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  description: Phylo-Movies is an open-source React and Flask web application, also
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  description: LifeSoaks was designed to find solvent channels in macromolecular structures
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  description: The electron density score for individual atoms (EDIA) quantifies the
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  description: SIENA is a software pipeline enabling the fully automated construction
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  description: DoGSite3 was developed for predicting robust and reliable small molecule
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  cost: Free of charge
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  description: Jalview is a free cross-platform program for multiple sequence alignment
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    and explore molecular structures and annotation.
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    url: https://www.jalview.org/about/citation
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      - term: FASTA
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      - term: FASTA-aln
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      - term: Pileup
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      - term: GFF2-seq
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      - term: BLC
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      - term: RNAML
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      - term: Format
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      - term: BioJSON (Jalview)
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      - term: ClustalW format
        uri: http://edamontology.org/format_1982
      - term: mmCIF
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      - term: PHYLIP format
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      - term: VCF
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      - term: Stockholm format
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      - term: GFF3-seq
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      - term: GCG MSF
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    - data:
        term: Structure alignment
        uri: http://edamontology.org/data_0886
      format:
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    note: 'Other Input formats:

      AMSA (.amsa);

      JnetFile (.concise, .jnet);

      PFAM (.pfam);

      Substitution matrix (.matrix);

      Jalview Project File (.jvp);

      Jalview Feature File (.features, .jvfeatures);

      Jalview Annotations File (.annotations, .jvannotations);

      Predicted Aligned Error (PAE) Matrix File (.json)

      ...

      Other Output formats:

      PFAM (.pfam);

      BioJS (.biojs) (interactive HTML/Javascript);

      Jalview Project File (.jvp);'
    operation:
    - term: Sequence alignment editing
      uri: http://edamontology.org/operation_3081
    - term: Phylogenetic tree analysis
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    - term: Sequence visualisation
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      - term: BLC
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      - term: BioJSON (Jalview)
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      - term: ClustalW format
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      - term: JSON
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      - term: PHYLIP format
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      - term: Stockholm format
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      - term: GCG MSF
        uri: http://edamontology.org/format_1947
    - data:
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        uri: http://edamontology.org/data_2884
      format:
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      - term: Format
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      - term: HTML
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      - term: SVG
        uri: http://edamontology.org/format_3604
      - term: PNG
        uri: http://edamontology.org/format_3603
  homepage: https://www.jalview.org/
  homepage_status: 0
  language: []
  lastUpdate: '2025-12-11T14:16:30.074724Z'
  license: GPL-3.0
  link:
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    type:
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  - note: null
    type:
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  - note: Latest development version
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  - note: null
    type:
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  - note: Twitter feed
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  - note: YouTube training videos
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  - note: null
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    url: https://www.linkedin.com/company/104771886/
  maturity: Mature
  name: Jalview
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    metadata:
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      authors: []
      citationCount: 7717
      date: '2009-05-07T00:00:00Z'
      journal: Bioinformatics
      title: Jalview Version 2-A multiple sequence alignment editor and analysis workbench
    note: null
    pmcid: PMC2672624
    pmid: '19151095'
    type: []
    version: null
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  toolType:
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  topic:
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  validated: 1
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  description: "HBAT (Hydrogen Bond Analysis Tool) is a package to automate the analysis\
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  validated: 1
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- accessibility: Open access (with restrictions)
  additionDate: '2022-04-22T14:17:27.559879Z'
  biotoolsCURIE: biotools:cellsys
  biotoolsID: cellsys
  collectionID:
  - PerMedCoE
  confidence_flag: null
  cost: null
  credit: []
  description: TiSim-CellSys is a modular software tool for efficient off-lattice
    simulation of growth and organization processes in multicellular systems in two
    and three dimensions. It implements an agent-based model that approximates cells
    as isotropic, elastic and adhesive objects. Cell migration is modeled by an equation
    of motion for each cell. The software includes many modules specifically tailored
    to support the simulation and analysis of virtual tissues including real-time
    3D visualization and VRML 2.0 support. All cell and environment parameters can
    be independently varied which facilitates species specific simulations and allows
    for detailed analyses of growth dynamics and links between cellular and multicellular
    phenotypes.
  documentation:
  - note: null
    type:
    - User manual
    url: https://www.hoehme.com/images/Software/cellsys_user_guide.pdf
  download:
  - note: null
    type: Binaries
    url: https://www.hoehme.com/software/tisim
    version: '5.0'
  editPermission:
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    - ArnauMontagud
    type: public
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  function:
  - cmd: null
    input:
    - data:
        term: Simulation
        uri: http://edamontology.org/data_3869
      format: []
    note: null
    operation:
    - term: Simulation analysis
      uri: http://edamontology.org/operation_0244
    output: []
  homepage: https://www.hoehme.com/software/tisim
  homepage_status: 0
  language: []
  lastUpdate: '2025-07-16T09:46:10.555167Z'
  license: null
  link: []
  maturity: null
  name: TiSim
  operatingSystem: []
  otherID: []
  owner: tntiniak
  publication:
  - doi: 10.1093/bioinformatics/btq437
    metadata:
      abstract: CellSys is a modular software tool for efficient off-lattice simulation
        of growth and organization processes in multi-cellular systems in 2D and 3D.
        It implements an agent-based model that approximates cells as isotropic, elastic
        and adhesive objects. Cell migration is modeled by an equation of motion for
        each cell. The software includes many modules specifically tailored to support
        the simulation and analysis of virtual tissues including real-time 3D visualization
        and VRML 2.0 support. All cell and environment parameters can be independently
        varied which facilitates species specific simulations and allows for detailed
        analyses of growth dynamics and links between cellular and multi-cellular
        phenotypes. © The Author(s) 2010. Published by Oxford University Press.
      authors:
      - name: Hoehme S.
      - name: Drasdo D.
      citationCount: 139
      date: '2010-08-13T00:00:00Z'
      journal: Bioinformatics
      title: A cell-based simulation software for multi-cellular systems
    note: null
    pmcid: PMC2951083
    pmid: '20709692'
    type: []
    version: null
  relation: []
  toolType: []
  topic:
  - term: Genotype and phenotype
    uri: http://edamontology.org/topic_0625
  - term: Cell biology
    uri: http://edamontology.org/topic_2229
  - term: Model organisms
    uri: http://edamontology.org/topic_0621
  validated: 0
  version:
  - '5.0'
- accessibility: null
  additionDate: '2025-07-07T09:04:03.787249Z'
  biotoolsCURIE: biotools:sqanti3
  biotoolsID: sqanti3
  collectionID: []
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: ana.conesa@csic.es
    fundrefid: null
    gridid: null
    name: Ana Conesa
    note: null
    orcidid: https://orcid.org/0000-0001-9597-311X
    rorid: null
    typeEntity: null
    typeRole: []
    url: null
  - email: pablo.atienza@csic.es
    fundrefid: null
    gridid: null
    name: Pablo Atienza
    note: Maintainer of SQANTI3
    orcidid: https://orcid.org/0009-0002-1093-693X
    rorid: null
    typeEntity: Person
    typeRole:
    - Maintainer
    url: null
  - email: fabian.robledo@csic.es
    fundrefid: null
    gridid: null
    name: Fabián Robledo
    note: Maintainer of SQANTI3 and ELIXIR-related contact
    orcidid: https://orcid.org/0009-0005-9047-3315
    rorid: null
    typeEntity: Person
    typeRole:
    - Maintainer
    url: null
  description: "SQANTI3 constitutes the first module of the Functional IsoTranscriptomics\
    \ (FIT) pipeline, which is an end-to-end strategy to perform isoform-level bioinformatics\
    \ analyses. \n\nThe SQANTI3 tool is designed to enable quality control and filtering\
    \ of long read-defined transcriptomes, which are often rich in artifacts and false-positive\
    \ isoforms. \n\nTherefore, a good curation of the transcriptome is indispensable\
    \ to proceed with FIT analysis and produce valid, biologically sound conclusions/hypothesis."
