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  additionDate: '2017-12-18T00:03:45Z'
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    typeEntity: Person
    typeRole:
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    url: http://olegtrott.com/
  description: AutoDock Vina is a new open-source program for drug discovery, molecular
    docking and virtual screening, offering multi-core capability, high performance
    and enhanced accuracy and ease of use.
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  - note: null
    type:
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    operation:
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    output: []
  homepage: http://vina.scripps.edu/
  homepage_status: 0
  language:
  - C++
  lastUpdate: '2026-06-04T08:07:30.690513Z'
  license: null
  link:
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    type:
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    pmid: '19499576'
    type:
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    version: null
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  toolType:
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  topic:
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  - term: Molecular modelling
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  - term: Molecular docking
    uri: http://edamontology.org/topic_2275
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    typeEntity: Person
    typeRole:
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  description: Comprehensive set of programs for phylogenetic analyses; available
    for PC and Mac; source code available for easy compiling in UNIX.
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    type:
    - General
    url: http://evolution.genetics.washington.edu/phylip/phylip.html
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    - term: Phylogenetic tree analysis
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    metadata:
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        and epidemiological problems as well as insights about the origins and development
        of physiological features in present day organisms. Consensus phylogenies
        based on the bootstrap and other resampling methods play a crucial part in
        analyzing the robustness of the trees produced for these analyses. Methodology:
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        matrix, and maximum likelihood methods. We have modified the PHYLIP package
        using MPI to enable large-scale phylogenetic study of protein sequences, using
        a statistically robust number of bootstrapped datasets, to be performed in
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        the PHYLIP programs and reports the performance of the parallel PHYLIP programs
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        art desktop workstation are reduced to calculations that can be performed
        over lunchtime on a modern parallel computer. Of the three protein methods
        tested, the maximum likelihood method scales the best, followed by the distance
        method, and then the maximum parsimony method. However, the maximum likelihood
        method requires significant memory resources, which limits its application
        to more moderately sized protein datasets. © 2010 Ropelewski et al.'
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      - name: Nicholas H.B.
      - name: Mendez R.R.G.
      citationCount: 13
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      title: 'MPI-PHYLIP: Parallelizing computationally intensive phylogenetic analysis
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    type: []
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    type: []
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  - term: Model organisms
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  - term: Gene and protein families
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  - term: Physiology
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    url: null
  description: The package implements an algorithm for fast gene set enrichment analysis.
    Using the fast algorithm allows to make more permutations and get more fine grained
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  license: MIT
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  toolType:
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  additionDate: '2017-03-24T10:30:37Z'
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  description: A server that supports several different algorithms for the analysis
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  documentation:
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    metadata:
      abstract: The DICHROWEB web server enables on-line analyse of circular dichroism
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        and graphical analyses comparing calculated structures and experimental data.
        The server is located at http://www.cryst.bbk.ac.uk/cdweb and may be accessed
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        form. The server facilitates analyses using five popular algorithms and (currently)
        seven different reference databases by accepting data in a user-friendly manner
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      citationCount: 2098
      date: '2004-07-01T00:00:00Z'
      journal: Nucleic Acids Research
      title: DICHROWEB, an online server for protein secondary structure analyses
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    note: null
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    type: []
    version: null
  - doi: 10.1093/bioinformatics/18.1.211
    metadata:
      abstract: A user-friendly website for the analysis of protein secondary structures
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      - name: Whitmore L.
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      citationCount: 660
      date: '2002-01-01T00:00:00Z'
      journal: Bioinformatics
      title: 'DICHROWEB: An interactive website for the analysis of protein secondary
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    note: null
    pmcid: null
    pmid: '11836237'
    type: []
    version: null
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  toolType:
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  - term: Structural biology
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  - term: Protein structure analysis
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  - term: Proteins
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  validated: 1
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- accessibility: Open access (with restrictions)
  additionDate: '2026-03-28T10:21:22.720256Z'
  biotoolsCURIE: biotools:bionoculars
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  confidence_flag: tool
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  description: "Life science search engine providing access to 80M+ articles, from\
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  documentation:
  - note: null
    type:
    - Quick start guide
    url: https://www.bionoculars.com/tutorial
  - note: null
    type:
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    output: []
  homepage: https://www.bionoculars.com/
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  name: Bionoculars
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  owner: SyllogistTeam
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  toolType:
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  - term: Medicine
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  - term: Natural language processing
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  - term: Ontology and terminology
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  additionDate: '2018-12-12T12:35:31Z'
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    url: https://biotools.readthedocs.io/en/latest/contributors.html
  description: The community registry of computational tools and data resources for
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  language:
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  - term: Bioinformatics
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  - term: Data curation and archival
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  - term: Computational biology
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- accessibility: null
  additionDate: '2026-02-27T17:39:14.144907Z'
  biotoolsCURIE: biotools:random_number_lab
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  cost: Free of charge
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    fundrefid: null
    gridid: null
    name: Thomas Amthor
    note: null
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    rorid: null
    typeEntity: Person
    typeRole:
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    - Maintainer
    url: null
  description: An interactive set of tools including randomization of data (even stratified
    random sampling) and random assignments for studies, generation of random numbers
    following specific probability distributions, generation of random and quasi-random
    point distributions and sampling patterns, noise in one or two dimensions with
    adjustable spectral properties, random walks and Lévy flights. Own data tables
    can be provided for random sampling in a privacy-friendly way, as data processing
    takes place directly in the browser and no data is transferred to anywhere else.
    The Random Number Lab also offers some educational material and worksheets and
    can be used for scientific and educational purposes.
