18.04.tar.xz
    version: '1.1'
  editPermission:
    authors:
    - ELIXIR-CZ
    type: group
  elixirCommunity:
  - 3D-BioInfo
  elixirNode:
  - Czech Republic
  elixirPlatform:
  - Tools
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Protein structure
        uri: http://edamontology.org/data_1460
      format:
      - term: PDB
        uri: http://edamontology.org/format_1476
    - data:
        term: Small molecule structure
        uri: http://edamontology.org/data_1463
      format:
      - term: PDB
        uri: http://edamontology.org/format_1476
    note: trajectory of ligand passing through protein tunnel and its energy
    operation:
    - term: Protein-ligand docking
      uri: http://edamontology.org/operation_0482
    output:
    - data:
        term: Protein structure report
        uri: http://edamontology.org/data_1537
      format:
      - term: raw
        uri: http://edamontology.org/format_1957
      - term: PDB
        uri: http://edamontology.org/format_1476
  homepage: https://loschmidt.chemi.muni.cz/caverdock/
  homepage_status: 0
  language:
  - C++
  - Python
  lastUpdate: '2024-11-24T20:23:05.902530Z'
  license: Proprietary
  link: []
  maturity: Mature
  name: CaverDock
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: Loschmidt Laboratories
  publication:
  - doi: 10.1093/bioinformatics/btz386
    metadata:
      abstract: 'Motivation: Protein tunnels and channels are key transport pathways
        that allow ligands to pass between proteins'' external and internal environments.
        These functionally important structural features warrant detailed attention.
        It is difficult to study the ligand binding and unbinding processes experimentally,
        while molecular dynamics simulations can be time-consuming and computationally
        demanding. Results: CaverDock is a new software tool for analysing the ligand
        passage through the biomolecules. The method uses the optimized docking algorithm
        of AutoDock Vina for ligand placement docking and implements a parallel heuristic
        algorithm to search the space of possible trajectories. The duration of the
        simulations takes from minutes to a few hours. Here we describe the implementation
        of the method and demonstrate CaverDock''s usability by: (i) comparison of
        the results with other available tools, (ii) determination of the robustness
        with large ensembles of ligands and (iii) the analysis and comparison of the
        ligand trajectories in engineered tunnels. Thorough testing confirms that
        CaverDock is applicable for the fast analysis of ligand binding and unbinding
        in fundamental enzymology and protein engineering. Availability and implementation:
        User guide and binaries for Ubuntu are freely available for non-commercial
        use at https://loschmidt.chemi.muni.cz/caverdock/. The web implementation
        is available at https://loschmidt.chemi.muni.cz/caverweb/. The source code
        is available upon request. Supplementary information: Supplementary data are
        available at Bioinformatics online.'
      authors:
      - name: Vavra O.
      - name: Filipovic J.
      - name: Plhak J.
      - name: Bednar D.
      - name: Marques S.M.
      - name: Brezovsky J.
      - name: Stourac J.
      - name: Matyska L.
      - name: Damborsky J.
      citationCount: 55
      date: '2019-12-01T00:00:00Z'
      journal: Bioinformatics
      title: 'CaverDock: A molecular docking-based tool to analyse ligand transport
        through protein tunnels and channels'
    note: null
    pmcid: null
    pmid: '31077297'
    type:
    - Primary
    version: '1.0'
  - doi: 10.1109/tcbb.2019.2907492
    metadata:
      abstract: Here we present a novel method for the analysis of transport processes
        in proteins and its implementation called CaverDock. Our method is based on
        a modified molecular docking algorithm. It iteratively places the ligand along
        the access tunnel in such a way that the ligand movement is contiguous and
        the energy is minimized. The result of CaverDock calculation is a ligand trajectory
        and an energy profile of transport process. CaverDock uses the modified docking
        program Autodock Vina for molecular docking and implements a parallel heuristic
        algorithm for searching the space of possible trajectories. Our method lies
        in between the geometrical approaches and molecular dynamics simulations.
        Contrary to the geometrical methods, it provides an evaluation of chemical
        forces. However, it is far less computationally demanding and easier to set
        up compared to molecular dynamics simulations. CaverDock will find a broad
        use in the fields of computational enzymology, drug design, and protein engineering.
        The software is available free of charge to the academic users at https://loschmidt.chemi.muni.cz/caverdock/.
      authors:
      - name: Filipovic J.
      - name: Vavra O.
      - name: Plhak J.
      - name: Bednar D.
      - name: Marques S.M.
      - name: Brezovsky J.
      - name: Matyska L.
      - name: Damborsk J.
      citationCount: 26
      date: '2020-09-01T00:00:00Z'
      journal: IEEE/ACM Transactions on Computational Biology and Bioinformatics
      title: 'CaverDock: A Novel Method for the Fast Analysis of Ligand Transport'
    note: null
    pmcid: null
    pmid: '30932844'
    type:
    - Primary
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  toolType:
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  topic:
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    uri: http://edamontology.org/topic_2814
  - term: Small molecules
    uri: http://edamontology.org/topic_0154
  - term: Proteins
    uri: http://edamontology.org/topic_0078
  validated: 1
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  - '1.1'
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  additionDate: '2016-06-30T11:17:55Z'
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    url: null
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    name: European Union
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  description: A web interface for identification and analysis of tunnels and channels
    in static protein structures with automated starting point detection.
  documentation:
  - note: null
    type:
    - User manual
    url: https://loschmidt.chemi.muni.cz/caverweb/?action=help&
  - note: null
    type:
    - Training material
    url: https://loschmidt.chemi.muni.cz/caverweb/?action=example&
  - note: null
    type:
    - Terms of use
    url: https://loschmidt.chemi.muni.cz/caverweb/?action=terms&
  download: []
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  elixirNode:
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  elixirPlatform:
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  function:
  - cmd: null
    input:
    - data:
        term: Protein structure
        uri: http://edamontology.org/data_1460
      format:
      - term: PDB
        uri: http://edamontology.org/format_1476
    note: identification of tunnels and pockets
    operation:
    - term: Protein property calculation
      uri: http://edamontology.org/operation_0250
    output:
    - data:
        term: Protein structure report
        uri: http://edamontology.org/data_1537
      format:
      - term: Textual format
        uri: http://edamontology.org/format_2330
      - term: PDB
        uri: http://edamontology.org/format_1476
  homepage: https://loschmidt.chemi.muni.cz/caverweb/
  homepage_status: 0
  language:
  - JavaScript
  - Java
  lastUpdate: '2024-11-24T20:23:04.296230Z'
  license: Proprietary
  link: []
  maturity: Mature
  name: CAVER Web
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: Loschmidt Laboratories
  publication:
  - doi: 10.1093/nar/gkz378
    metadata:
      abstract: Caver Web 1.0 is a web server for comprehensive analysis of protein
        tunnels and channels, and study of the ligands' transport through these transport
        pathways. Caver Web is the first interactive tool allowing both the analyses
        within a single graphical user interface. The server is built on top of the
        abundantly used tunnel detection tool Caver 3.02 and CaverDock 1.0 enabling
        the study of the ligand transport. The program is easy-to-use as the only
        required inputs are a protein structure for a tunnel identification and a
        list of ligands for the transport analysis. The automated guidance procedures
        assist the users to set up the calculation in a way to obtain biologically
        relevant results. The identified tunnels, their properties, energy profiles
        and trajectories for ligands' passages can be calculated and visualized. The
        tool is very fast (2-20 min per job) and is applicable even for virtual screening
        purposes. Its simple setup and comprehensive graphical user interface make
        the tool accessible for a broad scientific community. The server is freely
        available at https://loschmidt.chemi.muni.cz/caverweb.
      authors:
      - name: Stourac J.
      - name: Vavra O.
      - name: Kokkonen P.
      - name: Filipovic J.
      - name: Pinto G.
      - name: Brezovsky J.
      - name: Damborsky J.
      - name: Bednar D.
      citationCount: 151
      date: '2019-07-01T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'Caver Web 1.0: Identification of tunnels and channels in proteins and
        analysis of ligand transport'
    note: null
    pmcid: PMC6602463
    pmid: '31114897'
    type:
    - Primary
    version: null
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    type: uses
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    type: uses
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    type: uses
  toolType:
  - Web application
  topic:
  - term: Protein structure analysis
    uri: http://edamontology.org/topic_2814
  - term: Proteins
    uri: http://edamontology.org/topic_0078
  validated: 1
  version:
  - '1.1'
- accessibility: null
  additionDate: '2015-11-07T20:39:02Z'
  biotoolsCURIE: biotools:caver_pymol_plugin
  biotoolsID: caver_pymol_plugin
  collectionID:
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  - ELIXIR-CZ
  - CAVER
  confidence_flag: null
  cost: Free of charge
  credit:
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    fundrefid: null
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    name: Eva Sebestova
    note: null
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    typeEntity: Person
    typeRole:
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  description: A PyMOL plugin for identification and analysis of tunnels and channels
    in static protein structures.
  documentation:
  - note: null
    type:
    - Citation instructions
    url: http://www.caver.cz/index.php?sid=123
  - note: null
    type:
    - General
    url: http://www.caver.cz/index.php?sid=132
  - note: null
    type:
    - User manual
    url: http://www.caver.cz/fil/download/manual/caver_plugin_userguide.pdf
  download:
  - note: null
    type: Downloads page
    url: http://caver.cz/index.php?sid=199
    version: null
  - note: null
    type: Source code
    url: https://github.com/loschmidt/caver-pymol-plugin/archive/v3.0.3.zip
    version: 3.0.3
  editPermission:
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  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: Analysis of tunnels and channels in proteins
    operation:
    - term: Protein property calculation
      uri: http://edamontology.org/operation_0250
    output:
    - data:
        term: Protein structure report
        uri: http://edamontology.org/data_1537
      format:
      - term: Textual format
        uri: http://edamontology.org/format_2330
      - term: PDB
        uri: http://edamontology.org/format_1476
  homepage: http://www.caver.cz
  homepage_status: 0
  language:
  - Python
  lastUpdate: '2024-11-24T20:23:02.487427Z'
  license: GPL-3.0
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/loschmidt/caver-pymol-plugin
  maturity: Mature
  name: CAVER PyMOL plugin
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: Loschmidt Laboratories
  publication:
  - doi: 10.1371/journal.pcbi.1002708
    metadata:
      abstract: Tunnels and channels facilitate the transport of small molecules,
        ions and water solvent in a large variety of proteins. Characteristics of
        individual transport pathways, including their geometry, physico-chemical
        properties and dynamics are instrumental for understanding of structure-function
        relationships of these proteins, for the design of new inhibitors and construction
        of improved biocatalysts. CAVER is a software tool widely used for the identification
        and characterization of transport pathways in static macromolecular structures.
        Herein we present a new version of CAVER enabling automatic analysis of tunnels
        and channels in large ensembles of protein conformations. CAVER 3.0 implements
        new algorithms for the calculation and clustering of pathways. A trajectory
        from a molecular dynamics simulation serves as the typical input, while detailed
        characteristics and summary statistics of the time evolution of individual
        pathways are provided in the outputs. To illustrate the capabilities of CAVER
        3.0, the tool was applied for the analysis of molecular dynamics simulation
        of the microbial enzyme haloalkane dehalogenase DhaA. CAVER 3.0 safely identified
        and reliably estimated the importance of all previously published DhaA tunnels,
        including the tunnels closed in DhaA crystal structures. Obtained results
        clearly demonstrate that analysis of molecular dynamics simulation is essential
        for the estimation of pathway characteristics and elucidation of the structural
        basis of the tunnel gating. CAVER 3.0 paves the way for the study of important
        biochemical phenomena in the area of molecular transport, molecular recognition
        and enzymatic catalysis. The software is freely available as a multiplatform
        command-line application at http://www.caver.cz. © 2012 Chovancova et al.
      authors:
      - name: Chovancova E.
      - name: Pavelka A.
      - name: Benes P.
      - name: Strnad O.
      - name: Brezovsky J.
      - name: Kozlikova B.
      - name: Gora A.
      - name: Sustr V.
      - name: Klvana M.
      - name: Medek P.
      - name: Biedermannova L.