  documentation:
  - note: SQANTI3 main documentation resource
    type:
    - General
    url: https://github.com/ConesaLab/SQANTI3/wiki
  - note: null
    type:
    - Code of conduct
    url: https://github.com/ConesaLab/SQANTI3/blob/master/CODE_OF_CONDUCT.md
  - note: Command-line options and instructions for the QC submodule
    type:
    - Command-line options
    url: https://github.com/ConesaLab/SQANTI3/wiki/Running-SQANTI3-Quality-Control
  - note: Command-line options and instructions for the filter submodule
    type:
    - Command-line options
    url: https://github.com/ConesaLab/SQANTI3/wiki/Running-SQANTI3-filter
  - note: Command-line options and instructions for the rescue submodule
    type:
    - Command-line options
    url: https://github.com/ConesaLab/SQANTI3/wiki/Running-SQANTI3-rescue
  - note: Instructions to install and use sqanti, either in docker or apptainer containers
      or in a linux system
    type:
    - Installation instructions
    url: https://github.com/ConesaLab/SQANTI3/wiki/Dependencies-and-installation
  - note: Basic tutorial with examples to start using SQANTI3
    type:
    - Quick start guide
    url: https://github.com/ConesaLab/SQANTI3/wiki/Tutorial:-running-SQANTI3-on-an-example-dataset
  - note: Changelog and release notes for every version
    type:
    - Release notes
    url: https://github.com/ConesaLab/SQANTI3/releases
  - note: Citation instructions are on the end of the Github repository's main page
    type:
    - Citation instructions
    url: https://github.com/ConesaLab/SQANTI3?tab=readme-ov-file#how-to-cite-sqanti3
  - note: Benchmarking about the resources needed to run sqanti3 with multiple cores
    type:
    - Other
    url: https://github.com/ConesaLab/SQANTI3/wiki/SQANTI3-memory-requeriments-and-paralellization
  download:
  - note: null
    type: Downloads page
    url: https://github.com/ConesaLab/SQANTI3/releases
    version: null
  - note: Version 5.5 download link from github
    type: Binaries
    url: https://github.com/ConesaLab/SQANTI3/releases/download/v5.5/SQANTI3_v5.5.zip
    version: '5.5'
  editPermission:
    authors:
    - Fabian-RY
    type: group
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  homepage: https://github.com/ConesaLab/SQANTI3
  homepage_status: 0
  language:
  - Python
  lastUpdate: '2025-07-07T09:35:33.280160Z'
  license: GPL-3.0
  link:
  - note: Github repository for source code access and download
    type:
    - Repository
    url: https://github.com/ConesaLab/SQANTI3
  maturity: Mature
  name: SQANTI3
  operatingSystem:
  - Linux
  otherID: []
  owner: Fabian-RY
  publication:
  - doi: 10.1038/s41592-024-02229-2
    metadata:
      abstract: SQANTI3 offers a flexible tool for quality control, curation and annotation
        of long-read RNA sequencing data. SQANTI3 is a tool designed for the quality
        control, curation and annotation of long-read transcript models obtained with
        third-generation sequencing technologies. Leveraging its annotation framework,
        SQANTI3 calculates quality descriptors of transcript models, junctions and
        transcript ends. With this information, potential artifacts can be identified
        and replaced with reliable sequences. Furthermore, the integrated functional
        annotation feature enables subsequent functional iso-transcriptomics analyses.
      authors:
      - name: Pardo-Palacios F.J.
      - name: Arzalluz-Luque A.
      - name: Kondratova L.
      - name: Salguero P.
      - name: Mestre-Tomas J.
      - name: Amorin R.
      - name: Estevan-Morio E.
      - name: Liu T.
      - name: Nanni A.
      - name: McIntyre L.
      - name: Tseng E.
      - name: Conesa A.
      citationCount: 41
      date: '2024-05-01T00:00:00Z'
      journal: Nature Methods
      title: 'SQANTI3: curation of long-read transcriptomes for accurate identification
        of known and novel isoforms'
    note: Publication of SQANTI3
    pmcid: null
    pmid: null
    type:
    - Primary
    version: '5.1'
  - doi: 10.1101/gr.222976.117
    metadata:
      abstract: High-throughput sequencing of full-length transcripts using long reads
        has paved the way for the discovery of thousands of novel transcripts, even
        in well-annotated mammalian species. The advances in sequencing technology
        have created a need for studies and tools that can characterize these novel
        variants. Here, we present SQANTI, an automated pipeline for the classification
        of long-read transcripts that can assess the quality of data and the preprocessing
        pipeline using 47 unique descriptors. We apply SQANTI to a neuronal mouse
        transcriptome using Pacific Biosciences (PacBio) long reads and illustrate
        how the tool is effective in characterizing and describing the composition
        of the full-length transcriptome. We perform extensive evaluation of ToFU
        PacBio transcripts by PCR to reveal that an important number of the novel
        transcripts are technical artifacts of the sequencing approach and that SQANTI
        quality descriptors can be used to engineer a filtering strategy to remove
        them. Most novel transcripts in this curated transcriptome are novel combinations
        of existing splice sites, resulting more frequently in novel ORFs than novel
        UTRs, and are enriched in both general metabolic and neural-specific functions.
        We show that these new transcripts have a major impact in the correct quantification
        of transcript levels by state-of-the-art short-read-based quantification algorithms.
        By comparing our iso-transcriptome with public proteomics databases, we find
        that alternative isoforms are elusive to proteogenomics detection. SQANTI
        allows the user to maximize the analytical outcome of long-read technologies
        by providing the tools to deliver quality-evaluated and curated full-length
        transcriptomes.
      authors:
      - name: Tardaguila M.
      - name: De La Fuente L.
      - name: Marti C.
      - name: Pereira C.
      - name: Pardo-Palacios F.J.
      - name: Del Risco H.
      - name: Ferrell M.
      - name: Mellado M.
      - name: Macchietto M.
      - name: Verheggen K.
      - name: Edelmann M.
      - name: Ezkurdia I.
      - name: Vazquez J.
      - name: Tress M.
      - name: Mortazavi A.
      - name: Martens L.
      - name: Rodriguez-Navarro S.
      - name: Moreno-Manzano V.
      - name: Conesa A.
      citationCount: 256
      date: '2018-03-01T00:00:00Z'
      journal: Genome Research
      title: 'SQANTI: Extensive characterization of long-read transcript sequences
        for quality control in full-length transcriptome identification and quantification'
    note: Original SQANTI publication
    pmcid: null
    pmid: null
    type:
    - Method
    version: null
  relation: []
  toolType:
  - Command-line tool
  topic:
  - term: Bioinformatics
    uri: http://edamontology.org/topic_0091
  - term: Gene transcripts
    uri: http://edamontology.org/topic_3512
  validated: 0
  version:
  - '5.5'
- accessibility: Open access
  additionDate: '2016-07-12T10:54:05Z'
  biotoolsCURIE: biotools:pia
  biotoolsID: pia
  collectionID:
  - KNIME
  - de.NBI
  - Proteomics
  - BioInfra.Prot
  - CUBiMed.RUB
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: julian.uszkoreit@rub.de
    fundrefid: null
    gridid: null
    name: Julian Uszkoreit
    note: null
    orcidid: http://orcid.org/0000-0001-7522-4007
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    - Developer
    - Maintainer
    url: null
  - email: cubimed@rub.de
    fundrefid: null
    gridid: null
    name: CUBiMed.RUB
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
    - Provider
    url: null
  description: The main focus lays on the integrated inference algorithms, concluding
    the proteins from a set of identified spectra. But it also allows you to integrate
    results of various search engines, inspect your peptide spectrum matches, calculate
    FDR values across different results and visualize the correspondence between PSMs,
    peptides and proteins.