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  download: []
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    input: []
    note: Generation of sequences of random numbers or elements, spatial point patterns,
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  - cmd: null
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    note: Visualization of random distributions and random processes
    operation:
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    output: []
  - cmd: null
    input: []
    note: Randomization and permutation of data in a privacy-preserving way
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    output: []
  homepage: https://randomnumberlab.org
  homepage_status: 0
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  lastUpdate: '2026-02-27T18:10:10.460700Z'
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  link: []
  maturity: Mature
  name: Random Number Lab
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  - iOS
  - Mac
  - Android
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    value: RRID:SCR_028010
    version: null
  owner: thomas9
  publication: []
  relation: []
  toolType:
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  topic:
  - term: Statistics and probability
    uri: http://edamontology.org/topic_2269
  - term: Experimental design and studies
    uri: http://edamontology.org/topic_3678
  validated: 0
  version: []
- accessibility: null
  additionDate: '2017-03-25T16:29:49Z'
  biotoolsCURIE: biotools:psipred
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    rorid: null
    typeEntity: Person
    typeRole:
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    url: null
  description: The PSIPRED Protein Analysis Workbench unites many available analysis
    tools into a single web based framework. An excellent tool for prediction of secondary
    structure, with access to GenTHREADER for protein fold recognition and MEMSAT-2
    transmembrane topology prediction.
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  - note: null
    type:
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    url: http://bioinf.cs.ucl.ac.uk/index.php?id=779
  download: []
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    metadata:
      abstract: 'The PSIPRED protein structure prediction server allows users to submit
        a protein sequence, perform a prediction of their choice and receive the results
        of the prediction both textually via e-mail and graphically via the web. The
        user may select one of three prediction methods to apply to their sequence:
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        a new version of a widely used transmembrane topology prediction method; or
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        Freely available to non-commercial users at http://globin.bio.warwick.ac.uk/psipred/.'
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      - name: McGuffin L.J.
      - name: Bryson K.
      - name: Jones D.T.
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      date: '2000-01-01T00:00:00Z'
      journal: Bioinformatics
      title: The PSIPRED protein structure prediction server
    note: null
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  - doi: 10.1006/jmbi.1999.3091
    metadata:
      abstract: A two-stage neural network has been used to predict protein secondary
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        found to be superior to those produced by other methods, including the popular
        PHD method according to our own benchmarking results and the results from
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        experiment (CASP3), where the method was evaluated by stringent blind testing.
        Using a new testing set based on a set of 187 unique folds, and three-way
        cross-validation based on structural similarity criteria rather than sequence
        similarity criteria used previously (no similar folds were present in both
        the testing and training sets) the method presented here (PSIPRED) achieved
        an average Q3 score of between 76.5% to 78.3% depending on the precise definition
        of observed secondary structure used, which is the highest published score
        for any method to date. Given the success of the method in CASP3, it is reasonable
        to be confident that the evaluation presented here gives a fair indication
        of the performance of the method in general.
      authors:
      - name: Jones D.T.
      citationCount: 4685
      date: '1999-09-17T00:00:00Z'
      journal: Journal of Molecular Biology
      title: Protein secondary structure prediction based on position-specific scoring
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    note: null
    pmcid: null
    pmid: '10493868'
    type: []
    version: null
  - doi: 10.1093/nar/gkt381
    metadata:
      abstract: Here, we present the new UCL Bioinformatics Group's PSIPRED Protein
        Analysis Workbench. The Workbench unites all of our previously available analysis
        methods into a single web-based framework. The new web portal provides a greatly
        streamlined user interface with a number of new features to allow users to
        better explore their results. We offer a number of additional services to
        enable computationally scalable execution of our prediction methods; these
        include SOAP and XML-RPC web server access and new HADOOP packages. All software
        and services are available via the UCL Bioinformatics Group website at http://bioinf.cs.ucl.ac.uk/.
      authors:
      - name: Buchan D.W.
      - name: Minneci F.
      - name: Nugent T.C.
      - name: Bryson K.
      - name: Jones D.T.
      citationCount: 1109
      date: '2013-01-01T00:00:00Z'
      journal: Nucleic acids research
      title: Scalable web services for the PSIPRED Protein Analysis Workbench.
    note: null
    pmcid: PMC3692098
    pmid: '23748958'
    type: []
    version: null
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      abstract: The SWISS-2DPAGE database was established in 1993 and is maintained
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      - name: Appel R.D.
      citationCount: 98
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    note: null
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    multiple sequence alignments (MSAs). Optionally, paths to existing family HMMs
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  description: Efficient implementations for all the popular synergy scoring models
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      - name: Sakurai N.
      - name: Suzuki H.
      - name: Shibata D.
      - name: Neumann S.
      - name: Iida T.
      - name: Tanaka K.
      - name: Funatsu K.
      - name: Matsuura F.
      - name: Soga T.
      - name: Taguchi R.
      - name: Saito K.