      - name: Sochor J.
      - name: Damborsky J.
      citationCount: 947
      date: '2012-01-01T00:00:00Z'
      journal: PLoS Computational Biology
      title: 'CAVER 3.0: A Tool for the Analysis of Transport Pathways in Dynamic
        Protein Structures'
    note: null
    pmcid: PMC3475669
    pmid: '23093919'
    type:
    - Primary
    version: null
  relation:
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    type: uses
  toolType:
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  - Plug-in
  topic:
  - term: Protein structure analysis
    uri: http://edamontology.org/topic_2814
  - term: Proteins
    uri: http://edamontology.org/topic_0078
  validated: 1
  version:
  - 3.0.3
- accessibility: Open access
  additionDate: '2015-11-07T20:33:31Z'
  biotoolsCURIE: biotools:caver
  biotoolsID: caver
  collectionID:
  - Czech Republic
  - ELIXIR-CZ
  - CAVER
  confidence_flag: null
  cost: Free of charge
  credit:
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    fundrefid: null
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    name: Eva Sebestova
    note: null
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    typeRole:
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  - email: 99207@mail.muni.cz
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    name: Antonin Pavelka
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    - Primary contact
    url: null
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    note: null
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    name: Ministry of Education of the Czech Republic
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    note: null
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    name: Grant Agency of the Czech Academy of Sciences
    note: null
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  description: A tool for identification and analysis of tunnels and channels in static
    and dynamic protein structures.
  documentation:
  - note: null
    type:
    - Citation instructions
    url: http://www.caver.cz/index.php?sid=123
  - note: null
    type:
    - General
    url: http://www.caver.cz/index.php?sid=132
  download:
  - note: null
    type: Source code
    url: http://www.caver.cz/fil/download/caver30/302/caver_3.0.2.zip
    version: null
  - note: null
    type: Binaries
    url: http://www.caver.cz/fil/download/caver30/302/caver_3.0.2.zip
    version: null
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  - Czech Republic
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  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Protein structure
        uri: http://edamontology.org/data_1460
      format:
      - term: PDB
        uri: http://edamontology.org/format_1476
    note: Analysis of tunnels and channels in proteins
    operation:
    - term: Protein property calculation
      uri: http://edamontology.org/operation_0250
    output:
    - data:
        term: Protein structure report
        uri: http://edamontology.org/data_1537
      format:
      - term: Textual format
        uri: http://edamontology.org/format_2330
      - term: PDB
        uri: http://edamontology.org/format_1476
  homepage: http://www.caver.cz
  homepage_status: 0
  language:
  - Java
  lastUpdate: '2024-11-24T20:23:01.025433Z'
  license: GPL-3.0
  link:
  - note: null
    type:
    - Repository
    url: http://www.caver.cz/fil/download/caver30/302/caver_3.0.2.zip
  maturity: Mature
  name: CAVER
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: Loschmidt Laboratories
  publication:
  - doi: 10.1371/journal.pcbi.1002708
    metadata:
      abstract: Tunnels and channels facilitate the transport of small molecules,
        ions and water solvent in a large variety of proteins. Characteristics of
        individual transport pathways, including their geometry, physico-chemical
        properties and dynamics are instrumental for understanding of structure-function
        relationships of these proteins, for the design of new inhibitors and construction
        of improved biocatalysts. CAVER is a software tool widely used for the identification
        and characterization of transport pathways in static macromolecular structures.
        Herein we present a new version of CAVER enabling automatic analysis of tunnels
        and channels in large ensembles of protein conformations. CAVER 3.0 implements
        new algorithms for the calculation and clustering of pathways. A trajectory
        from a molecular dynamics simulation serves as the typical input, while detailed
        characteristics and summary statistics of the time evolution of individual
        pathways are provided in the outputs. To illustrate the capabilities of CAVER
        3.0, the tool was applied for the analysis of molecular dynamics simulation
        of the microbial enzyme haloalkane dehalogenase DhaA. CAVER 3.0 safely identified
        and reliably estimated the importance of all previously published DhaA tunnels,
        including the tunnels closed in DhaA crystal structures. Obtained results
        clearly demonstrate that analysis of molecular dynamics simulation is essential
        for the estimation of pathway characteristics and elucidation of the structural
        basis of the tunnel gating. CAVER 3.0 paves the way for the study of important
        biochemical phenomena in the area of molecular transport, molecular recognition
        and enzymatic catalysis. The software is freely available as a multiplatform
        command-line application at http://www.caver.cz. © 2012 Chovancova et al.
      authors:
      - name: Chovancova E.
      - name: Pavelka A.
      - name: Benes P.
      - name: Strnad O.
      - name: Brezovsky J.
      - name: Kozlikova B.
      - name: Gora A.
      - name: Sustr V.
      - name: Klvana M.
      - name: Medek P.
      - name: Biedermannova L.
      - name: Sochor J.
      - name: Damborsky J.
      citationCount: 947
      date: '2012-01-01T00:00:00Z'
      journal: PLoS Computational Biology
      title: 'CAVER 3.0: A Tool for the Analysis of Transport Pathways in Dynamic
        Protein Structures'
    note: null
    pmcid: PMC3475669
    pmid: '23093919'
    type:
    - Primary
    version: null
  relation: []
  toolType:
  - Command-line tool
  topic:
  - term: Protein structure analysis
    uri: http://edamontology.org/topic_2814
  - term: Proteins
    uri: http://edamontology.org/topic_0078
  validated: 1
  version:
  - '3.02'
- accessibility: Open access
  additionDate: '2020-05-14T05:43:26Z'
  biotoolsCURIE: biotools:enzymeminer
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  credit:
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    name: Simeon Borko
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    name: Jan Stourac
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  description: EnzymeMiner identifies putative members of enzyme families or subfamilies
    and facilitates the selection of promising targets for experimental characterization.
    Two key selection criteria are (i) the predicted solubility and (ii) the sequence
    identities visualised using an interactive sequence similarity network. The search
    query can be a sequence from the Swiss-Prot database or a custom sequence with
    a custom description of essential residues. The output is an interactive selection
    table containing annotated identified sequences.
  documentation:
  - note: null
    type:
    - User manual
    url: https://loschmidt.chemi.muni.cz/enzymeminer/help
  - note: null
    type:
    - Training material
    url: https://loschmidt.chemi.muni.cz/enzymeminer/example
  - note: null
    type:
    - Terms of use
    url: https://loschmidt.chemi.muni.cz/enzymeminer/terms-of-use
  download: []
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  function:
  - cmd: null
    input:
    - data:
        term: Protein sequence
        uri: http://edamontology.org/data_2976
      format:
      - term: FASTA
        uri: http://edamontology.org/format_1929
    note: null
    operation:
    - term: Sequence similarity search
      uri: http://edamontology.org/operation_0346
    - term: Sequence clustering
      uri: http://edamontology.org/operation_0291
    - term: Sequence annotation
      uri: http://edamontology.org/operation_0361
    - term: Protein solubility prediction
      uri: http://edamontology.org/operation_0409
    output:
    - data:
        term: Protein features
        uri: http://edamontology.org/data_1277
      format:
      - term: xlsx
        uri: http://edamontology.org/format_3620
    - data:
        term: Sequence set (protein)
        uri: http://edamontology.org/data_1233
      format:
      - term: FASTA
        uri: http://edamontology.org/format_1929
    - data:
        term: Sequence cluster (protein)
        uri: http://edamontology.org/data_1245
      format: []
  homepage: https://loschmidt.chemi.muni.cz/enzymeminer/
  homepage_status: 0
  language:
  - JavaScript
  - Java
  lastUpdate: '2024-11-24T20:22:58.362628Z'
  license: Proprietary
  link: []
  maturity: Mature
  name: EnzymeMiner
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: Loschmidt Laboratories
  publication:
  - doi: 10.1093/nar/gkaa372
    metadata:
      abstract: Millions of protein sequences are being discovered at an incredible
        pace, representing an inexhaustible source of biocatalysts. Despite genomic
        databases growing exponentially, classical biochemical characterization techniques
        are time-demanding, cost-ineffective and low-throughput. Therefore, computational
        methods are being developed to explore the unmapped sequence space efficiently.
        Selection of putative enzymes for biochemical characterization based on rational
        and robust analysis of all available sequences remains an unsolved problem.
        To address this challenge, we have developed EnzymeMiner––a web server for
        automated screening and annotation of diverse family members that enables
        selection of hits for wet-lab experiments. EnzymeMiner prioritizes sequences
        that are more likely to preserve the catalytic activity and are heterologously
        expressible in a soluble form in Escherichia coli. The solubility prediction
        employs the in-house SoluProt predictor developed using machine learning.
        EnzymeMiner reduces the time devoted to data gathering, multi-step analysis,
        sequence prioritization and selection from days to hours. The successful use
        case for the haloalkane dehalogenase family is described in a comprehensive
        tutorial available on the EnzymeMiner web page. EnzymeMiner is a universal
        tool applicable to any enzyme family that provides an interactive and easy-to-use
        web interface freely available at https://loschmidt.chemi.muni.cz/enzymeminer/.
      authors:
      - name: Hon J.
      - name: Borko S.
      - name: Stourac J.
      - name: Prokop Z.
      - name: Zendulka J.
      - name: Bednar D.
      - name: Martinek T.
      - name: Damborsky J.
      citationCount: 56
      date: '2021-01-01T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'EnzymeMiner: Automated mining of soluble enzymes with diverse structures,
        catalytic properties and stabilities'
    note: null
    pmcid: PMC7319543
    pmid: '32392342'
    type: []
    version: null
  relation:
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    type: uses
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    type: uses
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  - biotoolsID: interproscan_4
    type: uses
  - biotoolsID: soluprot
    type: uses
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    type: uses
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    type: uses
  - biotoolsID: mmseqs2
    type: uses
  - biotoolsID: uniprotkb_swiss-prot
    type: uses
  toolType:
  - Web application
  topic:
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    uri: http://edamontology.org/topic_0121
  - term: Sequence analysis
    uri: http://edamontology.org/topic_0080
  - term: Data mining
    uri: http://edamontology.org/topic_3473
  - term: Enzymes
    uri: http://edamontology.org/topic_0821
  - term: Proteins
    uri: http://edamontology.org/topic_0078
  validated: 1
  version:
  - '1.0'
- accessibility: Open access
  additionDate: '2015-11-07T20:36:20Z'
  biotoolsCURIE: biotools:caver_analyst
  biotoolsID: caver_analyst
  collectionID:
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  - ELIXIR-CZ
  - CAVER
  confidence_flag: null
  cost: Free of charge (with restrictions)
  credit:
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    fundrefid: null
    gridid: null
    name: Adam Jurcik
    note: null
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    url: null
  - email: 222755@mail.muni.cz
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    name: David Bednar
    note: null
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    url: null
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    gridid: null
    name: Norwegian Research Council
    note: null
    orcidid: null
    rorid: null
    typeEntity: Funding agency
    typeRole:
    - Contributor
    url: null
  description: A tool for interactive visualization and analysis of tunnels, channels
    and cavities in protein structures.
  documentation:
  - note: null
    type:
    - Citation instructions
    url: http://www.caver.cz/index.php?sid=123
  - note: null
    type:
    - User manual
    url: https://caver.cz/fil/download/manual/CAVER_Analyst_2.0_Beta-user_guide.pdf
  download:
  - note: null
    type: Binaries
    url: https://www.caver.cz/fil/download/caver_analyst/caver_analyst2_beta2.zip
    version: '2.0'
  - note: null
    type: Downloads page
    url: https://caver.cz/index.php?sid=199
    version: null
  editPermission:
    authors: []
    type: private
  elixirCommunity: []
  elixirNode:
  - Czech Republic
  elixirPlatform:
  - Tools
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Protein structure
        uri: http://edamontology.org/data_1460
      format:
      - term: PDB
        uri: http://edamontology.org/format_1476
      - term: AMBER top
        uri: http://edamontology.org/format_3881
    - data:
        term: Trajectory data
        uri: http://edamontology.org/data_3870
      format:
      - term: XTC
        uri: http://edamontology.org/format_3875
      - term: NetCDF
        uri: http://edamontology.org/format_3650
      - term: AMBER top
        uri: http://edamontology.org/format_3881
      - term: trr
        uri: http://edamontology.org/format_3910
      - term: PSF
        uri: http://edamontology.org/format_3882
    note: Analysis and visualization of tunnels and channels in proteins
    operation:
    - term: Structure visualisation
      uri: http://edamontology.org/operation_0570
    - term: Protein property calculation
      uri: http://edamontology.org/operation_0250
    - term: Accessible surface calculation
      uri: http://edamontology.org/operation_0384
    - term: Protein secondary structure prediction
      uri: http://edamontology.org/operation_0267
    output:
    - data:
        term: Protein structure report
        uri: http://edamontology.org/data_1537
      format:
      - term: Textual format
        uri: http://edamontology.org/format_2330
      - term: PDB
        uri: http://edamontology.org/format_1476
  homepage: https://www.caver.cz
  homepage_status: 0
  language:
  - Java
  lastUpdate: '2024-11-24T20:22:56.347730Z'
  license: Proprietary
  link: []
  maturity: Mature
  name: CAVER Analyst
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: Loschmidt Laboratories
  publication:
  - doi: 10.1093/bioinformatics/bty386
    metadata:
      abstract: Motivation Studying the transport paths of ligands, solvents, or ions
        in transmembrane proteins and proteins with buried binding sites is fundamental
        to the understanding of their biological function. A detailed analysis of
        the structural features influencing the transport paths is also important
        for engineering proteins for biomedical and biotechnological applications.