  documentation:
  - note: null
    type:
    - General
    url: https://github.com/medbioinf/pia/wiki
  download:
  - note: null
    type: Source code
    url: https://github.com/mpc-bioinformatics/pia
    version: null
  - note: null
    type: Software package
    url: http://bioconda.github.io/recipes/pia/README.html
    version: null
  - note: null
    type: Binaries
    url: https://github.com/mpc-bioinformatics/pia/releases
    version: null
  - note: null
    type: Container file
    url: https://hub.docker.com/r/julianusz/pia
    version: null
  editPermission:
    authors: []
    type: private
  elixirCommunity:
  - Proteomics
  elixirNode:
  - Germany
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Mass spectrometry spectra
        uri: http://edamontology.org/data_0943
      format:
      - term: Mascot .dat file
        uri: http://edamontology.org/format_3713
      - term: mzIdentML
        uri: http://edamontology.org/format_3247
      - term: TSV
        uri: http://edamontology.org/format_3475
      - term: PRIDE XML
        uri: http://edamontology.org/format_3684
      - term: X!Tandem XML
        uri: http://edamontology.org/format_3711
      - term: MSF
        uri: http://edamontology.org/format_3702
      - term: mzTab
        uri: http://edamontology.org/format_3681
    note: PIA allows you to inspect the results of common proteomics spectrum identification
      search engines, combine them seamlessly and conduct statistical analyses. The
      main focus of PIA lays on the integrated inference algorithms, i.e. concluding
      the proteins from a set of identified spectra. But it also allows you to inspect
      your peptide spectrum matches, calculate FDR values across different search
      engine results and visualize the correspondence between PSMs, peptides and proteins.
      Search engine results in several formats peptide spectrum matches (PSMs) and
      peptides Inferred Proteins
    operation:
    - term: Protein identification
      uri: http://edamontology.org/operation_3767
    - term: Target-Decoy
      uri: http://edamontology.org/operation_3649
    output:
    - data:
        term: Peptide identification
        uri: http://edamontology.org/data_0945
      format:
      - term: Sequence feature table format (text)
        uri: http://edamontology.org/format_2206
      - term: KNIME datatable format
        uri: http://edamontology.org/format_3765
      - term: idXML
        uri: http://edamontology.org/format_3764
      - term: TSV
        uri: http://edamontology.org/format_3475
      - term: mzTab
        uri: http://edamontology.org/format_3681
      - term: mzIdentML
        uri: http://edamontology.org/format_3247
    - data:
        term: Protein identifier
        uri: http://edamontology.org/data_0989
      format:
      - term: Sequence feature table format (text)
        uri: http://edamontology.org/format_2206
      - term: KNIME datatable format
        uri: http://edamontology.org/format_3765
      - term: idXML
        uri: http://edamontology.org/format_3764
      - term: TSV
        uri: http://edamontology.org/format_3475
      - term: mzTab
        uri: http://edamontology.org/format_3681
      - term: mzIdentML
        uri: http://edamontology.org/format_3247
  homepage: https://github.com/medbioinf/pia
  homepage_status: 0
  language:
  - Java
  lastUpdate: '2025-05-02T13:15:26.717477Z'
  license: BSD-3-Clause
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/medbioinf/pia
  maturity: Mature
  name: PIA - Protein Inference Algorithms
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: julianu
  publication:
  - doi: 10.1021/acs.jproteome.5b00121
    metadata:
      abstract: Protein inference connects the peptide spectrum matches (PSMs) obtained
        from database search engines back to proteins, which are typically at the
        heart of most proteomics studies. Different search engines yield different
        PSMs and thus different protein lists. Analysis of results from one or multiple
        search engines is often hampered by different data exchange formats and lack
        of convenient and intuitive user interfaces. We present PIA, a flexible software
        suite for combining PSMs from different search engine runs and turning these
        into consistent results. PIA can be integrated into proteomics data analysis
        workflows in several ways. A user-friendly graphical user interface can be
        run either locally or (e.g., for larger core facilities) from a central server.
        For automated data processing, stand-alone tools are available. PIA implements
        several established protein inference algorithms and can combine results from
        different search engines seamlessly. On several benchmark data sets, we show
        that PIA can identify a larger number of proteins at the same protein FDR
        when compared to that using inference based on a single search engine. PIA
        supports the majority of established search engines and data in the mzIdentML
        standard format. It is implemented in Java and freely available at https://github.com/mpc-bioinformatics/pia.
      authors:
      - name: Uszkoreit J.
      - name: Maerkens A.
      - name: Perez-Riverol Y.
      - name: Meyer H.E.
      - name: Marcus K.
      - name: Stephan C.
      - name: Kohlbacher O.
      - name: Eisenacher M.
      citationCount: 57
      date: '2015-07-02T00:00:00Z'
      journal: Journal of Proteome Research
      title: 'PIA: An Intuitive Protein Inference Engine with a Web-Based User Interface'
    note: null
    pmcid: null
    pmid: '25938255'
    type:
    - Primary
    version: null
  - doi: 10.1021/acs.jproteome.8b00723
    metadata:
      abstract: Proteomics using LC-MS/MS has become one of the main methods to analyze
        the proteins in biological samples in high-throughput. But the existing mass-spectrometry
        instruments are still limited with respect to resolution and measurable mass
        ranges, which is one of the main reasons why shotgun proteomics is the major
        approach. Here proteins are digested, which leads to the identification and
        quantification of peptides instead. While often neglected, the important step
        of protein inference needs to be conducted to infer from the identified peptides
        to the actual proteins in the original sample. In this work, we highlight
        some of the previously published and newly added features of the tool PIA
        - Protein Inference Algorithms, which helps the user with the protein inference
        of measured samples. We also highlight the importance of the usage of PSI
        standard file formats, as PIA is the only current software supporting all
        available standards used for spectrum identification and protein inference.
        Additionally, we briefly describe the benefits of working with workflow environments
        for proteomics analyses and show the new features of the PIA nodes for the
        KNIME Analytics Platform. Finally, we benchmark PIA against a recently published
        data set for isoform detection. PIA is open source and available for download
        on GitHub (https://github.com/mpc-bioinformatics/pia) or directly via the
        community extensions inside the KNIME analytics platform.
      authors:
      - name: Uszkoreit J.
      - name: Perez-Riverol Y.
      - name: Eggers B.
      - name: Marcus K.
      - name: Eisenacher M.
      citationCount: 30
      date: '2019-02-01T00:00:00Z'
      journal: Journal of Proteome Research
      title: Protein Inference Using PIA Workflows and PSI Standard File Formats
    note: null
    pmcid: null
    pmid: '30474983'
    type: []
    version: null
  relation:
  - biotoolsID: knime
    type: uses
  toolType:
  - Command-line tool
  - Library
  - Desktop application
  - Workflow
  topic:
  - term: Proteomics
    uri: http://edamontology.org/topic_0121
  - term: Proteomics experiment
    uri: http://edamontology.org/topic_3520
  - term: Protein variants
    uri: http://edamontology.org/topic_3120
  validated: 1
  version:
  - '1.5'
- accessibility: null
  additionDate: '2016-01-19T16:39:56Z'
  biotoolsCURIE: biotools:openms
  biotoolsID: openms
  collectionID:
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  - de.NBI
  - Proteomics
  - OpenMS
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: null
    fundrefid: null
    gridid: null
    name: ETH Zürich
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
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    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Eberhard-Karls-Universität Tübingen
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
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    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Freie Universität Berlin
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
    - Provider
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Center for Integrative Bioinformatics (CiBi)
    note: null
    orcidid: null
    rorid: null
    typeEntity: Consortium
    typeRole: []
    url: null
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    fundrefid: null
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    note: null
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    rorid: null
    typeEntity: Institute
    typeRole:
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    url: null
  - email: open-ms-general@lists.sourceforge.net
    fundrefid: null
    gridid: null
    name: General Mailinglist
    note: null
    orcidid: null
    rorid: null
    typeEntity: null
    typeRole:
    - Support
    url: null
  - email: open-ms-general@lists.sourceforge.net
    fundrefid: null
    gridid: null
    name: General Mailinglist
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Hannes Röst
    note: null
    orcidid: http://orcid.org/0000-0003-0990-7488
    rorid: null
    typeEntity: Person
    typeRole:
    - Contributor
    url: null
  description: Open source library and a collection of tools and interfaces for the
    analysis of mass spectrometry data. Includes over 200 standalone (TOPP) tools
    that can be combined to a workflow with the integrated workflow editor TOPPAS.