      - name: Nishioka T.
      citationCount: 1747
      date: '2010-01-01T00:00:00Z'
      journal: Journal of Mass Spectrometry
      title: 'MassBank: A public repository for sharing mass spectral data for life
        sciences'
    note: null
    pmcid: null
    pmid: '20623627'
    type:
    - Primary
    version: null
  relation: []
  toolType:
  - Database portal
  topic:
  - term: Metabolomics
    uri: http://edamontology.org/topic_3172
  validated: 1
  version: []
- accessibility: null
  additionDate: '2017-01-17T14:51:18Z'
  biotoolsCURIE: biotools:proteinprospector
  biotoolsID: proteinprospector
  collectionID:
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  - Proteomics
  confidence_flag: tool
  cost: null
  credit:
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    fundrefid: null
    gridid: null
    name: Admin
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Maintainer
    url: null
  - email: webmaster@ms-utils.org
    fundrefid: null
    gridid: null
    name: null
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Documentor
    url: http://ms-utils.org
  description: A suite of protein identification tools.
  documentation:
  - note: null
    type:
    - User manual
    url: http://prospector.ucsf.edu/prospector/html/instruct/allman.htm
  download: []
  editPermission:
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    - n.m.palmblad@lumc.nl
    type: group
  elixirCommunity: []
  elixirNode: []
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  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Protein fragment weight comparison
      uri: http://edamontology.org/operation_2929
    - term: Blind peptide database search
      uri: http://edamontology.org/operation_3647
    output: []
  homepage: http://prospector.ucsf.edu
  homepage_status: 0
  language: []
  lastUpdate: '2025-08-28T15:15:11.245617Z'
  license: null
  link:
  - note: null
    type:
    - Software catalogue
    url: http://ms-utils.org
  maturity: null
  name: ProteinProspector
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID:
  - type: rrid
    value: RRID:SCR_014558
    version: null
  owner: msutils_import
  publication:
  - doi: 10.1074/mcp.d500002-mcp200
    metadata:
      abstract: A thorough analysis of the protein interaction partners of the yeast
        GTPase Gsp1p was carried out by a multidimensional chromatography strategy
        of strong cation exchange fractionation of peptides followed by reverse phase
        LC-ESI-MSMS using a QSTAR instrument. This dataset was then analyzed using
        the latest developmental version of Protein Prospector. The Prospector search
        results were also compared with results from the search engine "Mascot" using
        a new results comparison program within Prospector named "SearchCompare."
        The results from this study demonstrate that the high quality data produced
        on a quadrupole selecting, quadrupole collision cell, time-of-flight (QqTOF)
        geometry instrument allows for confident assignment of the vast majority of
        interpretable spectra by current search engines. © 2005 by The American Society
        for Biochemistry and Molecular Biology, Inc.
      authors:
      - name: Chalkley R.J.
      - name: Baker P.R.
      - name: Huang L.
      - name: Hansen K.C.
      - name: Allen N.P.
      - name: Rexach M.
      - name: Burlingame A.L.
      citationCount: 165
      date: '2005-08-01T00:00:00Z'
      journal: Molecular and Cellular Proteomics
      title: 'Comprehensive analysis of a multidimensional liquid chromatography mass
        spectrometry dataset acquired on a quadrupole selecting, quadrupole collision
        cells, time-of-flight mass spectrometer: II New developments in protein prospector
        allow for reliable and comprehensive automatic analysis of large datasets'
    note: null
    pmcid: null
    pmid: '15937296'
    type:
    - Primary
    version: null
  relation: []
  toolType:
  - Web application
  topic:
  - term: Proteomics
    uri: http://edamontology.org/topic_0121
  - term: Proteomics experiment
    uri: http://edamontology.org/topic_3520
  - term: Database management
    uri: http://edamontology.org/topic_3489
  validated: 1
  version: []
- accessibility: Open access
  additionDate: '2016-09-30T15:59:05Z'
  biotoolsCURIE: biotools:silva
  biotoolsID: silva
  collectionID:
  - de.NBI
  - de.NBI-biodata
  - DSMZ Digital Diversity
  confidence_flag: tool
  cost: Free of charge
  credit:
  - email: hub@dsmz.de
    fundrefid: null
    gridid: grid.420081.f
    name: Leibniz Institute DSMZ-German Collection of Microorganisms and Cell Cultures
    note: null
    orcidid: null
    rorid: 02tyer376
    typeEntity: Institute
    typeRole:
    - Provider
    url: https://www.dsmz.de
  - email: contact@arb-silva.de
    fundrefid: null
    gridid: grid.507782.f
    name: SILVA Team
    note: null
    orcidid: null
    rorid: 027z9pz32
    typeEntity: Division
    typeRole:
    - Primary contact
    url: https://www.arb-silva.de/contact/team/
  description: SILVA provides comprehensive, quality checked and regularly updated
    datasets of aligned small (16S/18S, SSU) and large subunit (23S/28S, LSU) ribosomal
    RNA (rRNA) sequences for all three domains of life (Bacteria, Archaea and Eukaryota).
  documentation:
  - note: null
    type:
    - Terms of use
    url: https://www.arb-silva.de/silva-license-information/
  - note: null
    type:
    - Citation instructions
    url: https://www.arb-silva.de/contact/
  - note: null
    type:
    - General
    url: https://www.arb-silva.de/documentation/
  - note: null
    type:
    - FAQ
    url: https://www.arb-silva.de/documentation/faqs/
  download:
  - note: SILVA dataset archive
    type: Downloads page
    url: https://www.arb-silva.de/download/archive/
    version: null
  editPermission:
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    type: private
  elixirCommunity: []
  elixirNode:
  - Germany
  elixirPlatform:
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  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Sequence accession (nucleic acid)
        uri: http://edamontology.org/data_1097
      format:
      - term: plain text format (unformatted)
        uri: http://edamontology.org/format_1964
    - data:
        term: Taxon
        uri: http://edamontology.org/data_1868
      format:
      - term: plain text format (unformatted)
        uri: http://edamontology.org/format_1964
    - data:
        term: Strain name
        uri: http://edamontology.org/data_1046
      format:
      - term: plain text format (unformatted)
        uri: http://edamontology.org/format_1964
    - data:
        term: Article ID
        uri: http://edamontology.org/data_1088
      format:
      - term: plain text format (unformatted)
        uri: http://edamontology.org/format_1964
    - data:
        term: Organism name
        uri: http://edamontology.org/data_2909
      format:
      - term: plain text format (unformatted)
        uri: http://edamontology.org/format_1964
    note: The search and retrieval functions of the SILVA website can be used to build
      custom subsets of sequences. In addition to simple searches e.g. for accession
      numbers, organism names, taxonomic entities, or publication DOI/PubMed IDs,
      complex queries over several database fields using constraints such as sequence
      length or quality values are possible. The results can be sorted according to
      accession numbers, organism names, sequence length, sequence and alignment quality
      and Pintail values. The search results show accession number, organism name,
      sequence length, sequence quality values, taxonomic classifications, and links
      to view the full sequence record on SILVA and on ENA. Sequences found via search
      and added to download cart can be downloaded as FASTA and ARB files.