        Results CAVER Analyst 2.0 is a software tool for quantitative analysis and
        real-time visualization of tunnels and channels in static and dynamic structures.
        This version provides the users with many new functions, including advanced
        techniques for intuitive visual inspection of the spatiotemporal behavior
        of tunnels and channels. Novel integrated algorithms allow an efficient analysis
        and data reduction in large protein structures and molecular dynamic simulations.
        Availability and implementation CAVER Analyst 2.0 is a multi-platform standalone
        Java-based application. Binaries and documentation are freely available at
        www.caver.cz. Supplementary informationSupplementary dataare available at
        Bioinformatics online.
      authors:
      - name: Jurcik A.
      - name: Bednar D.
      - name: Byska J.
      - name: Marques S.M.
      - name: Furmanova K.
      - name: Daniel L.
      - name: Kokkonen P.
      - name: Brezovsky J.
      - name: Strnad O.
      - name: Stourac J.
      - name: Pavelka A.
      - name: Manak M.
      - name: Damborsky J.
      - name: Kozlikova B.
      citationCount: 247
      date: '2018-10-15T00:00:00Z'
      journal: Bioinformatics
      title: 'CAVER Analyst 2.0: Analysis and visualization of channels and tunnels
        in protein structures and molecular dynamics trajectories'
    note: null
    pmcid: PMC6184705
    pmid: '29741570'
    type:
    - Primary
    version: null
  relation:
  - biotoolsID: caver
    type: uses
  - biotoolsID: uniprotkb_swiss-prot
    type: uses
  toolType:
  - Desktop application
  topic:
  - term: Protein structure analysis
    uri: http://edamontology.org/topic_2814
  - term: Proteins
    uri: http://edamontology.org/topic_0078
  validated: 1
  version:
  - '2.0'
- accessibility: Open access
  additionDate: '2015-11-07T20:40:08Z'
  biotoolsCURIE: biotools:predictsnp
  biotoolsID: predictsnp
  collectionID:
  - Czech Republic
  - Rare Disease
  - ELIXIR-CZ
  confidence_flag: null
  cost: Free of charge (with restrictions)
  credit:
  - email: jaroslav.bendl@gmail.com
    fundrefid: null
    gridid: null
    name: Jaroslav Bendl
    note: null
    orcidid: https://orcid.org/0000-0001-9989-2720
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: null
  - email: stourac.jan@gmail.com
    fundrefid: null
    gridid: null
    name: Jan Stourac
    note: null
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    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    - Support
    url: null
  - email: null
    fundrefid: null
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    name: Ondrej Salanda
    note: null
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    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: null
  - email: brezovsky@mail.muni.cz
    fundrefid: null
    gridid: null
    name: Jan Brezovsky
    note: null
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    rorid: null
    typeEntity: Person
    typeRole:
    - Contributor
    url: null
  - email: 1441@mail.muni.cz
    fundrefid: null
    gridid: null
    name: Jiri Damborsky
    note: null
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    rorid: null
    typeEntity: Person
    typeRole:
    - Contributor
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Eric D. Wieben
    note: null
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    rorid: null
    typeEntity: Person
    typeRole:
    - Contributor
    url: null
  - email: zendulka@fit.vut.cz
    fundrefid: null
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    name: Jaroslav Zendulka
    note: null
    orcidid: https://orcid.org/0000-0001-8718-7493
    rorid: null
    typeEntity: Person
    typeRole:
    - Contributor
    url: null
  - email: 99207@mail.muni.cz
    fundrefid: null
    gridid: null
    name: Antonin Pavelka
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Loschmidt Laboratories
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
    - Provider
    url: https://loschmidt.chemi.muni.cz/peg/
  - email: null
    fundrefid: null
    gridid: null
    name: Masaryk University, Brno, Czech Republic
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
    - Provider
    url: https://www.muni.cz/
  - email: null
    fundrefid: null
    gridid: null
    name: International Centre for Clinical Research, Brno, Czech Republic
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
    - Provider
    url: https://www.fnusa-icrc.org/en/
  - email: null
    fundrefid: null
    gridid: null
    name: Brno University of Technology, Brno, Czech Republic
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
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    url: https://www.vutbr.cz/
  - email: null
    fundrefid: null
    gridid: null
    name: Mayo Clinic, Rochester, New York, United States of America
    note: null
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    rorid: null
    typeEntity: Institute
    typeRole:
    - Provider
    url: https://www.mayoclinic.org/
  - email: null
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    note: null
    orcidid: null
    rorid: null
    typeEntity: Consortium
    typeRole:
    - Provider
    url: https://www.elixir-czech.cz/
  - email: predictsnp@sci.muni.cz
    fundrefid: null
    gridid: null
    name: PredictSNP team
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: European Regional Development Fund
    note: null
    orcidid: null
    rorid: null
    typeEntity: Funding agency
    typeRole:
    - Contributor
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: European Social Fund
    note: null
    orcidid: null
    rorid: null
    typeEntity: Funding agency
    typeRole:
    - Contributor
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Grant Agency of the Czech Republic
    note: null
    orcidid: null
    rorid: null
    typeEntity: Funding agency
    typeRole:
    - Contributor
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Ministry of Education of the Czech Republic
    note: null
    orcidid: null
    rorid: null
    typeEntity: Funding agency
    typeRole:
    - Contributor
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Brno University of Technology
    note: null
    orcidid: null
    rorid: null
    typeEntity: Funding agency
    typeRole:
    - Contributor
    url: null
  description: A consensus classifier that combines six of the top performing tools
    for the prediction of the effects of mutation on protein function. The obtained
    results are provided together with annotations extracted from the Protein Mutant
    Database and the UniProt database.
  documentation:
  - note: null
    type:
    - User manual
    url: https://loschmidt.chemi.muni.cz/predictsnp1/docs/USER_GUIDE.pdf
  download:
  - note: null
    type: Binaries
    url: https://loschmidt.chemi.muni.cz/predictsnp1/docs/predictsnp-1.0.tar.gz
    version: null
  editPermission:
    authors: []
    type: private
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  elixirNode:
  - Czech Republic
  elixirPlatform:
  - Tools
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Protein sequence (raw)
        uri: http://edamontology.org/data_2974
      format:
      - term: FASTA
        uri: http://edamontology.org/format_1929
    note: Prediction of the effect of amino acid substitution on protein function
    operation:
    - term: Variant effect prediction
      uri: http://edamontology.org/operation_0331
    output:
    - data:
        term: Protein features
        uri: http://edamontology.org/data_1277
      format:
      - term: HTML
        uri: http://edamontology.org/format_2331
      - term: Textual format
        uri: http://edamontology.org/format_2330
    - data:
        term: UniProt ID
        uri: http://edamontology.org/data_2291
      format: []
  homepage: https://loschmidt.chemi.muni.cz/predictsnp1
  homepage_status: 0
  language:
  - JavaScript
  - Java
  - Python
  lastUpdate: '2024-11-24T20:22:54.522074Z'
  license: Proprietary
  link: []
  maturity: Mature
  name: PredictSNP
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: Loschmidt Laboratories
  publication:
  - doi: 10.1371/journal.pcbi.1003440
    metadata:
      abstract: 'Single nucleotide variants represent a prevalent form of genetic
        variation. Mutations in the coding regions are frequently associated with
        the development of various genetic diseases. Computational tools for the prediction
        of the effects of mutations on protein function are very important for analysis
        of single nucleotide variants and their prioritization for experimental characterization.
        Many computational tools are already widely employed for this purpose. Unfortunately,
        their comparison and further improvement is hindered by large overlaps between
        the training datasets and benchmark datasets, which lead to biased and overly
        optimistic reported performances. In this study, we have constructed three
        independent datasets by removing all duplicities, inconsistencies and mutations
        previously used in the training of evaluated tools. The benchmark dataset
        containing over 43,000 mutations was employed for the unbiased evaluation
        of eight established prediction tools: MAPP, nsSNPAnalyzer, PANTHER, PhD-SNP,
        PolyPhen-1, PolyPhen-2, SIFT and SNAP. The six best performing tools were
        combined into a consensus classifier PredictSNP, resulting into significantly
        improved prediction performance, and at the same time returned results for
        all mutations, confirming that consensus prediction represents an accurate
        and robust alternative to the predictions delivered by individual tools. A
        user-friendly web interface enables easy access to all eight prediction tools,
        the consensus classifier PredictSNP and annotations from the Protein Mutant
        Database and the UniProt database. The web server and the datasets are freely
        available to the academic community at http://loschmidt.chemi.muni.cz/predictsnp.
        © 2014 Bendl et al.'
      authors:
      - name: Bendl J.
      - name: Stourac J.
      - name: Salanda O.
      - name: Pavelka A.
      - name: Wieben E.D.
      - name: Zendulka J.
      - name: Brezovsky J.
      - name: Damborsky J.
      citationCount: 595
      date: '2014-01-01T00:00:00Z'
      journal: PLoS Computational Biology
      title: 'PredictSNP: Robust and Accurate Consensus Classifier for Prediction
        of Disease-Related Mutations'
    note: null
    pmcid: PMC3894168
    pmid: '24453961'
    type:
    - Primary
    version: '1.0'
  relation:
  - biotoolsID: mapp
    type: uses
  - biotoolsID: nssnpanalyzer
    type: uses
  - biotoolsID: panther
    type: uses
  - biotoolsID: phd-snp
    type: uses
  - biotoolsID: polyphen
    type: uses
  - biotoolsID: polyphen-2
    type: uses
  - biotoolsID: sift
    type: uses
  - biotoolsID: snap
    type: uses
  toolType:
  - Command-line tool
  - Web application
  topic:
  - term: DNA polymorphism
    uri: http://edamontology.org/topic_2885
  - term: Medical informatics
    uri: http://edamontology.org/topic_3063
  - term: Rare diseases
    uri: http://edamontology.org/topic_3325
  - term: Proteins
    uri: http://edamontology.org/topic_0078
  - term: Genetics
    uri: http://edamontology.org/topic_3053
  validated: 1
  version:
  - '1.0'
- accessibility: null
  additionDate: '2015-11-25T19:04:17Z'
  biotoolsCURIE: biotools:setter
  biotoolsID: setter
  collectionID:
  - Czech Republic
  - ELIXIR-CZ
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: null
    fundrefid: null
    gridid: null
    name: Petr Čech
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: David Hoksza
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Daniel Svozil
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Daniel Svozil
    note: null
    orcidid: null
    rorid: null
    typeEntity: null
    typeRole:
    - Contributor
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Charles University in Prague, Czech Republic
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
    - Provider
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: University of Chemistry and Technology Prague, Czech Republic
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
    - Provider
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: ELIXIR-CZ
    note: null
    orcidid: null
    rorid: null
    typeEntity: Consortium
    typeRole: []
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Czech Science Foundation
    note: null
    orcidid: null
    rorid: null
    typeEntity: Funding agency
    typeRole:
    - Contributor
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: ELIXIR-CZ
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
    - Provider
    url: null
  - email: svozild@vscht.cz
    fundrefid: null
    gridid: null
    name: Daniel Svozil
    note: null
    orcidid: null
    rorid: null
    typeEntity: null
    typeRole:
    - Support
    url: null
  - email: david.hoksza@mff.cuni.cz
    fundrefid: null
    gridid: null
    name: David Hoksza
    note: null
    orcidid: null
    rorid: null
    typeEntity: null
    typeRole:
    - Support
    url: null
  - email: svozild@vscht.cz
    fundrefid: null
    gridid: null
    name: Daniel Svozil
    note: null
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    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  - email: david.hoksza@mff.cuni.cz
    fundrefid: null
    gridid: null
    name: David Hoksza
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  description: A web application for RNA structure comparison.