    Raw and intermediate mass spectrometry data can be visualised with the included
    viewer TOPPView.
  documentation:
  - note: null
    type:
    - General
    url: http://ftp.mi.fu-berlin.de/pub/OpenMS/release-documentation/html/index.html
  download:
  - note: null
    type: Source code
    url: https://github.com/OpenMS/OpenMS
    version: null
  - note: null
    type: Binaries
    url: http://sourceforge.net/projects/open-ms/files/OpenMS/OpenMS-2.0/
    version: null
  - note: null
    type: Source code
    url: https://github.com/OpenMS/OpenMS
    version: null
  editPermission:
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    - proteomics.bio.tools
    type: group
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Mass spectrometry data
        uri: http://edamontology.org/data_2536
      format:
      - term: pepXML
        uri: http://edamontology.org/format_3655
      - term: mzQuantML
        uri: http://edamontology.org/format_3248
      - term: dta
        uri: http://edamontology.org/format_3652
      - term: FASTA
        uri: http://edamontology.org/format_1929
      - term: protXML
        uri: http://edamontology.org/format_3747
      - term: idXML
        uri: http://edamontology.org/format_3764
      - term: OBO
        uri: http://edamontology.org/format_2549
      - term: XML
        uri: http://edamontology.org/format_2332
      - term: TraML
        uri: http://edamontology.org/format_3246
      - term: mzML
        uri: http://edamontology.org/format_3244
      - term: mzIdentML
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      - term: qcML
        uri: http://edamontology.org/format_3683
    - data:
        term: Peptide identification
        uri: http://edamontology.org/data_0945
      format:
      - term: pepXML
        uri: http://edamontology.org/format_3655
      - term: mzQuantML
        uri: http://edamontology.org/format_3248
      - term: dta
        uri: http://edamontology.org/format_3652
      - term: FASTA
        uri: http://edamontology.org/format_1929
      - term: protXML
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      - term: idXML
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      - term: OBO
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      - term: XML
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      - term: TraML
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      - term: mzML
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      - term: mzIdentML
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      - term: mzXML
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      - term: MGF
        uri: http://edamontology.org/format_3651
      - term: qcML
        uri: http://edamontology.org/format_3683
    note: null
    operation:
    - term: Protein identification
      uri: http://edamontology.org/operation_3767
    - term: Parsing
      uri: http://edamontology.org/operation_1812
    - term: Data handling
      uri: http://edamontology.org/operation_2409
    - term: Chromatographic alignment
      uri: http://edamontology.org/operation_3628
    - term: Mass spectra calibration
      uri: http://edamontology.org/operation_3627
    - term: Formatting
      uri: http://edamontology.org/operation_0335
    - term: Protein quantification
      uri: http://edamontology.org/operation_3630
    - term: Retention time prediction
      uri: http://edamontology.org/operation_3633
    - term: Annotation
      uri: http://edamontology.org/operation_0226
    - term: Protein feature detection
      uri: http://edamontology.org/operation_3092
    - term: Isotope-coded protein label
      uri: http://edamontology.org/operation_3705
    - term: Label-free quantification
      uri: http://edamontology.org/operation_3634
    - term: iTRAQ
      uri: http://edamontology.org/operation_3639
    - term: Peptide identification
      uri: http://edamontology.org/operation_3631
    - term: Peak detection
      uri: http://edamontology.org/operation_3215
    - term: Mass spectrum visualisation
      uri: http://edamontology.org/operation_3694
    - term: Labeled quantification
      uri: http://edamontology.org/operation_3635
    - term: Splitting
      uri: http://edamontology.org/operation_3359
    - term: Spectral analysis
      uri: http://edamontology.org/operation_3214
    - term: Deisotoping
      uri: http://edamontology.org/operation_3629
    - term: Target-Decoy
      uri: http://edamontology.org/operation_3649
    - term: Prediction and recognition (protein)
      uri: http://edamontology.org/operation_3023
    - term: Comparison
      uri: http://edamontology.org/operation_2424
    - term: Standardisation and normalisation
      uri: http://edamontology.org/operation_3435
    output:
    - data:
        term: Peptide identification
        uri: http://edamontology.org/data_0945
      format:
      - term: pepXML
        uri: http://edamontology.org/format_3655
      - term: mzQuantML
        uri: http://edamontology.org/format_3248
      - term: dta
        uri: http://edamontology.org/format_3652
      - term: FASTA
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      - term: idXML
        uri: http://edamontology.org/format_3764
      - term: mzXML
        uri: http://edamontology.org/format_3654
      - term: TraML
        uri: http://edamontology.org/format_3246
      - term: mzML
        uri: http://edamontology.org/format_3244
      - term: mzIdentML
        uri: http://edamontology.org/format_3247
      - term: MGF
        uri: http://edamontology.org/format_3651
      - term: qcML
        uri: http://edamontology.org/format_3683
    - data:
        term: Expression data
        uri: http://edamontology.org/data_2603
      format:
      - term: pepXML
        uri: http://edamontology.org/format_3655
      - term: mzQuantML
        uri: http://edamontology.org/format_3248
      - term: dta
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      - term: FASTA
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      - term: idXML
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      - term: mzXML
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      - term: TraML
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        uri: http://edamontology.org/format_3244
      - term: mzIdentML
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      - term: MGF
        uri: http://edamontology.org/format_3651
      - term: qcML
        uri: http://edamontology.org/format_3683
  homepage: http://www.openms.de
  homepage_status: 0
  language:
  - C++
  lastUpdate: '2025-04-30T11:39:30.251890Z'
  license: BSD-3-Clause
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/OpenMS/OpenMS
  maturity: Mature
  name: OpenMS
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: samwein
  publication:
  - doi: 10.1038/nmeth.3959
    metadata:
      abstract: © 2016 Nature America, Inc. All rights reserved.High-resolution mass
        spectrometry (MS) has become an important tool in the life sciences, contributing
        to the diagnosis and understanding of human diseases, elucidating biomolecular
        structural information and characterizing cellular signaling networks. However,
        the rapid growth in the volume and complexity of MS data makes transparent,
        accurate and reproducible analysis difficult. We present OpenMS 2.0 (http://www.openms.de),
        a robust, open-source, cross-platform software specifically designed for the
        flexible and reproducible analysis of high-throughput MS data. The extensible
        OpenMS software implements common mass spectrometric data processing tasks
        through a well-defined application programming interface in C++ and Python
        and through standardized open data formats. OpenMS additionally provides a
        set of 185 tools and ready-made workflows for common mass spectrometric data
        processing tasks, which enable users to perform complex quantitative mass
        spectrometric analyses with ease.
      authors:
      - name: Rost H.L.
      - name: Sachsenberg T.
      - name: Aiche S.
      - name: Bielow C.
      - name: Weisser H.
      - name: Aicheler F.
      - name: Andreotti S.
      - name: Ehrlich H.-C.
      - name: Gutenbrunner P.
      - name: Kenar E.
      - name: Liang X.
      - name: Nahnsen S.
      - name: Nilse L.
      - name: Pfeuffer J.
      - name: Rosenberger G.
      - name: Rurik M.
      - name: Schmitt U.
      - name: Veit J.
      - name: Walzer M.
      - name: Wojnar D.
      - name: Wolski W.E.
      - name: Schilling O.
      - name: Choudhary J.S.
      - name: Malmstrom L.
      - name: Aebersold R.
      - name: Reinert K.