    operation:
    - term: Query and retrieval
      uri: http://edamontology.org/operation_0224
    output:
    - data:
        term: Sequence report
        uri: http://edamontology.org/data_2955
      format:
      - term: HTML
        uri: http://edamontology.org/format_2331
    - data:
        term: Sequence alignment (nucleic acid)
        uri: http://edamontology.org/data_1383
      format:
      - term: ARB
        uri: http://edamontology.org/format_3830
      - term: FASTA-aln
        uri: http://edamontology.org/format_1984
    - data:
        term: Nucleic acid sequence
        uri: http://edamontology.org/data_2977
      format:
      - term: ARB
        uri: http://edamontology.org/format_3830
      - term: FASTA-aln
        uri: http://edamontology.org/format_1984
  - cmd: null
    input:
    - data:
        term: Nucleic acid sequence
        uri: http://edamontology.org/data_2977
      format:
      - term: nucleotide
        uri: http://edamontology.org/format_1207
    - data:
        term: PCR primers
        uri: http://edamontology.org/data_1240
      format:
      - term: nucleotide
        uri: http://edamontology.org/format_1207
    note: "The SILVA Probe Match and Evaluation Tool detects and displays all occurrences\
      \ of a given probe or primer sequence in the SILVA datasets. \n\nTestPrime allows\
      \ you to evaluate the performance of primer pairs by running an in silico PCR\
      \ on the SILVA databases. From the results of the PCR, TestPrime computes coverages\
      \ for each taxonomic group in all of the taxonomies offered by SILVA."
    operation:
    - term: Primer and probe design
      uri: http://edamontology.org/operation_2419
    output:
    - data:
        term: Report
        uri: http://edamontology.org/data_2048
      format:
      - term: CSV
        uri: http://edamontology.org/format_3752
      - term: HTML
        uri: http://edamontology.org/format_2331
    - data:
        term: Sequence set
        uri: http://edamontology.org/data_0850
      format:
      - term: Binary format
        uri: http://edamontology.org/format_2333
    - data:
        term: Nucleic acid sequence alignment
        uri: http://edamontology.org/data_1383
      format:
      - term: ARB
        uri: http://edamontology.org/format_3830
      - term: FASTA-aln
        uri: http://edamontology.org/format_1984
    - data:
        term: Nucleic acid sequence
        uri: http://edamontology.org/data_2977
      format:
      - term: ARB
        uri: http://edamontology.org/format_3830
      - term: FASTA-aln
        uri: http://edamontology.org/format_1984
  - cmd: null
    input:
    - data:
        term: Nucleic acid sequence
        uri: http://edamontology.org/data_2977
      format:
      - term: FASTA-aln
        uri: http://edamontology.org/format_1984
    note: The Alignment, Classification and Tree Service (ACT) of SILVA allows to
      align and optionally classify sequences using the SILVA Incremental Aligner
      (SINA). From aligned sequences, (optionally) phylogenetic trees can be inferred
      using FastTree or RAxML.
    operation:
    - term: Multiple sequence alignment
      uri: http://edamontology.org/operation_0492
    - term: Global alignment
      uri: http://edamontology.org/operation_0496
    - term: Taxonomic classification
      uri: http://edamontology.org/operation_3460
    - term: Phylogenetic inference (maximum likelihood and Bayesian methods)
      uri: http://edamontology.org/operation_0547
    output:
    - data:
        term: Nucleic acid sequence alignment
        uri: http://edamontology.org/data_1383
      format:
      - term: ARB
        uri: http://edamontology.org/format_3830
      - term: FASTA-aln
        uri: http://edamontology.org/format_1984
    - data:
        term: Sequence alignment report
        uri: http://edamontology.org/data_0867
      format:
      - term: CSV
        uri: http://edamontology.org/format_3752
      - term: Textual format
        uri: http://edamontology.org/format_2330
    - data:
        term: Phylogenetic tree
        uri: http://edamontology.org/data_0872
      format:
      - term: newick
        uri: http://edamontology.org/format_1910
    - data:
        term: Taxonomic classification
        uri: http://edamontology.org/data_1872
      format:
      - term: CSV
        uri: http://edamontology.org/format_3752
  homepage: https://www.arb-silva.de
  homepage_status: 0
  language: []
  lastUpdate: '2025-06-30T13:26:42.882897Z'
  license: CC-BY-4.0
  link:
  - note: SILVA Taxonomy Browser
    type:
    - Service
    url: https://www.arb-silva.de/browser/
  - note: SILVA metadata search
    type:
    - Service
    url: https://www.arb-silva.de/search/
  - note: 'ACT: Alignment, Classification and Tree Service'
    type:
    - Service
    url: https://www.arb-silva.de/aligner/
  - note: SILVA Probe Match and Evaluation Tool
    type:
    - Service
    url: https://www.arb-silva.de/search/testprobe/
  - note: SILVA Primer Evaluation Tool
    type:
    - Service
    url: https://www.arb-silva.de/search/testprime/
  - note: Web-based viewer for the SILVA guide trees
    type:
    - Service
    url: https://treeviewer.arb-silva.de/
  maturity: Mature
  name: SILVA rRNA database
  operatingSystem: []
  otherID:
  - type: rrid
    value: RRID:SCR_006423
    version: null
  owner: silva
  publication:
  - doi: 10.1093/nar/gks1219
    metadata:
      abstract: SILVA (from Latin silva, forest, http://www.arb-silva.de) is a comprehensive
        web resource for up to date, quality-controlled databases of aligned ribosomal
        RNA (rRNA) gene sequences from the Bacteria, Archaea and Eukaryota domains
        and supplementary online services. The referred database release 111 (July
        2012) contains 3194 778 small subunit and 288717 large subunit rRNA gene sequences.