  documentation:
  - note: null
    type:
    - Citation instructions
    - General
    url: http://setter.projekty.ms.mff.cuni.cz/help/index/
  download: []
  editPermission:
    authors:
    - davidhokszamff
    - mar_nov
    type: group
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  elixirNode:
  - Czech Republic
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  - Tools
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: PDB ID
        uri: http://edamontology.org/data_1127
      format:
      - term: PDB
        uri: http://edamontology.org/format_1476
    note: Secondary-based RNA tertiary structure superposition either PDBID or user-prepared
      PDB
    operation:
    - term: Nucleic acid structure analysis
      uri: http://edamontology.org/operation_2481
    - term: RNA secondary structure alignment
      uri: http://edamontology.org/operation_0502
    output:
    - data:
        term: Secondary structure alignment (RNA)
        uri: http://edamontology.org/data_0881
      format: []
  homepage: http://setter.projekty.ms.mff.cuni.cz/
  homepage_status: 0
  language:
  - C++
  - Python
  lastUpdate: '2024-11-24T20:22:35.598559Z'
  license: null
  link: []
  maturity: Mature
  name: SETTER
  operatingSystem:
  - Linux
  otherID: []
  owner: ELIXIR-CZ
  publication:
  - doi: 10.1093/nar/gks560
    metadata:
      abstract: The recent discoveries of regulatory non-coding RNAs changed our view
        of RNA as a simple information transfer molecule. Understanding the architecture
        and function of active RNA molecules requires methods for comparing and analyzing
        their 3D structures. While structural alignment of short RNAs is achievable
        in a reasonable amount of time, large structures represent much bigger challenge.
        Here, we present the SETTER web server for the RNA structure pairwise comparison
        utilizing the SETTER (SEcondary sTructure-based TERtiary Structure Similarity
        Algorithm) algorithm. The SETTER method divides an RNA structure into the
        set of non-overlapping structural elements called generalized secondary structure
        units (GSSUs). The SETTER algorithm scales as O(n 2) with the size of a GSSUs
        and as O(n) with the number of GSSUs in the structure. This scaling gives
        SETTER its high speed as the average size of the GSSU remains constant irrespective
        of the size of the structure. However, the favorable speed of the algorithm
        does not compromise its accuracy. The SETTER web server together with the
        stand-alone implementation of the SETTER algorithm are freely accessible at
        http://siret.cz/setter. © 2012 The Author(s).
      authors:
      - name: Cech P.
      - name: Svozil D.
      - name: Hoksza D.
      citationCount: 22
      date: '2012-07-01T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'SETTER: Web server for RNA structure comparison'
    note: null
    pmcid: PMC3394248
    pmid: '22693209'
    type:
    - Primary
    version: null
  - doi: 10.1186/s12859-015-0696-8
    metadata:
      abstract: 'Background: Understanding the architecture and function of RNA molecules
        requires methods for comparing and analyzing their tertiary and quaternary
        structures. While structural superposition of short RNAs is achievable in
        a reasonable time, large structures represent much bigger challenge. Therefore,
        we have developed a fast and accurate algorithm for RNA pairwise structure
        superposition called SETTER and implemented it in the SETTER web server. However,
        though biological relationships can be inferred by a pairwise structure alignment,
        key features preserved by evolution can be identified only from a multiple
        structure alignment. Thus, we extended the SETTER algorithm to the alignment
        of multiple RNA structures and developed the MultiSETTER algorithm. Results:
        In this paper, we present the updated version of the SETTER web server that
        implements a user friendly interface to the MultiSETTER algorithm. The server
        accepts RNA structures either as the list of PDB IDs or as user-defined PDB
        files. After the superposition is computed, structures are visualized in 3D
        and several reports and statistics are generated. Conclusion: To the best
        of our knowledge, the MultiSETTER web server is the first publicly available
        tool for a multiple RNA structure alignment. The MultiSETTER server offers
        the visual inspection of an alignment in 3D space which may reveal structural
        and functional relationships not captured by other multiple alignment methods
        based either on a sequence or on secondary structure motifs.'
      authors:
      - name: Cech P.
      - name: Hoksza D.
      - name: Svozil D.
      citationCount: 10
      date: '2015-08-12T00:00:00Z'
      journal: BMC Bioinformatics
      title: 'MultiSETTER: Web server for multiple RNA structure comparison'
    note: null
    pmcid: PMC4531852
    pmid: '26264783'
    type:
    - Other
    version: null
  - doi: 10.1109/tcbb.2014.2351810
    metadata:
      abstract: Recent advances in RNA research and the steady growth of available
        RNA structures call for bioinformatics methods for handling and analyzing
        RNA structural data. Recently, we introduced SETTER - a fast and accurate
        method for RNA pairwise structure alignment. In this paper, we describe MultiSETTER,
        SETTER extension for multiple RNA structure alignment. MultiSETTER combines
        SETTER's decomposition of RNA structures into non-overlapping structural subunits
        with the multiple sequence alignment algorithm ClustalW adapted for the structure
        alignment. The accuracy of MultiSETTER was assessed by the automatic classification
        of RNA structures and its comparison to SCOR annotations. In addition, MultiSETTER
        classification was also compared to multiple sequence alignment-based and
        secondary structure alignment-based classifications provided by LocARNA and
        RNADistance tools, respectively. MultiSETTER precompiled Windows libraries,
        as well as the C++ source code, are freely available from http://siret.cz/multisetter.
      authors:
      - name: Hoksza D.
      - name: Svozil D.
      citationCount: 6
      date: '2015-05-01T00:00:00Z'
      journal: IEEE/ACM Transactions on Computational Biology and Bioinformatics
      title: Multiple 3D RNA structure superposition using neighbor joining
    note: null
    pmcid: null
    pmid: '26357263'
    type:
    - Other
    version: null
  relation: []
  toolType:
  - Web application
  topic:
  - term: RNA
    uri: http://edamontology.org/topic_0099
  - term: Nucleic acid structure analysis
    uri: http://edamontology.org/topic_0097
  validated: 1
  version:
  - '1.0'
- accessibility: Open access
  additionDate: '2016-12-19T14:28:44Z'
  biotoolsCURIE: biotools:clustalo
  biotoolsID: clustalo
  collectionID:
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  - Bioconda
  - galaxyPasteur
  - DebianMed
  confidence_flag: null
  cost: Free of charge
  credit:
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    fundrefid: null
    gridid: null
    name: Clustal helpdesk
    note: null
    orcidid: null
    rorid: null
    typeEntity: Division
    typeRole:
    - Primary contact
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Science Foundation Ireland
    note: null
    orcidid: null
    rorid: null
    typeEntity: Funding agency
    typeRole: []
    url: http://www.sfi.ie/
  description: Multiple sequence alignment software. The name is occassionally spelled
    as ClustalOmega, Clustal Ω, ClustalΩ, Clustal O, ClustalO.
  documentation:
  - note: null
    type:
    - General
    url: http://www.clustal.org/omega/#Documentation
  - note: Clustal README file
    type:
    - User manual
    url: http://www.clustal.org/omega/README
  - note: null
    type:
    - Installation instructions
    url: http://www.clustal.org/omega/INSTALL
  download:
  - note: null
    type: Downloads page
    url: http://www.clustal.org/omega/#Download
    version: null
  - note: Debian package (Debian Med Packaging Team). Source code package 'clustalo'
      and binary packages including API and its documentation.
    type: Software package
    url: https://tracker.debian.org/pkg/clustalo
    version: null
  - note: Conda package (Bioconda channel). Conda recipe at https://github.com/bioconda/bioconda-recipes/tree/master/recipes/clustalo/meta.yaml
    type: Software package
    url: https://bioconda.github.io/recipes/clustalo/README.html
    version: null
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  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Sequence
        uri: http://edamontology.org/data_2044
      format:
      - term: FASTA
        uri: http://edamontology.org/format_1929
    note: null
    operation:
    - term: Multiple sequence alignment
      uri: http://edamontology.org/operation_0492
    output:
    - data:
        term: Sequence alignment
        uri: http://edamontology.org/data_0863
      format:
      - term: FASTA
        uri: http://edamontology.org/format_1929
  homepage: http://www.clustal.org/omega/
  homepage_status: 0
  language: []
  lastUpdate: '2024-11-24T20:19:47.776845Z'
  license: GPL-2.0
  link:
  - note: null
    type:
    - Galaxy service
    url: https://galaxy.pasteur.fr/?tool_id=toolshed.pasteur.fr%2Frepos%2Fdcorreia%2Fclustalo%2Fclustalo%2F1.2.1.1&version=1.2.1.1&__identifer=9si4ugr4fwu
  - note: null
    type:
    - Issue tracker
    url: http://bioinf.ucd.ie/bugzilla/buglist.cgi?quicksearch=clustal
  maturity: Mature
  name: Clustal Omega
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: hmenager
  publication:
  - doi: 10.1038/msb.2011.75
    metadata:
      abstract: Multiple sequence alignments are fundamental to many sequence analysis
        methods. Most alignments are computed using the progressive alignment heuristic.
        These methods are starting to become a bottleneck in some analysis pipelines
        when faced with data sets of the size of many thousands of sequences. Some
        methods allow computation of larger data sets while sacrificing quality, and
        others produce high-quality alignments, but scale badly with the number of
        sequences. In this paper, we describe a new program called Clustal Omega,
        which can align virtually any number of protein sequences quickly and that
        delivers accurate alignments. The accuracy of the package on smaller test
        cases is similar to that of the high-quality aligners. On larger data sets,
        Clustal Omega outperforms other packages in terms of execution time and quality.
        Clustal Omega also has powerful features for adding sequences to and exploiting
        information in existing alignments, making use of the vast amount of precomputed
        information in public databases like Pfam. © 2011 EMBO and Macmillan Publishers
        Limited All rights reserved.
      authors:
      - name: Sievers F.
      - name: Wilm A.
      - name: Dineen D.
      - name: Gibson T.J.
      - name: Karplus K.
      - name: Li W.
      - name: Lopez R.
      - name: McWilliam H.
      - name: Remmert M.
      - name: Soding J.
      - name: Thompson J.D.
      - name: Higgins D.G.
      citationCount: 11023
      date: '2011-10-19T00:00:00Z'
      journal: Molecular Systems Biology
      title: Fast, scalable generation of high-quality protein multiple sequence alignments
        using Clustal Omega
    note: null
    pmcid: PMC3261699
    pmid: '21988835'
    type:
    - Primary
    version: null
  - doi: 10.1002/pro.3290
    metadata:
      abstract: Clustal Omega is a widely used package for carrying out multiple sequence
        alignment. Here, we describe some recent additions to the package and benchmark
        some alternative ways of making alignments. These benchmarks are based on
        protein structure comparisons or predictions and include a recently described
        method based on secondary structure prediction. In general, Clustal Omega
        is fast enough to make very large alignments and the accuracy of protein alignments
        is high when compared to alternative packages. The package is freely available
        as executables or source code from www.clustal.org or can be run on-line from
        a variety of sites, especially the EBI www.ebi.ac.uk.
      authors:
      - name: Sievers F.