      - name: Kohlbacher O.
      citationCount: 246
      date: '2016-08-30T00:00:00Z'
      journal: Nature Methods
      title: 'OpenMS: A flexible open-source software platform for mass spectrometry
        data analysis'
    note: null
    pmcid: null
    pmid: '27575624'
    type:
    - Primary
    version: null
  - doi: 10.1007/978-1-60761-987-1_23
    metadata:
      abstract: Proteomics experiments based on state-of-the-art mass spectrometry
        produce vast amounts of data, which cannot be analyzed manually. Hence, software
        is needed which is able to analyze the data in an automated fashion. The need
        for robust and reusable software tools triggered the development of libraries
        implementing different algorithms for the various analysis steps. OpenMS is
        such a software library and provides a wealth of data structures and algorithms
        for the analysis of mass spectrometric data. For users unfamiliar with programming,
        TOPP ("The OpenMS Proteomics Pipeline") offers a wide range of already implemented
        tools sharing the same interface and designed for a specific analysis task
        each. TOPP thus makes the sophisticated algorithms of OpenMS accessible to
        nonprogrammers. The individual TOPP tools can be strung together into pipelines
        for analyzing mass spectrometry-based experiments starting from the raw output
        of the mass spectrometer. These analysis pipelines can be constructed using
        a graphical editor. Even complex analytical workflows can thus be analyzed
        with ease.
      authors:
      - name: Bertsch A.
      - name: Gropl C.
      - name: Reinert K.
      - name: Kohlbacher O.
      citationCount: 65
      date: '2011-01-01T00:00:00Z'
      journal: Methods in molecular biology (Clifton, N.J.)
      title: 'OpenMS and TOPP: open source software for LC-MS data analysis.'
    note: null
    pmcid: null
    pmid: null
    type:
    - Other
    version: null
  relation: []
  toolType:
  - Library
  - Workbench
  topic:
  - term: Proteomics experiment
    uri: http://edamontology.org/topic_3520
  - term: Proteomics
    uri: http://edamontology.org/topic_0121
  - term: Metabolomics
    uri: http://edamontology.org/topic_3172
  validated: 1
  version:
  - 2.0.0
- accessibility: null
  additionDate: '2016-04-15T11:52:42Z'
  biotoolsCURIE: biotools:comparems2
  biotoolsID: comparems2
  collectionID:
  - ms-utils
  - Proteomics
  confidence_flag: tool
  cost: Free of charge
  credit:
  - email: null
    fundrefid: null
    gridid: null
    name: lumc.nl
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
    - Support
    url: https://www.lumc.nl
  - email: magnus.palmblad@gmail.com
    fundrefid: null
    gridid: null
    name: Magnus Palmblad
    note: null
    orcidid: http://orcid.org/0000-0002-5865-8994
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    - Primary contact
    - Documentor
    url: https://github.com/magnuspalmblad
  - email: null
    fundrefid: null
    gridid: null
    name: Rob Marissen
    note: null
    orcidid: https://orcid.org/0000-0002-1220-9173
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: https://github.com/524D
  description: compareMS2 is a tool for comparing sets of (tandem) mass spectra for
    clustering samples, molecular phylogenetics, identification of biological species
    or tissues, and quality control. compareMS2 currently consumes Mascot Generic
    Format, or MGF, and produces output in a variety of common image and distance
    matrix formats.
  documentation:
  - note: null
    type:
    - General
    - Command-line options
    url: http://www.ms-utils.org/compareMS2.html
  - note: null
    type:
    - General
    - User manual
    - Command-line options
    - Installation instructions
    url: https://github.com/524D/compareMS2
  download:
  - note: null
    type: Source code
    url: http://www.ms-utils.org/compareMS2.c
    version: '1.0'
  - note: null
    type: Binaries
    url: http://www.ms-utils.org/compareMS2.html
    version: '1.0'
  - note: null
    type: Source code
    url: http://www.ms-utils.org/compareMS2.c
    version: '1.0'
  - note: null
    type: Source code
    url: https://github.com/524D/compareMS2/tree/main/src
    version: '2.0'
  - note: null
    type: Binaries
    url: https://github.com/524D/compareMS2/tree/main
    version: '2.0'
  editPermission:
    authors:
    - proteomics.bio.tools
    type: group
  elixirCommunity:
  - Proteomics
  elixirNode:
  - Netherlands
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Mass spectrometry data
        uri: http://edamontology.org/data_2536
      format:
      - term: MGF
        uri: http://edamontology.org/format_3651
    note: null
    operation:
    - term: Comparison
      uri: http://edamontology.org/operation_2424
    - term: Phylogenetic tree visualisation
      uri: http://edamontology.org/operation_0567
    output:
    - data:
        term: Species tree
        uri: http://edamontology.org/data_3272
      format:
      - term: PNG
        uri: http://edamontology.org/format_3603
      - term: SVG
        uri: http://edamontology.org/format_3604
    - data:
        term: Distance matrix
        uri: http://edamontology.org/data_2855
      format:
      - term: mega
        uri: http://edamontology.org/format_1991
      - term: Nexus format
        uri: http://edamontology.org/format_1912
      - term: newick
        uri: http://edamontology.org/format_1910
  homepage: https://github.com/524D/compareMS2
  homepage_status: 0
  language:
  - C
  - JavaScript
  lastUpdate: '2025-04-16T14:22:04.957317Z'
  license: MIT
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/524D/compareMS2
  - note: null
    type:
    - Software catalogue
    url: https://www.ms-utils.org/compareMS2.html
  - note: null
    type:
    - Software catalogue
    url: https://research-software-directory.org/software/comparems2
  maturity: Mature
  name: compareMS2
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: n.m.palmblad@lumc.nl
  publication:
  - doi: 10.1002/rcm.6162
    metadata:
      abstract: 'Rationale: Molecular phylogenetics is the study of evolution and
        relatedness of organisms or genes. Mass spectrometry is used routinely for
        bacterial identification and has also been used for phylogenetic analysis,
        for instance from bone material. Unfortunately, only a small fraction of the
        acquired tandem mass spectra allow direct interpretation. Methods: We describe
        a new algorithm and software for molecular phylogenetics using pairwise comparisons
        of tandem mass spectra from enzymatically digested proteins. The spectra need
        not be annotated and all acquired data is used in the analysis. To demonstrate
        the method, we analyzed tryptic digests of sera from four great apes and two
        other primates. Results: The distribution of spectra dot products for thousands
        of tandem mass spectra collected from two samples provides a measure on the
        fraction of shared peptides between the two samples. When inverted, this becomes
        a distance metric. By pairwise comparison between species and averaging over
        four individuals per species, it was possible to reconstruct the unique correct
        phylogenetic tree for the great apes and other primates. Conclusions: The
        new method described here has several attractive features compared with existing
        methods, among them simplicity, the unbiased use of all acquired data rather
        than a small subset of spectra, and the potential use of heavily degraded
        proteins or proteins with a priori unknown modifications. © 2012 John Wiley
        & Sons, Ltd.'
      authors:
      - name: Palmblad M.
      - name: Deelder A.M.
      citationCount: 30
      date: '2012-04-15T00:00:00Z'
      journal: Rapid Communications in Mass Spectrometry
      title: Molecular phylogenetics by direct comparison of tandem mass spectra
    note: null
    pmcid: null
    pmid: '22368051'
    type:
    - Primary
    version: '1.0'
  - doi: 10.1021/acs.jproteome.2c00457
    metadata:
      abstract: It has long been known that biological species can be identified from
        mass spectrometry data alone. Ten years ago, we described a method and software
        tool, compareMS2, for calculating a distance between sets of tandem mass spectra,
        as routinely collected in proteomics. This method has seen use in species
        identification and mixture characterization in food and feed products, as
        well as other applications. Here, we present the first major update of this
        software, including a new metric, a graphical user interface and additional
        functionality. The data have been deposited to ProteomeXchange with dataset
        identifier PXD034932.
      authors:
      - name: Marissen R.
      - name: Varunjikar M.S.