        Since the initial description of the project, substantial new features have
        been introduced, including advanced quality control procedures, an improved
        rRNA gene aligner, online tools for probe and primer evaluation and optimized
        browsing, searching and downloading on the website. Furthermore, the extensively
        curated SILVA taxonomy and the new non-redundant SILVA datasets provide an
        ideal reference for high-throughput classification of data from next-generation
        sequencing approaches. © The Author(s) 2012.
      authors:
      - name: Quast C.
      - name: Pruesse E.
      - name: Yilmaz P.
      - name: Gerken J.
      - name: Schweer T.
      - name: Yarza P.
      - name: Peplies J.
      - name: Glockner F.O.
      citationCount: 22633
      date: '2013-01-01T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'The SILVA ribosomal RNA gene database project: Improved data processing
        and web-based tools'
    note: null
    pmcid: PMC3531112
    pmid: '23193283'
    type:
    - Primary
    version: null
  - doi: 10.1093/nar/gkt1209
    metadata:
      abstract: SILVA (from Latin silva, forest, http://www.arb-silva.de) is a comprehensive
        resource for up-to-date quality-controlled databases of aligned ribosomal
        RNA (rRNA) gene sequences from the Bacteria, Archaea and Eukaryota domains
        and supplementary online services. SILVA provides a manually curated taxonomy
        for all three domains of life, based on representative phylogenetic trees
        for the small- and large-subunit rRNA genes. This article describes the improvements
        the SILVA taxonomy has undergone in the last 3 years. Specifically we are
        focusing on the curation process, the various resources used for curation
        and the comparison of the SILVA taxonomy with Greengenes and RDP-II taxonomies.
        Our comparisons not only revealed a reasonable overlap between the taxa names,
        but also points to significant differences in both names and numbers of taxa
        between the three resources. © 2013 The Author(s). Published by Oxford University
        Press.
      authors:
      - name: Yilmaz P.
      - name: Parfrey L.W.
      - name: Yarza P.
      - name: Gerken J.
      - name: Pruesse E.
      - name: Quast C.
      - name: Schweer T.
      - name: Peplies J.
      - name: Ludwig W.
      - name: Glockner F.O.
      citationCount: 2590
      date: '2014-01-01T00:00:00Z'
      journal: Nucleic Acids Research
      title: The SILVA and "all-species Living Tree Project (LTP)" taxonomic frameworks
    note: null
    pmcid: PMC3965112
    pmid: '24293649'
    type:
    - Other
    version: null
  - doi: 10.1093/nar/gkm864
    metadata:
      abstract: 'Sequencing ribosomal RNA (rRNA) genes is currently the method of
        choice for phylogenetic reconstruction, nucleic acid based detection and quantification
        of microbial diversity. The ARB software suite with its corresponding rRNA
        datasets has been accepted by researchers worldwide as a standard tool for
        large scale rRNA analysis. However, the rapid increase of publicly available
        rRNA sequence data has recently hampered the maintenance of comprehensive
        and curated rRNA knowledge databases. A new system, SILVA (from Latin silva,
        forest), was implemented to provide a central comprehensive web resource for
        up to date, quality controlled databases of aligned rRNA sequences from the
        Bacteria, Archaea and Eukarya domains. All sequences are checked for anomalies,
        carry a rich set of sequence associated contextual information, have multiple
        taxonomic classifications, and the latest validly described nomenclature.
        Furthermore, two precompiled sequence datasets compatible with ARB are offered
        for download on the SILVA website: (i) the reference (Ref) datasets, comprising
        only high quality, nearly full length sequences suitable for in-depth phylogenetic
        analysis and probe design and (ii) the comprehensive Parc datasets with all
        publicly available rRNA sequences longer than 300 nucleotides suitable for
        biodiversity analyses. The latest publicly available database release 91 (August
        2007) hosts 547 521 sequences split into 461 823 small subunit and 85 689
        large subunit rRNAs. © 2007 The Author(s).'
      authors:
      - name: Pruesse E.
      - name: Quast C.
      - name: Knittel K.
      - name: Fuchs B.M.
      - name: Ludwig W.
      - name: Peplies J.