      - name: Higgins D.G.
      citationCount: 1148
      date: '2018-01-01T00:00:00Z'
      journal: Protein Science
      title: Clustal Omega for making accurate alignments of many protein sequences
    note: null
    pmcid: PMC5734385
    pmid: '28884485'
    type:
    - Primary
    version: null
  - doi: 10.1002/0471250953.bi0313s48
    metadata:
      abstract: Clustal Omega is a package for making multiple sequence alignments
        of amino acid or nucleotide sequences, quickly and accurately. It is a complete
        upgrade and rewrite of earlier Clustal programs. This unit describes how to
        run Clustal Omega interactively from a command line, although it can also
        be run online from several sites. The unit describes a basic protocol for
        taking a set of unaligned sequences and producing a full alignment. There
        are also protocols for using an external HMM or iteration to help improve
        an alignment.
      authors:
      - name: Sievers F.
      - name: Higgins D.G.
      citationCount: 414
      date: '2014-01-01T00:00:00Z'
      journal: Current Protocols in Bioinformatics
      title: Clustal Omega
    note: How to use Clustal Omega. Not open access.
    pmcid: null
    pmid: '25501942'
    type:
    - Usage
    version: null
  relation: []
  toolType:
  - Command-line tool
  - Library
  topic:
  - term: Sequence analysis
    uri: http://edamontology.org/topic_0080
  validated: 1
  version:
  - 1.0 - 1.2
- accessibility: Open access
  additionDate: '2019-07-02T12:41:10Z'
  biotoolsCURIE: biotools:CyGenexpi
  biotoolsID: CyGenexpi
  collectionID: []
  confidence_flag: null
  cost: Free of charge
  credit:
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    fundrefid: null
    gridid: null
    name: Martin Modrák
    note: null
    orcidid: http://orcid.org/0000-0002-8886-7797
    rorid: null
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    typeRole:
    - Primary contact
    - Developer
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Ministry of Education, Youth and Sports of the Czech Republic
    note: 'C4Sys research infrastructure project (MEYS project No: LM20150055), and
      ELIXIR_CZ  project (MEYS project no. LM2015047)'
    orcidid: null
    rorid: null
    typeEntity: Funding agency
    typeRole: []
    url: null
  description: CyGenexpi is a Cytoscape plugin for validating/inferring genetic networks
    from time series expression data. It is based on a ordinary differential equation
    (ODE) model of gene regulation.
  documentation:
  - note: null
    type:
    - General
    url: https://github.com/cas-bioinf/genexpi/wiki/CyGenexpi
  download:
  - note: null
    type: Downloads page
    url: http://apps.cytoscape.org/apps/cygenexpi
    version: 1.4.2
  - note: null
    type: Source code
    url: https://github.com/cas-bioinf/genexpi
    version: 1.4.2
  editPermission:
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    type: group
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  elixirNode:
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  function:
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    input:
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        term: Gene expression matrix
        uri: http://edamontology.org/data_3112
      format:
      - term: DSV
        uri: http://edamontology.org/format_3751
    note: More info at https://github.com/cas-bioinf/genexpi/wiki/Example
    operation:
    - term: Gene regulatory network analysis
      uri: http://edamontology.org/operation_1781
    output:
    - data:
        term: Pathway or network report
        uri: http://edamontology.org/data_2984
      format:
      - term: DSV
        uri: http://edamontology.org/format_3751
  homepage: https://github.com/cas-bioinf/genexpi/wiki/CyGenexpi
  homepage_status: 0
  language:
  - Java
  lastUpdate: '2024-11-24T20:17:46.610252Z'
  license: LGPL-3.0
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/cas-bioinf/genexpi
  - note: null
    type:
    - Software catalogue
    url: http://apps.cytoscape.org/apps/cygenexpi
  maturity: Emerging
  name: CyGenexpi
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: modrak_m
  publication:
  - doi: 10.1186/s12859-018-2138-x
    metadata:
      abstract: 'Background: Identifying regulons of sigma factors is a vital subtask
        of gene network inference. Integrating multiple sources of data is essential
        for correct identification of regulons and complete gene regulatory networks.
        Time series of expression data measured with microarrays or RNA-seq combined
        with static binding experiments (e.g., ChIP-seq) or literature mining may
        be used for inference of sigma factor regulatory networks. Results: We introduce
        Genexpi: a tool to identify sigma factors by combining candidates obtained
        from ChIP experiments or literature mining with time-course gene expression
        data. While Genexpi can be used to infer other types of regulatory interactions,
        it was designed and validated on real biological data from bacterial regulons.
        In this paper, we put primary focus on CyGenexpi: a plugin integrating Genexpi
        with the Cytoscape software for ease of use. As a part of this effort, a plugin
        for handling time series data in Cytoscape called CyDataseries has been developed
        and made available. Genexpi is also available as a standalone command line
        tool and an R package. Conclusions: Genexpi is a useful part of gene network
        inference toolbox. It provides meaningful information about the composition
        of regulons and delivers biologically interpretable results.'
      authors:
      - name: Modrak M.
      - name: Vohradsky J.
      citationCount: 9
      date: '2018-04-13T00:00:00Z'
      journal: BMC Bioinformatics
      title: 'Genexpi: A toolset for identifying regulons and validating gene regulatory
        networks using time-course expression data'
    note: null
    pmcid: PMC5899412
    pmid: '29653518'
    type: []
    version: 1.3.0
  relation: []
  toolType:
  - Plug-in
  topic:
  - term: Gene regulation
    uri: http://edamontology.org/topic_0204
  validated: 1
  version:
  - 1.4.2
  - 1.3.0
- accessibility: Open access
  additionDate: '2020-12-21T12:36:03Z'
  biotoolsCURIE: biotools:cgi
  biotoolsID: cgi
  collectionID:
  - BBG genomic tools
  - RIS3CAT VEIS
  confidence_flag: null
  cost: Free of charge (with restrictions)
  credit:
  - email: null
    fundrefid: null
    gridid: null
    name: La Marato TV3
    note: null
    orcidid: null
    rorid: null
    typeEntity: Funding agency
    typeRole: []
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: European Research Council
    note: null
    orcidid: null
    rorid: null
    typeEntity: Funding agency
    typeRole: []
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: AECC
    note: null
    orcidid: null
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    typeEntity: Funding agency
    typeRole: []
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  - email: null
    fundrefid: null
    gridid: null
    name: Spanish Ministry of Economy and Competitiveness
    note: null
    orcidid: null
    rorid: null
    typeEntity: Funding agency
    typeRole: []
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: H2020-EU.3.1.6. - Health care provision and integrated care
    note: null
    orcidid: null
    rorid: null
    typeEntity: Funding agency
    typeRole: []
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: AGAUR
    note: null
    orcidid: null
    rorid: null
    typeEntity: Funding agency
    typeRole: []
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: UPF
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole: []
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: IRB Barcelona
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
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  description: Cancer Genome Interpreter (CGI) is designed to support the identification
    of tumor alterations that drive the disease and detect those that may be therapeutically
    actionable. CGI relies on existing knowledge collected from several resources
    and on computational methods that annotate the alterations in a tumor according
    to distinct levels of evidence.
  documentation:
  - note: null
    type:
    - FAQ
    - User manual
    - General
    url: https://www.cancergenomeinterpreter.org/faq
  - note: null
    type:
    - Terms of use
    url: https://creativecommons.org/licenses/by-nc/4.0/
  download: []
  editPermission:
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    - Iker
    - jordi.deu@upf.edu
    - sgonzal
    type: group
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Sequence variations
        uri: http://edamontology.org/data_3498
      format:
      - term: TSV
        uri: http://edamontology.org/format_3475
      - term: VCF
        uri: http://edamontology.org/format_3016
    - data:
        term: Phenotype name
        uri: http://edamontology.org/data_3275
      format:
      - term: plain text format (unformatted)
        uri: http://edamontology.org/format_1964
    note: Identifying all the potential driver genes on a list of somatic mutations.
    operation:
    - term: Variant effect prediction
      uri: http://edamontology.org/operation_0331
    output:
    - data:
        term: Feature table
        uri: http://edamontology.org/data_1270
      format:
      - term: TSV
        uri: http://edamontology.org/format_3475
  - cmd: null
    input:
    - data:
        term: Sequence variations
        uri: http://edamontology.org/data_3498
      format:
      - term: VCF
        uri: http://edamontology.org/format_3016
      - term: TSV
        uri: http://edamontology.org/format_3475
    - data:
        term: Phenotype name
        uri: http://edamontology.org/data_3275
      format:
      - term: plain text format (unformatted)
        uri: http://edamontology.org/format_1964
    note: Providing list of biomarkers and cancer treatments based on genomic annotations
    operation:
    - term: Gene functional annotation
      uri: http://edamontology.org/operation_3672
    output:
    - data:
        term: Database search results
        uri: http://edamontology.org/data_2080
      format:
      - term: TSV
        uri: http://edamontology.org/format_3475
  homepage: https://www.cancergenomeinterpreter.org/
  homepage_status: 0
  language:
  - Python
  - JavaScript
  lastUpdate: '2024-11-24T20:16:52.724131Z'
  license: Apache-2.0
  link:
  - note: null
    type:
    - Other
    url: https://www.cancergenomeinterpreter.org
  maturity: Mature
  name: Cancer Genome Interpreter (CGI)
  operatingSystem:
  - Linux
  otherID: []
  owner: nlopezb
  publication:
  - doi: 10.1186/s13073-018-0531-8
    metadata:
      abstract: While tumor genome sequencing has become widely available in clinical
        and research settings, the interpretation of tumor somatic variants remains
        an important bottleneck. Here we present the Cancer Genome Interpreter, a
        versatile platform that automates the interpretation of newly sequenced cancer
        genomes, annotating the potential of alterations detected in tumors to act
        as drivers and their possible effect on treatment response. The results are
        organized in different levels of evidence according to current knowledge,
        which we envision can support a broad range of oncology use cases. The resource
        is publicly available at http://www.cancergenomeinterpreter.org.
      authors:
      - name: Tamborero D.
      - name: Rubio-Perez C.
      - name: Deu-Pons J.
      - name: Schroeder M.P.
      - name: Vivancos A.
      - name: Rovira A.
      - name: Tusquets I.
      - name: Albanell J.
      - name: Rodon J.
      - name: Tabernero J.
      - name: de Torres C.
      - name: Dienstmann R.
      - name: Gonzalez-Perez A.