      - name: Laros J.F.J.
      - name: Rasinger J.D.
      - name: Neely B.A.
      - name: Palmblad M.
      citationCount: 7
      date: '2023-02-03T00:00:00Z'
      journal: Journal of Proteome Research
      title: 'compareMS2 2.0: An Improved Software for Comparing Tandem Mass Spectrometry
        Datasets'
    note: null
    pmcid: PMC9903320
    pmid: '36173614'
    type:
    - Primary
    version: '2.0'
  - doi: 10.1021/acs.jproteome.1c00528
    metadata:
      abstract: Science is full of overlooked and undervalued research waiting to
        be rediscovered. Proteomics is no exception. In this perspective, we follow
        the ripples from a 1960 study of Zuckerkandl, Jones, and Pauling comparing
        tryptic peptides across animal species. This pioneering work directly led
        to the molecular clock hypothesis and the ensuing explosion in molecular phylogenetics.
        In the decades following, proteins continued to provide essential clues on
        evolutionary history. While technology has continued to improve, contemporary
        proteomics has strayed from this larger biological context, rarely comparing
        species or asking how protein structure, function, and interactions have evolved.
        Here we recombine proteomics with molecular phylogenetics, highlighting the
        value of framing proteomic results in a larger biological context and how
        almost forgotten research, though technologically surpassed, can still generate
        new ideas and illuminate our work from a different perspective. Though it
        is infeasible to read all research published on a large topic, looking up
        older papers can be surprisingly rewarding when rediscovering a "gem"at the
        end of a long citation chain, aided by digital collections and perpetually
        helpful librarians. Proper literature study reduces unnecessary repetition
        and allows research to be more insightful and impactful by truly standing
        on the shoulders of giants. All data was uploaded to MassIVE (https://massive.ucsd.edu/)
        as dataset MSV000087993.
      authors:
      - name: Neely B.A.
      - name: Palmblad M.
      citationCount: 1
      date: '2021-10-01T00:00:00Z'
      journal: Journal of Proteome Research
      title: 'Rewinding the Molecular Clock: Looking at Pioneering Molecular Phylogenetics
        Experiments in the Light of Proteomics'
    note: null
    pmcid: PMC8491155
    pmid: '34523928'
    type:
    - Review
    version: '2.0'
  relation: []
  toolType:
  - Command-line tool
  - Desktop application
  topic:
  - term: Phylogeny
    uri: http://edamontology.org/topic_0084
  - term: Proteomics
    uri: http://edamontology.org/topic_0121
  - term: Metabolomics
    uri: http://edamontology.org/topic_3172
  - term: Proteomics experiment
    uri: http://edamontology.org/topic_3520
  validated: 1
  version:
  - '1.0'
  - '2.0'
- accessibility: null
  additionDate: '2024-12-04T05:41:38.413068Z'
  biotoolsCURIE: biotools:biodepot_launcher
  biotoolsID: biodepot_launcher
  collectionID: []
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: lhhung@uw.edu
    fundrefid: null
    gridid: null
    name: Ling-Hong Hung
    note: null
    orcidid: https://orcid.org/0000-0002-5209-2248
    rorid: null
    typeEntity: null
    typeRole:
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    url: null
  - email: tjdahl@uw.edu
    fundrefid: null
    gridid: null
    name: Thomas Dahlstrom
    note: null
    orcidid: https://orcid.org/0000-0003-4363-0697
    rorid: null
    typeEntity: null
    typeRole:
    - Developer
    url: null
  - email: johnnyas@uw.edu
    fundrefid: null
    gridid: null
    name: Johnalbert Garnica
    note: null
    orcidid: https://orcid.org/0009-0004-6419-1560
    rorid: null
    typeEntity: null
    typeRole:
    - Developer
    url: null
  - email: kayee@uw.edu
    fundrefid: null
    gridid: null
    name: Ka Yee Yeung
    note: null
    orcidid: https://orcid.org/0000-0002-1754-7577
    rorid: null
    typeEntity: null
    typeRole:
    - Primary contact
    url: null
  description: The Biodepot Launcher is a desktop application that facilitates installation,
    management and deployment of containerized bioinformatics workflows. This application
    provides an interactive and easy-to-use interface to launch containerized analytical
    workflows that can be used to process biomedical data.
  documentation:
  - note: null
    type:
    - Installation instructions
    url: https://github.com/BioDepot/biodepot-launcher
  - note: null
    type:
    - Training material
    url: https://biodepot.github.io/training/running_bwb/bwb_launcher/
  download:
  - note: null
    type: Binaries
    url: https://github.com/BioDepot/biodepot-launcher
    version: null
  editPermission:
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  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Data analysis
      uri: http://edamontology.org/operation_2945
    output: []
  homepage: https://github.com/BioDepot/biodepot-launcher
  homepage_status: 0
  language:
  - JavaScript
  - Other
  lastUpdate: '2024-12-04T05:42:17.969436Z'
  license: MIT
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/BioDepot/biodepot-launcher
  - note: Training portal with screenshots and demo videos
    type:
    - Other
    url: https://biodepot.github.io/training/running_bwb/bwb_launcher/
  maturity: null
  name: Biodepot Launcher
  operatingSystem:
  - Linux
  - Mac
  - Windows
  otherID: []
  owner: kayee
  publication: []
  relation: []
  toolType:
  - Desktop application
  topic:
  - term: Bioinformatics
    uri: http://edamontology.org/topic_0091
  validated: 0
  version: []
- accessibility: null
  additionDate: '2015-09-11T21:52:42Z'
  biotoolsCURIE: biotools:cmd
  biotoolsID: cmd
  collectionID:
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  confidence_flag: null
  cost: null
  credit:
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    fundrefid: null
    gridid: null
    name: Leiden University Medical Center
    note: null
    orcidid: null
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    typeRole:
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    url: null
  - email: null
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    note: null
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    typeEntity: Project
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    url: null
  - email: null
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    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
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  description: Database of osteogenesis imperfecta and type III collagen variants.