      - name: Glockner F.O.
      citationCount: 5291
      date: '2007-12-01T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'SILVA: A comprehensive online resource for quality checked and aligned
        ribosomal RNA sequence data compatible with ARB'
    note: null
    pmcid: PMC2175337
    pmid: '17947321'
    type:
    - Other
    version: null
  - doi: 10.1093/bioinformatics/bts252
    metadata:
      abstract: 'Motivation: In the analysis of homologous sequences, computation
        of multiple sequence alignments (MSAs) has become a bottleneck. This is especially
        troublesome for marker genes like the ribosomal RNA (rRNA) where already millions
        of sequences are publicly available and individual studies can easily produce
        hundreds of thousands of new sequences. Methods have been developed to cope
        with such numbers, but further improvements are needed to meet accuracy requirements.Results:
        In this study, we present the SILVA Incremental Aligner (SINA) used to align
        the rRNA gene databases provided by the SILVA ribosomal RNA project. SINA
        uses a combination of k-mer searching and partial order alignment (POA) to
        maintain very high alignment accuracy while satisfying high throughput performance
        demands. SINA was evaluated in comparison with the commonly used high throughput
        MSA programs PyNAST and mothur. The three BRAliBase III benchmark MSAs could
        be reproduced with 99.3, 97.6 and 96.1 accuracy. A larger benchmark MSA comprising
        38 772 sequences could be reproduced with 98.9 and 99.3% accuracy using reference
        MSAs comprising 1000 and 5000 sequences. SINA was able to achieve higher accuracy
        than PyNAST and mothur in all performed benchmarks. © The Author(s) 2012.
        Published by Oxford University Press.'
      authors:
      - name: Pruesse E.
      - name: Peplies J.
      - name: Glockner F.O.
      citationCount: 2408
      date: '2012-07-01T00:00:00Z'
      journal: Bioinformatics
      title: 'SINA: Accurate high-throughput multiple sequence alignment of ribosomal
        RNA genes'
    note: null
    pmcid: PMC3389763
    pmid: '22556368'
    type:
    - Other
    version: null
  - doi: 10.1016/j.jbiotec.2017.06.1198
    metadata:
      abstract: SILVA (lat. forest) is a comprehensive web resource, providing services
        around up to date, high-quality datasets of aligned ribosomal RNA gene (rDNA)
        sequences from the Bacteria, Archaea, and Eukaryota domains. SILVA dates back
        to the year 1991 when Dr. Wolfgang Ludwig from the Technical University Munich
        started the integrated software workbench ARB (lat. tree) to support high-quality
        phylogenetic inference and taxonomy based on the SSU and LSU rDNA marker genes.
        At that time, the ARB project maintained both, the sequence reference datasets
        and the software package for data analysis. In 2005, with the massive increase
        of DNA sequence data, the maintenance of the software system ARB and the corresponding
        rRNA databases SILVA was split between Munich and the Microbial Genomics and
        Bioinformatics Research Group in Bremen. ARB has been continuously developed
        to include new features and improve the usability of the workbench. Thousands
        of users worldwide appreciate the seamless integration of common analysis
        tools under a central graphical user interface, in combination with its versatility.
        The first SILVA release was deployed in February 2007 based on the EMBL-EBI/ENA
        release 89. Since then, full SILVA releases offering the database content
        in various flavours are published at least annually, complemented by intermediate
        web-releases where only the SILVA web dataset is updated. SILVA is the only
        rDNA database project worldwide where special emphasis is given to the consistent
        naming of clades of uncultivated (environmental) sequences, where no validly
        described cultivated representatives are available. Also exclusive for SILVA
        is the maintenance of both comprehensive aligned 16S/18S rDNA and 23S/28S
        rDNA sequence datasets. Furthermore, the SILVA alignments and trees were designed
        to include Eukaryota, another unique feature among rDNA databases. With the
        termination of the European Ribosomal RNA Database Project in 2007, the SILVA
        database has become the authoritative rDNA database project for Europe. The
        application spectrum of ARB and SILVA ranges from biodiversity analysis, medical
        diagnostics, to biotechnology and quality control for academia and industry.
      authors:
      - name: Glockner F.O.
      - name: Yilmaz P.
      - name: Quast C.
      - name: Gerken J.
      - name: Beccati A.
      - name: Ciuprina A.
      - name: Bruns G.
      - name: Yarza P.
      - name: Peplies J.
      - name: Westram R.
      - name: Ludwig W.
      citationCount: 635
      date: '2017-11-10T00:00:00Z'
      journal: Journal of Biotechnology
      title: 25 years of serving the community with ribosomal RNA gene reference databases
        and tools
    note: null
    pmcid: null
    pmid: '28648396'
    type:
    - Review
    version: null
  - doi: 10.1186/s12859-017-1841-3
    metadata:
      abstract: 'Background: Phylogenetic trees are an important tool to study the
        evolutionary relationships among organisms. The huge amount of available taxa
        poses difficulties in their interactive visualization. This hampers the interaction
        with the users to provide feedback for the further improvement of the taxonomic
        framework. Results: The SILVA Tree Viewer is a web application designed for
        visualizing large phylogenetic trees without requiring the download of any
        software tool or data files. The SILVA Tree Viewer is based on Web Geographic
        Information Systems (Web-GIS) technology with a PostgreSQL backend. It enables
        zoom and pan functionalities similar to Google Maps. The SILVA Tree Viewer
        enables access to two phylogenetic (guide) trees provided by the SILVA database:
        the SSU Ref NR99 inferred from high-quality, full-length small subunit sequences,
        clustered at 99% sequence identity and the LSU Ref inferred from high-quality,
        full-length large subunit sequences. Conclusions: The Tree Viewer provides
        tree navigation, search and browse tools as well as an interactive feedback
        system to collect any kinds of requests ranging from taxonomy to data curation
        and improving the tool itself.'
      authors:
      - name: Beccati A.
      - name: Gerken J.