      - name: Lopez-Bigas N.
      citationCount: 354
      date: '2018-03-28T00:00:00Z'
      journal: Genome Medicine
      title: Cancer Genome Interpreter annotates the biological and clinical relevance
        of tumor alterations
    note: null
    pmcid: PMC5875005
    pmid: '29592813'
    type: []
    version: null
  relation:
  - biotoolsID: boostdm
    type: uses
  toolType:
  - Command-line tool
  - Web application
  - Web API
  topic:
  - term: Computational biology
    uri: http://edamontology.org/topic_3307
  - term: Oncology
    uri: http://edamontology.org/topic_2640
  - term: Bioinformatics
    uri: http://edamontology.org/topic_0091
  validated: 0
  version:
  - '1.0'
- accessibility: Open access
  additionDate: '2015-10-07T18:29:49Z'
  biotoolsCURIE: biotools:pdb-redo
  biotoolsID: pdb-redo
  collectionID:
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  - DRCAT
  - 3D-BioInfo-Structure-Function
  - 3D-BioInfo-Nucleic-Acid
  - 3D-BioInfo-Protein-Ligand-Interactions
  - INSTRUCT
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: r.joosten@nki.nl
    fundrefid: null
    gridid: null
    name: Robbie P. Joosten
    note: null
    orcidid: https://orcid.org/0000-0002-2323-2686
    rorid: null
    typeEntity: Person
    typeRole:
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    - Developer
    url: null
  - email: vriend@cmbi.ru.nl
    fundrefid: null
    gridid: null
    name: Gert Vriend
    note: Project initiator
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  - email: a.perrakis@nki.nl
    fundrefid: null
    gridid: null
    name: Anastassis Perrakis
    note: null
    orcidid: https://orcid.org/0000-0002-1151-6227
    rorid: null
    typeEntity: Person
    typeRole:
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    url: null
  - email: m.hekkelman@nki.nl
    fundrefid: null
    gridid: null
    name: Maarten Hekkelman
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
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    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Bart van Beusekom
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
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    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Krista Joosten
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
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    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Netherlands Organization for Scientific Research (NWO)
    note: Various grants (Veni, Vidi, TOP)
    orcidid: null
    rorid: null
    typeEntity: Funding agency
    typeRole: []
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: West-Life Horizon 2020
    note: null
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    rorid: null
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    name: iNEXT
    note: null
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    url: null
  - email: null
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    note: Financial and other support
    orcidid: null
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    typeEntity: Project
    typeRole:
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    url: https://www.ccp4.ac.uk
  description: Databank of optimised macromolecular structures. PDB-REDO entries are
    refined, rebuilt and validated with one consistent protocol using the equivalent
    entry in the Protein Data Bank and its experimental data. PDB-REDO entries typically
    have higher structural quality and a better fit to the experimental data.
  documentation:
  - note: null
    type:
    - General
    url: https://pdb-redo.eu
  download:
  - note: null
    type: Downloads page
    url: https://pdb-redo.eu/download-info.html
    version: null
  editPermission:
    authors:
    - rjoosten
    type: group
  elixirCommunity:
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  elixirNode: []
  elixirPlatform:
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  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: PDB ID
        uri: http://edamontology.org/data_1127
      format: []
    note: null
    operation:
    - term: Query and retrieval
      uri: http://edamontology.org/operation_0224
    output:
    - data:
        term: Structure
        uri: http://edamontology.org/data_0883
      format:
      - term: mmCIF
        uri: http://edamontology.org/format_1477
      - term: PDB
        uri: http://edamontology.org/format_1476
    - data:
        term: Protein structural quality report
        uri: http://edamontology.org/data_1539
      format:
      - term: JSON
        uri: http://edamontology.org/format_3464
      - term: Textual format
        uri: http://edamontology.org/format_2330
    - data:
        term: Electron density map
        uri: http://edamontology.org/data_0937
      format: []
    - data:
        term: Protein structure
        uri: http://edamontology.org/data_1460
      format:
      - term: dssp
        uri: http://edamontology.org/format_1454
  homepage: https://pdb-redo.eu
  homepage_status: 0
  language: []
  lastUpdate: '2024-11-24T20:12:11.088870Z'
  license: Freeware
  link: []
  maturity: Mature
  name: PDB-REDO databank of optimised macromolecular structures
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: rjoosten
  publication:
  - doi: 10.1107/s0907444911054515
    metadata:
      abstract: Developments of the PDB-REDO procedure that combine re-refinement
        and rebuilding within a unique decision-making framework to improve structures
        in the PDB are presented. PDB-REDO uses a variety of existing and custom-built
        software modules to choose an optimal refinement protocol (e.g. anisotropic,
        isotropic or overall B-factor refinement, TLS model) and to optimize the geometry
        versus data-refinement weights. Next, it proceeds to rebuild side chains and
        peptide planes before a final optimization round. PDB-REDO works fully automatically
        without the need for intervention by a crystallographic expert. The pipeline
        was tested on 12 000 PDB entries and the great majority of the test cases
        improved both in terms of crystallographic criteria such as R free and in
        terms of widely accepted geometric validation criteria. It is concluded that
        PDB-REDO is useful to update the otherwise static structures in the PDB to
        modern crystallographic standards. The publically available PDB-REDO database
        provides better model statistics and contributes to better refinement and
        validation targets. © International Union of Crystallography 2012.
      authors:
      - name: Joosten R.P.
      - name: Joosten K.
      - name: Murshudov G.N.
      - name: Perrakis A.
      citationCount: 179
      date: '2012-04-01T00:00:00Z'
      journal: 'Acta Crystallographica Section D: Biological Crystallography'
      title: 'PDB-REDO: Constructive validation, more than just looking for errors'
    note: null
    pmcid: PMC3322608
    pmid: '22505269'
    type: []
    version: null
  - doi: 10.1107/s0021889809008784
    metadata:
      abstract: Structural biology, homology modelling and rational drug design require
        accurate three-dimensional macromolecular coordinates. However, the coordinates
        in the Protein Data Bank (PDB) have not all been obtained using the latest
        experimental and computational methods. In this study a method is presented
        for automated re-refinement of existing structure models in the PDB. A large-scale
        benchmark with 16 807 PDB entries showed that they can be improved in terms
        of fit to the deposited experimental X-ray data as well as in terms of geometric
        quality. The re-refinement protocol uses TLS models to describe concerted
        atom movement. The resulting structure models are made available through the
        PDB-REDO databank (http://www.cmbi.ru.nl/pdb-redo/). Grid computing techniques
        were used to overcome the computational requirements of this endeavour. ©
        2009 International Union of Crystallography.
      authors:
      - name: Joosten R.P.
      - name: Salzemann J.
      - name: Bloch V.
      - name: Stockinger H.
      - name: Berglund A.-C.
      - name: Blanchet C.
      - name: Bongcam-Rudloff E.
      - name: Combet C.
      - name: Da Costa A.L.
      - name: Deleage G.
      - name: Diarena M.
      - name: Fabbretti R.
      - name: Fettahi G.
      - name: Flegel V.
      - name: Gisel A.
      - name: Kasam V.
      - name: Kervinen T.
      - name: Korpelainen E.
      - name: Mattila K.
      - name: Pagni M.
      - name: Reichstadt M.
      - name: Breton V.
      - name: Tickle I.J.
      - name: Vriend G.
      citationCount: 185
      date: '2009-01-01T00:00:00Z'
      journal: Journal of Applied Crystallography
      title: 'PDB-REDO: Automated re-refinement of X-ray structure models in the PDB'
    note: null
    pmcid: PMC3246819
    pmid: '22477769'
    type: []
    version: null
  - doi: 10.1107/s0907444908037591
    metadata:
      abstract: The deposition of X-ray data along with the customary structural models
        defining PDB entries makes it possible to apply large-scale re-refinement
        protocols to these entries, thus giving users the benefit of improvements
        in X-ray methods that have occurred since the structure was deposited. Automated
        gradient refinement is an effective method to achieve this goal, but real-space
        intervention is most often required in order to adequately address problems
        detected by structure-validation software. In order to improve the existing
        protocol, automated re-refinement was combined with structure validation and
        difference-density peak analysis to produce a catalogue of problems in PDB
        entries that are amenable to automatic correction. It is shown that re-refinement
        can be effective in producing improvements, which are often associated with
        the systematic use of the TLS parameterization of B factors, even for relatively
        new and high-resolution PDB entries, while the accompanying manual or semi-manual
        map analysis and fitting steps show good prospects for eventual automation.
        It is proposed that the potential for simultaneous improvements in methods
        and in re-refinement results be further encouraged by broadening the scope
        of depositions to include refinement metadata and ultimately primary rather
        than reduced X-ray data.
      authors:
      - name: Joosten R.P.
      - name: Womack T.
      - name: Vriend G.
      - name: Bricogne G.
      citationCount: 69
      date: '2009-01-20T00:00:00Z'
      journal: 'Acta Crystallographica Section D: Biological Crystallography'
      title: Re-refinement from deposited X-ray data can deliver improved models for
        most PDB entries
    note: null
    pmcid: PMC2631631
    pmid: '19171973'
    type: []
    version: null
  - doi: 10.1107/s2052252518010552
    metadata:
      abstract: Inherent protein flexibility, poor or low-resolution diffraction data
        or poorly defined electron-density maps often inhibit the building of complete
        structural models during X-ray structure determination. However, recent advances
        in crystallographic refinement and model building often allow completion of
        previously missing parts. This paper presents algorithms that identify regions
        missing in a certain model but present in homologous structures in the Protein
        Data Bank (PDB), and 'graft' these regions of interest. These new regions
        are refined and validated in a fully automated procedure. Including these
        developments in the PDB-REDO pipeline has enabled the building of 24 962 missing
        loops in the PDB. The models and the automated procedures are publicly available
        through the PDB-REDO databank and webserver. More complete protein structure
        models enable a higher quality public archive but also a better understanding
        of protein function, better comparison between homologous structures and more
        complete data mining in structural bioinformatics projects.
      authors:
      - name: Van Beusekom B.
      - name: Joosten K.
      - name: Hekkelman M.L.
      - name: Joosten R.P.
      - name: Perrakis A.
      citationCount: 22
      date: '2018-01-01T00:00:00Z'
      journal: IUCrJ
      title: Homology-based loop modeling yields more complete crystallographic protein
        structures
    note: null
    pmcid: PMC6126648
    pmid: '30224962'
    type: []
    version: null
  - doi: 10.1002/pro.3353
    metadata:
      abstract: 'The Protein Data Bank (PDB) is the global archive for structural
        information on macromolecules, and a popular resource for researchers, teachers,
        and students, amassing more than one million unique users each year. Crystallographic
        structure models in the PDB (more than 100,000 entries) are optimized against
        the crystal diffraction data and geometrical restraints. This process of crystallographic
        refinement typically ignored hydrogen bond (H-bond) distances as a source
        of information. However, H-bond restraints can improve structures at low resolution
        where diffraction data are limited. To improve low-resolution structure refinement,
        we present methods for deriving H-bond information either globally from well-refined
        high-resolution structures from the PDB-REDO databank, or specifically from
        on-the-fly constructed sets of homologous high-resolution structures. Refinement
        incorporating HOmology DErived Restraints (HODER), improves geometrical quality
        and the fit to the diffraction data for many low-resolution structures. To
        make these improvements readily available to the general public, we applied
        our new algorithms to all crystallographic structures in the PDB: using massively
        parallel computing, we constructed a new instance of the PDB-REDO databank
        (https://pdb-redo.eu). This resource is useful for researchers to gain insight
        on individual structures, on specific protein families (as we demonstrate
        with examples), and on general features of protein structure using data mining
        approaches on a uniformly treated dataset.'
      authors:
      - name: van Beusekom B.
      - name: Touw W.G.
      - name: Tatineni M.
      - name: Somani S.
      - name: Rajagopal G.
      - name: Luo J.
      - name: Gilliland G.L.
      - name: Perrakis A.
      - name: Joosten R.P.
      citationCount: 41
      date: '2018-03-01T00:00:00Z'
      journal: Protein Science
      title: Homology-based hydrogen bond information improves crystallographic structures
        in the PDB
    note: Algorithms for homology restrains; new databank
    pmcid: PMC5818736
    pmid: '29168245'
    type:
    - Method
    version: '7'
  - doi: 10.1093/bioinformatics/btr590
    metadata:
      abstract: 'Motivation: Macromolecular crystal structures in the Protein Data
        Bank (PDB) are a key source of structural insight into biological processes.
        These structures, some >30 years old, were constructed with methods of their
        era. With PDB_REDO, we aim to automatically optimize these structures to better
        fit their corresponding experimental data, passing the benefits of new methods
        in crystallography on to a wide base of non-crystallographer structure users.
        Results: We developed new algorithms to allow automatic rebuilding and remodeling
        of main chain peptide bonds and side chains in crystallographic electron density
        maps, and incorporated these and further enhancements in the PDB_REDO procedure.
        Applying the updated PDB_REDO to the oldest, but also to some of the newest
        models in the PDB, corrects existing modeling errors and brings these models
        to a higher quality, as judged by standard validation methods. © The Author(s)
        2011. Published by Oxford University Press.'
      authors:
      - name: Joosten R.P.
      - name: Joosten K.
      - name: Cohen S.X.
      - name: Vriend G.
      - name: Perrakis A.
      citationCount: 85
      date: '2011-12-01T00:00:00Z'
      journal: Bioinformatics
      title: Automatic rebuilding and optimization of crystallographic structures
        in the Protein Data Bank
    note: Algorithms for model rebuilding
    pmcid: PMC3232375
    pmid: '22034521'
    type:
    - Method
    version: null
  - doi: 10.1016/j.jmb.2016.02.002
    metadata:
      abstract: Structure validation is a key component of all steps in the structure
        determination process, from structure building, refinement, deposition, and
        evaluation all the way to post-deposition optimisation of structures in the
        Protein Data Bank (PDB) by re-refinement and re-building. Today, many aspects
        of protein structures are understood better than 10 years ago, and combined
        with improved software and more computing power, the automated PDB-REDO procedure
        can significantly improve about 85% of all X-ray structures ever deposited
        in the PDB. We review structure validation, structure improvement, and a series
        of validation resources and facilities that give access to improved PDB files
        and to reports on the quality of the original and the improved structures.