  documentation:
  - note: null
    type:
    - General
    url: https://eds.gene.le.ac.uk/docs/index.php
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  description: Display multiple-sequence alignment. The tool is also available as
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  description: Simplifying the generation of insight from protein structures through
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    input:
    - data:
        term: Sequence identifier
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      format:
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        uri: http://edamontology.org/format_2330
    - data:
        term: Organism identifier
        uri: http://edamontology.org/data_1869
      format:
      - term: Textual format
        uri: http://edamontology.org/format_2330
    note: You can find sequences based on a keyword search. For the identified sequence,
      Aquaria retrieves sequence-to-structure alignments from the PSSH2 database and
      visualises those on the web page. At the same time, a selected alignment is
      visualised in the 3D viewer (by default the one with most identical residues
      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
    operation:
    - term: Structure visualisation
      uri: http://edamontology.org/operation_0570
    - term: Structure database search
      uri: http://edamontology.org/operation_0339
    - term: Sequence visualisation
      uri: http://edamontology.org/operation_0564
    - term: Sequence database search
      uri: http://edamontology.org/operation_0338
    output: []
  - cmd: null
    input:
    - data:
        term: Sequence accession (protein)
        uri: http://edamontology.org/data_1096
      format:
      - term: UniProtKB format
        uri: http://edamontology.org/format_1963
    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:
      aquaria.ws/<UniprotAcc>.json json representation of one or more sequence-to-structure
      alignments annotated with alignment statistics'
    operation:
    - term: Protein structure prediction
      uri: http://edamontology.org/operation_0474
    output:
    - data:
        term: Sequence-structure alignment
        uri: http://edamontology.org/data_0893
      format:
      - term: JSON
        uri: http://edamontology.org/format_3464
  homepage: http://aquaria.ws
  homepage_status: 0
  language:
  - JavaScript
  - Java
  lastUpdate: '2024-11-25T15:45:50.420021Z'
  license: GPL-2.0
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/ODonoghueLab/Aquaria
  maturity: Mature
  name: Aquaria
  operatingSystem:
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  - Windows
  - Mac
  otherID: []
  owner: RostLab
  publication:
  - doi: 10.1038/nmeth.3258
    metadata: null
    note: null
    pmcid: null
    pmid: '25633501'
    type:
    - Primary
    version: null
  relation: []
  toolType:
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  - Web application
  topic:
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    uri: http://edamontology.org/topic_0082
  - term: Protein sites, features and motifs
    uri: http://edamontology.org/topic_3510
  - term: Protein structure analysis
    uri: http://edamontology.org/topic_2814
  validated: 1
  version:
  - '1'
- accessibility: null
  additionDate: '2015-10-01T21:33:09Z'
  biotoolsCURIE: biotools:loctree3
  biotoolsID: loctree3
  collectionID:
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  confidence_flag: null
  cost: Free of charge
  credit:
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    fundrefid: null
    gridid: null
    name: Maximilian Hecht
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
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    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Guy Yachdav
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
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    url: null
  - email: null
    fundrefid: null
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    name: Timothy Karl
    note: null
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    url: null
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    name: Tatyana Goldberg
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    typeEntity: Person
    typeRole:
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    url: null
  - email: null
    fundrefid: null
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    name: Burkhard Rost
    note: null
    orcidid: null
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    typeRole:
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    url: null
  - email: null
    fundrefid: null
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    name: Henrik Nielsen
    note: null
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    rorid: null
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    typeRole:
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    url: null
  - email: null
    fundrefid: null
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    name: Technische Universität München
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    typeEntity: Institute
    typeRole:
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    url: null
  - email: null
    fundrefid: null
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    name: Alexander von Humboldt Foundation through German Federal Ministry for Education
      and Research
    note: null
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    rorid: null
    typeEntity: Funding agency
    typeRole:
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    url: null
  - email: null
    fundrefid: null
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    name: Ernst Ludwig Ehrlich Studienwerk
    note: null
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    typeEntity: Funding agency
    typeRole:
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    url: null
  - email: null
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    name: RostLab
    note: null
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    typeRole:
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    url: null
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    fundrefid: null
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    url: https://rostlab.org/services/loctree3/
  description: Prediction of protein subcellular localization in 18 classes for eukaryota,
    6 for bacteria and 3 for archaea.
  documentation:
  - note: null
    type:
    - General
    url: https://rostlab.org/owiki/index.php/Loctree3
  download:
  - note: null
    type: Source code
    url: https://rostlab.org/owiki/index.php/Packages
    version: null
  - note: null
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    version: null
  editPermission:
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  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Protein sequence record
        uri: http://edamontology.org/data_2886
      format:
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        uri: http://edamontology.org/format_1929
    note: 'Prediction of protein sucellular localization in 18 classes for eukaryota,
      6 classes for bacteria and 3 for archaea using homology searches (PSI-BLAST)
      and machine learning (SVM) User can provide one or more sequences in FASTA format
      The prediction output contains: prediction score, from 1 (weak prediction) to
      100 (strong prediction); one of 18 localization classes for eukaryota, 6 for
      bacteria and 3 for archaea; GO identifier; GO term; prediction source (PSI-BLAST
      or SVM)'
    operation:
    - term: Protein subcellular localisation prediction
      uri: http://edamontology.org/operation_2489
    output:
    - data:
        term: Protein report
        uri: http://edamontology.org/data_0896
      format:
      - term: TSV
        uri: http://edamontology.org/format_3475
  homepage: https://rostlab.org/services/loctree3/
  homepage_status: 0
  language:
  - PHP
  - Java
  - Perl
  - JavaScript
  lastUpdate: '2024-11-25T15:45:41.322065Z'
  license: GPL-3.0
  link:
  - note: null
    type:
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    url: https://rostlab.org/owiki/index.php/Packages
  maturity: Mature
  name: LocTree3
  operatingSystem:
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  otherID: []
  owner: RostLab
  publication:
  - doi: 10.1093/nar/gku396
    metadata: null
    note: null
    pmcid: PMC4086075
    pmid: '24848019'
    type:
    - Primary
    version: null
  - doi: 10.1093/bioinformatics/bts390
    metadata: null
    note: null
    pmcid: PMC3436817
    pmid: '22962467'
    type:
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    version: null
  relation: []
  toolType:
  - Command-line tool
  - Web application
  topic:
  - term: Sequence analysis
    uri: http://edamontology.org/topic_0080
  - term: Protein properties
    uri: http://edamontology.org/topic_0123
  - term: Cell biology
    uri: http://edamontology.org/topic_2229
  validated: 1
  version:
  - 1.0.8
- accessibility: null
  additionDate: '2016-06-07T15:40:09Z'
  biotoolsCURIE: biotools:the_flux_simulator
  biotoolsID: the_flux_simulator
  collectionID: []
  confidence_flag: null
  cost: Free of charge
  credit:
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    gridid: null
    name: Micha Sammeth
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
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    url: null
  - email: null
    fundrefid: null
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    name: Lab Roderic Guigo Group
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
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    url: null
  - email: null
    fundrefid: null
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    note: null
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    rorid: null
    typeEntity: Institute
    typeRole:
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    url: null
  - email: micha@sammeth.net
    fundrefid: null
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    name: Micha Sammeth
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
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    url: null
  description: 'Model RNA-Seq experiments in silico: sequencing reads are produced
    from a reference genome according annotated transcripts.'
  documentation:
  - note: null
    type:
    - General
    url: http://sammeth.net/confluence/display/SIM/Home
  download:
  - note: null
    type: Source code
    url: http://sammeth.net/confluence/display/SIM/2+-+Download
    version: null
  - note: null
    type: Binaries
    url: http://sammeth.net/confluence/display/SIM/2+-+Download
    version: null
  editPermission:
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  function:
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    input:
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      format:
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    - data:
        term: Data
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      format: []
    note: 'The Flux Simulator aims at modeling RNA-Seq experiments in silico: sequencing
      reads are produced from a reference genome according annotated transcripts.
      The simulation pipeline models different steps as modules, each with a minimal
      set of parameters that can be estimated by experimental parameters.  The first
      step is-in fact-a transcriptome simulator. Subsequently, common sources of systematic
      bias in the abundance and distribution of produced reads are simulated by in
      silico library preparation and sequencing. Our models do not simulate molecular
      processes on the level of atoms, but represent a collection of deterministic
      approaches with a minimal set of parameters that can be estimated from observations
      of the experiment that is to be reproduced. Model development has to be understood
      as an iterative process to a maximal convergence of "model world" and "real
      world". It always requires a careful evaluation of all hypotheses and assumptions
      by comparison with experimental data.'
    operation:
    - term: Simulated gene expression data generation
      uri: http://edamontology.org/operation_3566
    output: []
  homepage: http://sammeth.net/confluence/display/SIM/Home
  homepage_status: 0
  language:
  - Java
  lastUpdate: '2024-11-25T15:42:24.196759Z'
  license: BSD-3-Clause
  link:
  - note: null
    type:
    - Repository
    url: http://sammeth.net/bitbucket/projects/BARNA/repos/barna/browse/barna.simulator
  maturity: Mature
  name: The Flux Simulator
  operatingSystem:
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  - Mac
  otherID: []
  owner: francisco.camara@crg.eu
  publication:
  - doi: 10.1093/nar/gks666
    metadata: null
    note: null
    pmcid: PMC3488205
    pmid: '22962361'
    type:
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    version: null
  relation: []
  toolType:
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  topic:
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    uri: http://edamontology.org/topic_0080
  validated: 1
  version:
  - 1.2.1
- accessibility: null
  additionDate: '2016-06-07T13:17:41Z'
  biotoolsCURIE: biotools:astalavista
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  confidence_flag: null
  cost: Free of charge
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    note: null
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    typeEntity: Person
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    url: null
  description: Alternative splicing trascriptional landscape visualization tool retrieves
    all alternative splicing events from generic transcript annotations.