      - name: Quast C.
      - name: Yilmaz P.
      - name: Glockner F.O.
      citationCount: 29
      date: '2017-09-30T00:00:00Z'
      journal: BMC Bioinformatics
      title: 'SILVA tree viewer: Interactive web browsing of the SILVA phylogenetic
        guide trees'
    note: null
    pmcid: null
    pmid: null
    type:
    - Other
    version: null
  relation:
  - biotoolsID: silvangs
    type: usedBy
  - biotoolsID: d3hub
    type: includedIn
  toolType:
  - Web application
  - Database portal
  topic:
  - term: Functional, regulatory and non-coding RNA
    uri: http://edamontology.org/topic_0659
  - term: Sequence analysis
    uri: http://edamontology.org/topic_0080
  - term: Phylogenetics
    uri: http://edamontology.org/topic_3293
  - term: Taxonomy
    uri: http://edamontology.org/topic_0637
  - term: Biodiversity
    uri: http://edamontology.org/topic_3050
  - term: Microbiology
    uri: http://edamontology.org/topic_3301
  - term: Probes and primers
    uri: http://edamontology.org/topic_0632
  validated: 1
  version: []
- accessibility: Open access
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  biotoolsCURIE: biotools:biosimulations
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  cost: Free of charge
  credit:
  - email: karr@mssm.edu
    fundrefid: null
    gridid: null
    name: Jonathan Karr
    note: null
    orcidid: https://orcid.org/0000-0002-2605-5080
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: https://www.karrlab.org
  - email: null
    fundrefid: null
    gridid: null
    name: Bilal Shaikh
    note: null
    orcidid: https://orcid.org/0000-0001-5801-5510
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: null
  description: BioSimulations is a web application for sharing and re-using biomodels,
    simulations, and visualizations of simulations results. BioSimulations supports
    a wide range of modeling frameworks (e.g., kinetic, constraint-based, and logical
    modeling), model formats (e.g., BNGL, CellML, SBML), and simulation tools (e.g.,
    COPASI, libRoadRunner/tellurium, NFSim, VCell). BioSimulations aims to help researchers
    discover published models that might be useful for their research and quickly
    try them via a simple web-based interface.
  documentation:
  - note: null
    type:
    - General
    url: https://docs.biosimulations.org
  - note: null
    type:
    - API documentation
    url: https://api.biosimulations.org/
  - note: null
    type:
    - Code of conduct
    url: https://docs.biosimulations.org/developers/conduct/
  - note: null
    type:
    - Terms of use
    url: https://docs.biosimulations.org/about/terms/
  download: []
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  function:
  - cmd: null
    input:
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        term: Mathematical model
        uri: http://edamontology.org/data_0950
      format:
      - term: SBML
        uri: http://edamontology.org/format_2585
      - term: CellML
        uri: http://edamontology.org/format_3240
    note: null
    operation:
    - term: Visualisation
      uri: http://edamontology.org/operation_0337
    - term: Modelling and simulation
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    output:
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        term: Trajectory data
        uri: http://edamontology.org/data_3870
      format:
      - term: CSV
        uri: http://edamontology.org/format_3752
      - term: SVG
        uri: http://edamontology.org/format_3604
  homepage: https://www.biosimulations.org/
  homepage_status: 0
  language:
  - JavaScript
  - Python
  lastUpdate: '2025-06-17T16:32:28.548746Z'
  license: MIT
  link:
  - note: null
    type:
    - Issue tracker
    url: https://github.com/reproducible-biomedical-modeling/Biosimulations/issues
  - note: null
    type:
    - Repository
    url: https://github.com/reproducible-biomedical-modeling/Biosimulations
  - note: null
    type:
    - Service
    url: https://api.biosimulations.org/
  maturity: Emerging
  name: BioSimulations
  operatingSystem: []
  otherID:
  - type: rrid
    value: RRID:SCR_018733
    version: null
  owner: Bioinfo
  publication: []
  relation:
  - biotoolsID: runbiosimulations
    type: uses
  - biotoolsID: biosimulators
    type: uses
  - biotoolsID: biomodels
    type: uses
  - biotoolsID: sbml
    type: uses
  - biotoolsID: bionetgen
    type: uses
  - biotoolsID: cobrapy
    type: uses
  - biotoolsID: copasi
    type: uses
  - biotoolsID: libroadrunner
    type: uses
  toolType:
  - Command-line tool
  - Web API
  - Web application
  - Web service
  topic:
  - term: Systems biology
    uri: http://edamontology.org/topic_2259
  - term: Molecular interactions, pathways and networks
    uri: http://edamontology.org/topic_0602
  validated: 1
  version: []
- accessibility: Open access
  additionDate: '2025-05-27T01:09:26.563025Z'
  biotoolsCURIE: biotools:human_microbiome_compendium
  biotoolsID: human_microbiome_compendium
  collectionID:
  - microbiome
  confidence_flag: tool
  cost: Free of charge
  credit:
  - email: rabdill@uchicago.edu
    fundrefid: null
    gridid: null
    name: Richard Abdill
    note: null
    orcidid: https://orcid.org/0000-0001-9565-5832
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: https://blekhmanlab.org
  description: Collection of human microbiome sequencing data that pairs subject metadata
    with relative abundance data derived from amplicon and shotgun metagenomic sequencing
    processed via uniform pipelines.