        Post-deposition optimisation generally leads to improved protein structures
        and a series of examples will illustrate how that, in turn, leads to improved
        or even novel biological insights.
      authors:
      - name: Touw W.G.
      - name: Joosten R.P.
      - name: Vriend G.
      citationCount: 27
      date: '2016-03-27T00:00:00Z'
      journal: Journal of Molecular Biology
      title: New Biological Insights from Better Structure Models
    note: Algorithms for correction and completion of N-glycosylation sites
    pmcid: null
    pmid: '26869101'
    type:
    - Method
    version: null
  - doi: 10.1107/s2059798316013036
    metadata:
      abstract: Many crystal structures in the Protein Data Bank contain zinc ions
        in a geometrically distorted tetrahedral complex with four Cys and/or His
        ligands. A method is presented to automatically validate and correct these
        zinc complexes. Analysis of the corrected zinc complexes shows that the average
        ZnCys distances and Cys-Zn-Cys angles are a function of the number of cysteines
        and histidines involved. The observed trends can be used to develop more contextsensitive
        targets for model validation and refinement.
      authors:
      - name: Touw W.G.
      - name: Van Beusekom B.
      - name: Evers J.M.G.
      - name: Vriend G.
      - name: Joosten R.P.
      citationCount: 24
      date: '2016-01-01T00:00:00Z'
      journal: 'Acta Crystallographica Section D: Structural Biology'
      title: Validation and correction of ZnCysxHisy complexes
    note: null
    pmcid: PMC5053137
    pmid: '27710932'
    type: []
    version: null
  - doi: 10.1107/s2059798319003875
    metadata:
      abstract: N-Glycosylation is one of the most common post-translational modifications
        and is implicated in, for example, protein folding and interaction with ligands
        and receptors. N-Glycosylation trees are complex structures of linked carbohydrate
        residues attached to asparagine residues. While carbohydrates are typically
        modeled in protein structures, they are often incomplete or have the wrong
        chemistry. Here, new tools are presented to automatically rebuild existing
        glycosylation trees, to extend them where possible, and to add new glycosylation
        trees if they are missing from the model. The method has been incorporated
        in the PDB-REDO pipeline and has been applied to build or rebuild 16 452 carbohydrate
        residues in 11 651 glycosylation trees in 4498 structure models, and is also
        available from the PDB-REDO web server. With better modeling of N-glycosylation,
        the biological function of this important modification can be better and more
        easily understood.
      authors:
      - name: van Beusekom B.
      - name: Wezel N.
      - name: Hekkelman M.L.
      - name: Perrakis A.
      - name: Emsley P.
      - name: Joosten R.P.
      citationCount: 19
      date: '2019-04-01T00:00:00Z'
      journal: 'Acta Crystallographica Section D: Structural Biology'
      title: Building and rebuilding N-glycans in protein structure models
    note: null
    pmcid: PMC6465985
    pmid: '30988258'
    type: []
    version: null
  relation: []
  toolType:
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  topic:
  - term: Structure analysis
    uri: http://edamontology.org/topic_0081
  validated: 1
  version: []
- accessibility: Open access
  additionDate: '2018-07-04T13:50:50Z'
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    fundrefid: null
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  description: Unified platform for comprehensive data fitting and analysis of protein
    thermal denaturation data. Allows simultaneous global data fitting using any combination
    of input data types and offers 12 protein unfolding pathway models for selection,
    including irreversible transitions often missing from other tools. The data fitting
    produces optimal parameter values, their confidence intervals, and statistical
    information to define unfolding pathways.
  documentation:
  - note: null
    type:
    - User manual
    url: https://loschmidt.chemi.muni.cz/calfitter/?action=help&
  - note: null
    type:
    - Training material
    url: https://loschmidt.chemi.muni.cz/calfitter/?action=example&
  - note: null
    type:
    - Terms of use
    url: https://loschmidt.chemi.muni.cz/calfitter/?action=terms&
  download: []
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  function:
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    input:
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        term: Experimental measurement
        uri: http://edamontology.org/data_3108
      format:
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        uri: http://edamontology.org/format_3620
    note: null
    operation:
    - term: Protein folding analysis
      uri: http://edamontology.org/operation_2415
    output:
    - data:
        term: Mathematical model
        uri: http://edamontology.org/data_0950
      format:
      - term: xlsx
        uri: http://edamontology.org/format_3620
  homepage: https://loschmidt.chemi.muni.cz/calfitter/
  homepage_status: 0
  language:
  - JavaScript
  - Java
  - Python
  lastUpdate: '2024-11-24T15:37:32.557978Z'
  license: Proprietary
  link: []
  maturity: Mature
  name: CalFitter
  operatingSystem:
  - Linux
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  otherID: []
  owner: Loschmidt Laboratories
  publication:
  - doi: 10.1093/nar/gky358
    metadata:
      abstract: Despite significant advances in the understanding of protein structure-function
        relationships, revealing protein folding pathways still poses a challenge
        due to a limited number of relevant experimental tools. Widely-used experimental
        techniques, such as calorimetry or spectroscopy, critically depend on a proper
        data analysis. Currently, there are only separate data analysis tools available
        for each type of experiment with a limited model selection. To address this
        problem, we have developed the CalFitter web server to be a unified platform
        for comprehensive data fitting and analysis of protein thermal denaturation
        data. The server allows simultaneous global data fitting using any combination
        of input data types and offers 12 protein unfolding pathway models for selection,
        including irreversible transitions often missing from other tools. The data
        fitting produces optimal parameter values, their confidence intervals, and
        statistical information to define unfolding pathways. The server provides
        an interactive and easy-to-use interface that allows users to directly analyse
        input datasets and simulate modelled output based on the model parameters.
        CalFitter web server is available free at https://loschmidt.chemi.muni.cz/calfitter/.
      authors:
      - name: Mazurenko S.
      - name: Stourac J.
      - name: Kunka A.
      - name: Nedeljkovic S.
      - name: Bednar D.
      - name: Prokop Z.
      - name: Damborsky J.
      citationCount: 30
      date: '2018-07-02T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'CalFitter: A web server for analysis of protein thermal denaturation
        data'
    note: null
    pmcid: PMC6031030
    pmid: '29762722'
    type: []
    version: '1.3'
  - doi: 10.1093/nar/gkac378
    metadata:
      abstract: The importance of the quantitative description of protein unfolding
        and aggregation for the rational design of stability or understanding the
        molecular basis of protein misfolding diseases is well established. Protein
        thermostability is typically assessed by calorimetric or spectroscopic techniques
        that monitor different complementary signals during unfolding. The CalFitter
        webserver has already proved integral to deriving invaluable energy parameters
        by global data analysis. Here, we introduce CalFitter 2.0, which newly incorporates
        singular value decomposition (SVD) of multi-wavelength spectral datasets into
        the global fitting pipeline. Processed time- or temperature-evolved SVD components
        can now be fitted together with other experimental data types. Moreover, deconvoluted
        basis spectra provide spectral fingerprints of relevant macrostates populated
        during unfolding, which greatly enriches the information gains of the CalFitter
        output. The SVD analysis is fully automated in a highly interactive module,
        providing access to the results to users without any prior knowledge of the
        underlying mathematics. Additionally, a novel data uploading wizard has been
        implemented to facilitate rapid and easy uploading of multiple datasets. Together,
        the newly introduced changes significantly improve the user experience, making
        this software a unique, robust, and interactive platform for the analysis
        of protein thermal denaturation data. The webserver is freely accessible at
        https://loschmidt.chemi.muni.cz/calfitter.
      authors:
      - name: Kunka A.
      - name: Lacko D.
      - name: Stourac J.
      - name: Damborsky J.
      - name: Prokop Z.
      - name: Mazurenko S.
      citationCount: 4
      date: '2022-07-05T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'CalFitter 2.0: Leveraging the power of singular value decomposition
        to analyse protein thermostability'
    note: null
    pmcid: PMC9252748
    pmid: '35580052'
    type: []
    version: '2.0'
  relation: []
  toolType:
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  topic:
  - term: Protein folding, stability and design
    uri: http://edamontology.org/topic_0130
  - term: Applied mathematics
    uri: http://edamontology.org/topic_3569
  - term: Proteomics
    uri: http://edamontology.org/topic_0121
  - term: Proteins
    uri: http://edamontology.org/topic_0078
  validated: 1
  version:
  - '2.0'
- accessibility: null
  additionDate: '2016-10-03T14:08:37Z'
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    name: European H2020 e-Infrastructure grant, EGI-Engage, grant no. 654142
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    name: European H2020 e-Infrastructure grant, BioExcel, grant no. 675728
    note: null
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    typeEntity: Funding agency
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    name: Netherlands Organization for Scientific Research (NWO), VICI grant no. 700.96.442
    note: null
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    rorid: null
    typeEntity: Funding agency
    typeRole: []
    url: null
  - email: null
    fundrefid: null
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    name: Netherlands Organization for Scientific Research (NWO) , TOP-PUNT grant
      no. 718.015.001
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    typeEntity: Funding agency
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    name: European H2020 e-Infrastructure grant, BioExcel, grant no. 823830
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    typeRole: []
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  - email: null
    fundrefid: null
    gridid: null
    name: European H2020 e-Infrastructure grant, EOSC-Hub, grant no.777536
    note: null
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    rorid: null
    typeEntity: Funding agency
    typeRole: []
    url: null
  description: 'High Ambiguity Driven biomolecular DOCKing: an information-driven
    flexible docking approach for the modeling of biomolecular complexes. It distinguishes
    itself from ab-initio docking methods in the fact that it encodes information
    from identified or predicted protein interfaces in ambiguous interaction restraints
    (AIRs) to drive the docking process. It can deal with a large class of modeling
    problems including protein-protein, protein-nucleic acids and protein-ligand complexes.'
  documentation:
  - note: Various tutorials describing the use of the HADDOCK server for various scenarios.;
      Tutorial
    type:
    - Training material
    url: http://www.bonvinlab.org/education/
  - note: Recording of a lecture of Prof. Bonvin at the CECAM BImMS 2019 workshop
      in Lugano (Oct. 7th, 2019)
    type:
    - Training material
    url: https://youtu.be/KUbEwGv21n8
  - note: HADDOCK2.2 online manual
    type:
    - User manual
    url: http://www.bonvinlab.org/software/haddock2.2/manual/
  - note: HADDOCK2.4 online manual
    type:
    - User manual
    url: http://www.bonvinlab.org/software/haddock2.4/manual/
  - note: BioExcel2020 summerschool - Integrative modelling lecture by Alexandre Bonvin
    type:
    - Training material
    url: https://www.youtube.com/watch?v=AULTBI3BqRY
  download:
  - note: null
    type: Downloads page
    url: http://www.bonvinlab.org/software/haddock2.4/download/
    version: '2.4'
  editPermission:
    authors:
    - jdianes
    type: group
  elixirCommunity:
  - 3D-BioInfo
  elixirNode:
  - Netherlands
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Molecular docking
      uri: http://edamontology.org/operation_0478
    output: []
  homepage: http://www.bonvinlab.org/software/haddock2.4/
  homepage_status: 0
  language: []
  lastUpdate: '2024-11-24T15:23:11.797426Z'
  license: null
  link:
  - note: HADDOCK2.2 software page
    type:
    - Repository
    url: http://www.bonvinlab.org/software/haddock2.2
  - note: HADDOCK2.4 software page
    type:
    - Repository
    url: http://www.bonvinlab.org/software/haddock2.4
  - note: HADDOCK2.4 web server
    type:
    - Service
    url: https://wenmr.science.uu.nl/haddock2.4
  - note: HADDOCK forum
    type:
    - Discussion forum
    url: https://ask.bioexcel.eu/c/haddock
  maturity: Mature
  name: HADDOCK
  operatingSystem:
  - Linux
  - Mac
  otherID: []
  owner: a.m.j.j.bonvin@uu.nl
  publication:
  - doi: 10.1016/j.jmb.2015.09.014
    metadata:
      abstract: The prediction of the quaternary structure of biomolecular macromolecules
        is of paramount importance for fundamental understanding of cellular processes
        and drug design. In the era of integrative structural biology, one way of
        increasing the accuracy of modeling methods used to predict the structure
        of biomolecular complexes is to include as much experimental or predictive
        information as possible in the process. This has been at the core of our information-driven
        docking approach HADDOCK. We present here the updated version 2.2 of the HADDOCK
        portal, which offers new features such as support for mixed molecule types,
        additional experimental restraints and improved protocols, all of this in
        a user-friendly interface. With well over 6000 registered users and 108,000
        jobs served, an increasing fraction of which on grid resources, we hope that
        this timely upgrade will help the community to solve important biological
        questions and further advance the field. The HADDOCK2.2 Web server is freely
        accessible to non-profit users at http://haddock.science.uu.nl/services/HADDOCK2.2.
      authors:
      - name: Van Zundert G.C.P.