  documentation:
  - note: null
    type:
    - General
    url: http://sammeth.net/confluence/display/ASTA/2+-+Download
  download:
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    type: Source code
    url: http://artifactory.sammeth.net/artifactory/barna/barna/barna.astalavista/3.2/astalavista-3.2.tgz
    version: null
  - note: null
    type: Binaries
    url: http://sammeth.net/confluence/display/ASTA/2+-+Download
    version: null
  editPermission:
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  function:
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    input:
    - data:
        term: Nucleic acid features
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      format: []
    note: The AStalavista web server extracts and displays alternative splicing (AS)
      events from a given genomic annotation of exon-intron gene coordinates. By comparing
      all given transcripts, AStalavista detects the variations in their splicing
      structure and identify all AS events (like exon skipping, alternate donor, etc)
      by assigning to each of them an AS code. AStalavista provides a vizual summary
      of the AS landscape in the analyzed dataset, the possibility to browse the results
      on the UCSC website or to download them in GTF or ASTA format. You can use AStalavista
      for any genome by providing your own annotation set, the identifier of your
      gene(s) of interest, or analyze the AS landscape of reference annotation datasets
      like Gencode, RefSeq, Ensembl, FlyBase,...
    operation:
    - term: Sequence visualisation
      uri: http://edamontology.org/operation_0564
    - term: Sequence annotation
      uri: http://edamontology.org/operation_0361
    output:
    - data:
        term: Sequence features
        uri: http://edamontology.org/data_1255
      format:
      - term: Image format
        uri: http://edamontology.org/format_3547
  homepage: http://sammeth.net/confluence/display/ASTA/Home
  homepage_status: 0
  language:
  - Java
  lastUpdate: '2024-11-25T15:42:23.141551Z'
  license: BSD-3-Clause
  link:
  - note: null
    type:
    - Repository
    url: http://sammeth.net/bitbucket/scm/barna/barna.git
  maturity: null
  name: AStalavista
  operatingSystem:
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  - Windows
  - Mac
  otherID: []
  owner: francisco.camara@crg.eu
  publication:
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    metadata: null
    note: null
    pmcid: PMC3290788
    pmid: '22113879'
    type:
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    version: null
  relation: []
  toolType:
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  topic:
  - term: Nucleic acid structure analysis
    uri: http://edamontology.org/topic_0097
  validated: 1
  version:
  - '3.2'
- accessibility: null
  additionDate: '2016-04-22T14:37:38Z'
  biotoolsCURIE: biotools:selenoprofiles3
  biotoolsID: selenoprofiles3
  collectionID: []
  confidence_flag: null
  cost: Free of charge
  credit:
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    gridid: null
    name: Marco Mariotti
    note: null
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  description: Pipeline for profile-based protein finding in genomes.
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  - note: null
    type:
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    url: http://big.crg.cat/services/selenoprofiles
  download:
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  function:
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    input:
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    note: Provided one or more protein alignments, it scans a target genome (or any
      other nucleotide database) and reports the gene structures of homologous genes.
      It can be used to easily characterize any protein family of interest across
      a massive amount of sequenced genomes, allowing a finely tuned filtering of
      results. Or it can be used with comprehensive sets of input profiles, in order
      to completely annotate by homology one or more genomes.
    operation:
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      uri: http://edamontology.org/operation_0362
    output:
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      format: []
  homepage: http://big.crg.cat/services/selenoprofiles
  homepage_status: 0
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  lastUpdate: '2024-11-25T15:42:22.026077Z'
  license: GPL-3.0
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    type:
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  maturity: Mature
  name: Selenoprofiles3
  operatingSystem: []
  otherID: []
  owner: francisco.camara@crg.eu
  publication:
  - doi: 10.1093/bioinformatics/btq516
    metadata: null
    note: null
    pmcid: PMC2958745
    pmid: '20861026'
    type:
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  relation: []
  toolType:
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  topic:
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  validated: 1
  version:
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- accessibility: null
  additionDate: '2016-03-18T09:58:17Z'
  biotoolsCURIE: biotools:motiflab
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  description: 'General workbench for analyzing regulatory sequence regions and discovering
    transcription factor binding sites and cis-regulatory modules. It can improve
    performance of binding site predictions by allowing users to integrate several
    motif discovery tools, as well as different types of data: phylogenetic conservation,
    epigenetic marks, DNase hypersensitive sites, ChIP-Seq data, positional binding
    preferences of transcription factors, TF-TF interactions, TF-expression and target
    gene expression.'
  documentation:
  - note: null
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    note: Computes Jumping ALIgnments from a protein sequence and an alignment of
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      uri: http://edamontology.org/operation_0292
    output: []
  homepage: http://bibiserv.cebitec.uni-bielefeld.de/jali
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    metadata: null
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    pmid: '12487762'
    type:
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    version: null
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  toolType:
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  topic:
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  version:
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- accessibility: null
  additionDate: '2016-01-20T09:51:59Z'
  biotoolsCURIE: biotools:guugle
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  description: RNA secondary structure analysis often requires searching for potential
    helices in large sequence data. We present a utility program that efficiently
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    note: We present a utility program that efficiently locates potential helical
      regions under RNA base pairing rules, which include Watson-Crick as well as
      G-U pairs.
    operation:
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    - term: Sequence database search
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    output:
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        term: Sequence report
        uri: http://edamontology.org/data_2955
      format: []
  homepage: http://bibiserv.cebitec.uni-bielefeld.de/guugle
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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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  validated: 1
  version:
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- accessibility: null
  additionDate: '2016-01-20T09:50:50Z'
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    rorid: null
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  description: This tool to detect structural variations is specifically designed
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    deletions and insertions. It does not make any assumptions on the composition
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  - note: null
    type:
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  additionDate: '2016-01-20T08:38:24Z'
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  description: With current sequencing technologies, it is feasible to generate a
    lot of reads for a given genome. However, the assembly usually ends up in a set
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  documentation:
  - note: null
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    note: Match a set of contigs to a related reference genome to order and orient
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    operation:
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    note: The program treecat can be used to estimate an ordering for a set of contigs.
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      where necessary. The layout graph is calculated based on the matches to several
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  language:
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  license: GPL-2.0
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  toolType:
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  validated: 1
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  description: Tool for finding the minimum free energy hybridization of a long and
    a short RNA. The hybridization is performed in a kind of domain mode, ie. the
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    is primarily meant as a means for microRNA target prediction.
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  - note: null
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    note: calculates a minimal free energy hybridization of RNA sequence(s) and miRNA(s)
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    output:
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  link:
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  maturity: Mature
  name: RNAhybrid
  operatingSystem:
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  otherID: []
  owner: FARINAZ
  publication:
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    metadata: null
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    pmcid: PMC1370637
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    type:
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  relation: []
  toolType:
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  - Command-line tool
  topic:
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  - term: Sequence sites, features and motifs
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  validated: 1
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- accessibility: null
  additionDate: '2016-01-19T15:00:57Z'
  biotoolsCURIE: biotools:snap2
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  description: Method that predicts the effects of single amino acid substitutions
    in a protein on the protein's function using neural networks.
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  - note: null
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  function:
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    input:
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    note: Prediction of SNP influence on protein function between neutral and effect.
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    operation:
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      uri: http://edamontology.org/operation_0484
    output:
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      format:
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        uri: http://edamontology.org/format_2330
  homepage: https://github.com/Rostlab/SNAP2
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  additionDate: '2016-04-01T10:14:18Z'
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  description: Efficiently assign taxonomic labels to as many reads as possible in
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    note: Using a custom precomputed reference database with a fast searchable index
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    output:
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  description: Set of post-processing tools aimed at improving the taxonomical classification
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    note: Taxonomic classification and species abundance analysis of metagenomic samples
      Metagenomic sample Genome database Taxonomic classification
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      format:
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  lastUpdate: '2024-11-25T15:37:36.362168Z'
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  topic:
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  validated: 1
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next: ?page=2
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