      - name: Rodrigues J.P.G.L.M.
      - name: Trellet M.
      - name: Schmitz C.
      - name: Kastritis P.L.
      - name: Karaca E.
      - name: Melquiond A.S.J.
      - name: Van Dijk M.
      - name: De Vries S.J.
      - name: Bonvin A.M.J.J.
      citationCount: 1929
      date: '2016-02-22T00:00:00Z'
      journal: Journal of Molecular Biology
      title: 'The HADDOCK2.2 Web Server: User-Friendly Integrative Modeling of Biomolecular
        Complexes'
    note: null
    pmcid: null
    pmid: '26410586'
    type:
    - Primary
    version: null
  - doi: 10.1021/ja026939x
    metadata:
      abstract: The structure determination of protein-protein complexes is a rather
        tedious and lengthy process, by both NMR and X-ray crystallography. Several
        methods based on docking to study protein complexes have also been well developed
        over the past few years. Most of these approaches are not driven by experimental
        data but are based on a combination of energetics and shape complementarity.
        Here, we present an approach called HADDOCK (High Ambiguity Driven protein-protein
        Docking) that makes use of biochemical and/or biophysical interaction data
        such as chemical shift perturbation data resulting from NMR titration experiments
        or mutagenesis data. This information is introduced as Ambiguous Interaction
        Restraints (AIRs) to drive the docking process. An AIR is defined as an ambiguous
        distance between all residues shown to be involved in the interaction. The
        accuracy of our approach is demonstrated with three molecular complexes. For
        two of these complexes, for which both the complex and the free protein structures
        have been solved, NMR titration data were available. Mutagenesis data were
        used in the last example. In all cases, the best structures generated by HADDOCK,
        that is, the structures with the lowest intermolecular energies, were the
        closest to the published structure of the respective complexes (within 2.0
        Å backbone RMSD).
      authors:
      - name: Dominguez C.
      - name: Boelens R.
      - name: Bonvin A.M.J.J.
      citationCount: 2472
      date: '2003-02-15T00:00:00Z'
      journal: Journal of the American Chemical Society
      title: 'HADDOCK: A protein-protein docking approach based on biochemical or
        biophysical information'
    note: null
    pmcid: null
    pmid: '12580598'
    type:
    - Primary
    version: null
  - doi: 10.1016/j.str.2015.03.014
    metadata:
      abstract: Protein-protein interactions play a central role in all cellular processes.
        Insight into their atomic architecture is therefore of paramount importance.
        Cryo-electron microscopy (cryo-EM) is capable of directly imaging large macromolecular
        complexes. Unfortunately, the resolution is usually not sufficient for a direct
        atomic interpretation. To overcome this, cryo-EM data are often combined with
        high-resolution atomic structures. However, current computational approaches
        typically do not include information from other experimental sources nor a
        proper physico-chemical description of the interfaces. Here we describe the
        integration of cryo-EM data into our data-driven docking program HADDOCK and
        its performance on a benchmark of 17 complexes. The approach is demonstrated
        on five systems using experimental cryo-EM data in the range of 8.5-21 Å resolution.
        For several cases, cryo-EM data are integrated with additional interface information,
        e.g. mutagenesis and hydroxyl radical footprinting data. The resulting models
        have high-quality interfaces, revealing novel details of the interactions.
      authors:
      - name: Van Zundert G.C.P.
      - name: Melquiond A.S.J.
      - name: Bonvin A.M.J.J.
      citationCount: 57
      date: '2015-05-05T00:00:00Z'
      journal: Structure
      title: 'Integrative modeling of biomolecular complexes: HADDOCKing with Cryo-electron
        microscopy data'
    note: null
    pmcid: null
    pmid: '25914056'
    type:
    - Primary
    version: null
  - doi: 10.1111/febs.12771
    metadata:
      abstract: Protein interactions define the homeostatic state of the cell. Our
        ability to understand these interactions and their role in both health and
        disease is tied to our knowledge of the 3D atomic structure of the interacting
        partners and their complexes. Despite advances in experimental method of structure
        determination, the majority of known protein interactions are still missing
        an atomic structure. High-resolution methods such as X-ray crystallography
        and NMR spectroscopy struggle with the high-throughput demand, while low-resolution
        techniques such as cryo-electron microscopy or small-angle X-ray scattering
        provide data that are too coarse. Computational structure prediction of protein
        complexes, or docking, was first developed to complement experimental research
        and has since blossomed into an independent and lively field of research.
        Its most successful products are hybrid approaches that combine powerful algorithms
        with experimental data from various sources to generate high-resolution models
        of protein complexes. This minireview introduces the concept of docking and
        docking with the help of experimental data, compares and contrasts the available
        integrative docking methods, and provides a guide for the experimental researcher
        for what types of data and which particular software can be used to model
        a protein complex. © 2014 FEBS.
      authors:
      - name: Rodrigues J.P.G.L.M.
      - name: Bonvin A.M.J.J.
      citationCount: 83
      date: '2014-01-01T00:00:00Z'
      journal: FEBS Journal
      title: Integrative computational modeling of protein interactions
    note: null
    pmcid: null
    pmid: '24588898'
    type:
    - Primary
    version: null
  - doi: 10.1016/j.yjsbx.2019.100006
    metadata:
      abstract: The West-Life project (https://about.west-life.eu/)is a Horizon 2020
        project funded by the European Commission to provide data processing and data
        management services for the international community of structural biologists,
        and in particular to support integrative experimental approaches within the
        field of structural biology. It has developed enhancements to existing web
        services for structure solution and analysis, created new pipelines to link
        these services into more complex higher-level workflows, and added new data
        management facilities. Through this work it has striven to make the benefits
        of European e-Infrastructures more accessible to life-science researchers
        in general and structural biologists in particular.
      authors:
      - name: Morris C.
      - name: Andreetto P.
      - name: Banci L.
      - name: Bonvin A.M.J.J.
      - name: Chojnowski G.
      - name: Cano L.D.
      - name: Carazo J.M.
      - name: Conesa P.
      - name: Daenke S.
      - name: Damaskos G.
      - name: Giachetti A.
      - name: Haley N.E.C.
      - name: Hekkelman M.L.
      - name: Heuser P.
      - name: Joosten R.P.
      - name: Kouril D.
      - name: Krenek A.
      - name: Kulhanek T.
      - name: Lamzin V.S.
      - name: Nadzirin N.
      - name: Perrakis A.
      - name: Rosato A.
      - name: Sanderson F.
      - name: Segura J.
      - name: Schaarschmidt J.
      - name: Sobolev E.
      - name: Traldi S.
      - name: Trellet M.E.
      - name: Velankar S.
      - name: Verlato M.
      - name: Winn M.
      citationCount: 3
      date: '2019-01-01T00:00:00Z'
      journal: 'Journal of Structural Biology: X'
      title: 'West-Life: A Virtual Research Environment for structural biology'
    note: null
    pmcid: PMC7337051
    pmid: '32647812'
    type:
    - Usage
    version: null
  - doi: 10.1007/s10723-012-9246-z
    metadata:
      abstract: The WeNMR (http://www. wenmr. eu) project is a European Union funded
        international effort to streamline and automate analysis of Nuclear Magnetic
        Resonance (NMR) and Small Angle X-Ray scattering (SAXS) imaging data for atomic
        and near-atomic resolution molecular structures. Conventional calculation
        of structure requires the use of various software packages, considerable user
        expertise and ample computational resources. To facilitate the use of NMR
        spectroscopy and SAXS in life sciences the WeNMR consortium has established
        standard computational workflows and services through easy-to-use web interfaces,
        while still retaining sufficient flexibility to handle more specific requests.
        Thus far, a number of programs often used in structural biology have been
        made available through application portals. The implementation of these services,
        in particular the distribution of calculations to a Grid computing infrastructure,
        involves a novel mechanism for submission and handling of jobs that is independent
        of the type of job being run. With over 450 registered users (September 2012),
        WeNMR is currently the largest Virtual Organization (VO) in life sciences.
        With its large and worldwide user community, WeNMR has become the first Virtual
        Research Community officially recognized by the European Grid Infrastructure
        (EGI). © 2012 The Author(s).
      authors:
      - name: Wassenaar T.A.
      - name: van Dijk M.
      - name: Loureiro-Ferreira N.
      - name: van der Schot G.
      - name: de Vries S.J.
      - name: Schmitz C.
      - name: van der Zwan J.
      - name: Boelens R.
      - name: Giachetti A.
      - name: Ferella L.
      - name: Rosato A.
      - name: Bertini I.
      - name: Herrmann T.
      - name: Jonker H.R.A.
      - name: Bagaria A.
      - name: Jaravine V.
      - name: Guntert P.
      - name: Schwalbe H.
      - name: Vranken W.F.
      - name: Doreleijers J.F.
      - name: Vriend G.
      - name: Vuister G.W.
      - name: Franke D.
      - name: Kikhney A.
      - name: Svergun D.I.
      - name: Fogh R.H.
      - name: Ionides J.
      - name: Laue E.D.
      - name: Spronk C.
      - name: Jurksa S.
      - name: Verlato M.
      - name: Badoer S.
      - name: Dal Pra S.
      - name: Mazzucato M.
      - name: Frizziero E.
      - name: Bonvin A.M.J.J.
      citationCount: 163
      date: '2012-12-01T00:00:00Z'
      journal: Journal of Grid Computing
      title: 'WeNMR: Structural Biology on the Grid'
    note: null
    pmcid: null
    pmid: null
    type:
    - Primary
    version: null
  - doi: 10.1038/nprot.2010.32
    metadata:
      abstract: Computational docking is the prediction or modeling of the three-dimensional
        structure of a biomolecular complex, starting from the structures of the individual
        molecules in their free, unbound form. HADDOC K is a popular docking program
        that takes a datadriven approach to docking, with support for a wide range
        of experimental data. Here we present the HADDOC K web server protocol, facilitating
        the modeling of biomolecular complexes for a wide community. The main web
        interface is user-friendly, requiring only the structures of the individual
        components and a list of interacting residues as input. Additional web interfaces
        allow the more advanced user to exploit the full range of experimental data
        supported by HADDOC K and to customize the docking process. The HADDOC K server
        has access to the resources of a dedicated cluster and of the e-NMR GRID infrastructure.
        Therefore, a typical docking run takes only a few minutes to prepare and a
        few hours to complete. © 2010 Nature Publishing Group.
      authors:
      - name: De Vries S.J.
      - name: Van Dijk M.
      - name: Bonvin A.M.J.J.
      citationCount: 1122
      date: '2010-04-15T00:00:00Z'
      journal: Nature Protocols
      title: The HADDOCK web server for data-driven biomolecular docking
    note: null
    pmcid: null
    pmid: '20431534'
    type:
    - Primary
    version: null
  relation: []
  toolType:
  - Web application
  - Web service
  - Suite
  topic:
  - term: Protein interactions
    uri: http://edamontology.org/topic_0128
  validated: 1
  version:
  - '2.2'
  - '2.4'
next: ?page=2
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