  documentation:
  - note: null
    type:
    - User manual
    url: https://zenodo.org/records/15122187/files/README.md
  download:
  - note: DOI links to the most recent release
    type: Biological data
    url: https://doi.org/10.5281/zenodo.8186993
    version: null
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  function: []
  homepage: https://microbiomap.org
  homepage_status: 0
  language:
  - R
  - Python
  lastUpdate: '2025-05-27T01:09:26.566817Z'
  license: CC-BY-2.0
  link:
  - note: Homepage of the project with links to multiple tools and datasets
    type:
    - Other
    url: https://microbiomap.org
  - note: Link to the most recent release of the compendium dataset
    type:
    - Repository
    url: https://doi.org/10.5281/zenodo.8186993
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  publication:
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    metadata: null
    note: null
    pmcid: PMC11848717
    pmid: '39848248'
    type:
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    version: 1.1.0
  relation: []
  toolType:
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  topic:
  - term: Metagenomics
    uri: http://edamontology.org/topic_3174
  - term: Microbial ecology
    uri: http://edamontology.org/topic_3697
  - term: FAIR data
    uri: http://edamontology.org/topic_4012
  - term: Metagenomics
    uri: http://edamontology.org/topic_3174
  - term: Phylogenetics
    uri: http://edamontology.org/topic_3293
  validated: 0
  version: []
- accessibility: null
  additionDate: '2017-03-27T07:19:58Z'
  biotoolsCURIE: biotools:isfinder
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  confidence_flag: null
  cost: null
  credit:
  - email: Patricia.Siguier@ibcg.biotoul.fr
    fundrefid: null
    gridid: null
    name: Patricia Siguier
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  description: It is a dedicated insertion sequence (IS) database which assigns names
    to individual ISs to maintain a coherent nomenclature, an IS repositaory including
    >3000 individual ISs from both bacteria and archaea and provides a basis for IS
    classification. Each IS is indexed in ISfinder with various associated pieces
    of information and classified into a group or family to provide some insight into
    its phylogeny.
  documentation:
  - note: null
    type:
    - General
    url: https://www-is.biotoul.fr/general_information.php
  download: []
  editPermission:
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  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Genome indexing
      uri: http://edamontology.org/operation_3211
    - term: Bibliography generation
      uri: http://edamontology.org/operation_3349
    - term: Gene-set enrichment analysis
      uri: http://edamontology.org/operation_2436
    output: []
  homepage: http://www-is.biotoul.fr
  homepage_status: 0
  language:
  - SQL
  lastUpdate: '2025-01-24T09:59:36.949842Z'
  license: null
  link: []
  maturity: null
  name: ISfinder
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID:
  - type: rrid
    value: RRID:SCR_003020
    version: null
  owner: Patricia_SIguier
  publication:
  - doi: 10.1093/nar/gkp947
    metadata:
      abstract: Insertion sequences (ISs) are among the smallest and simplest autonomous
        transposable elements. ISfinder (http://www-is.biotoul.fr/) is a dedicated
        IS database which assigns names to individual ISs to maintain a coherent nomenclature,
        an IS repository including >3000 individual ISs from both bacteria and archaea
        and provides a basis for IS classification. Each IS is indexed in ISfinder
        with various associated pieces of information (the complete nucleotide sequence,
        the sequence of the ends and target sites, potential open reading frames,
        strain of origin, distribution in other strains and available bibliography)
        and classified into a group or family to provide some insight into its phylogeny.
        ISfinder also includes extensive background information on ISs and transposons
        in general. Online tools are gradually being added. At present, it is difficult
        to visualize the global distribution of ISs in a given bacterial genome. Such
        information would facilitate understanding of the impact of these small transposable
        elements on shaping their host genome. Here we describe ISbrowser (http://www-genome.biotoul.fr/ISbrowser.php),
        an extension to the ISfinder platform and a tool which permits visualization
        of the position, orientation and distribution of complete and partial ISs
        in individual prokaryotic genomes. © The Author(s) 2009. Published by Oxford
        University Press.
      authors:
      - name: Kichenaradja P.
      - name: Siguier P.
      - name: Perochon J.
      - name: Chandler M.
      citationCount: 43
      date: '2009-11-11T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'ISbrowser: An extension of ISfinder for visualizing insertion sequences
        in prokaryotic genomes'
    note: null
    pmcid: PMC2808865
    pmid: '19906702'
    type: []
    version: null
  relation: []
  toolType:
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  topic:
  - term: Literature and language
    uri: http://edamontology.org/topic_3068
  - term: Phylogeny
    uri: http://edamontology.org/topic_0084
  - term: Mobile genetic elements
    uri: http://edamontology.org/topic_0798
  - term: Model organisms
    uri: http://edamontology.org/topic_0621
  - term: Sequencing
    uri: http://edamontology.org/topic_3168
  validated: 1
  version: []
- accessibility: null
  additionDate: '2021-01-18T11:52:53Z'
  biotoolsCURIE: biotools:pharos
  biotoolsID: pharos
  collectionID: []
  confidence_flag: tool
  cost: null
  credit:
  - email: toprea@salud.unm.edu
    fundrefid: null
    gridid: null
    name: Tudor I Oprea
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  description: 'Pharos is the web interface for data collected by the Illuminating
    the Druggable Genome initiative. Target, disease and ligand information are collected
    and displayed.


    You are using an outdated browser. Please upgrade your browser to improve your
    experience.'
  documentation:
  - note: null
    type:
    - API documentation
    url: https://pharos.nih.gov/api
  download: []
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  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Aggregation
      uri: http://edamontology.org/operation_3436
    - term: Visualisation
      uri: http://edamontology.org/operation_0337
    - term: Data retrieval
      uri: http://edamontology.org/operation_2422
    output: []
  homepage: https://pharos.nih.gov/
  homepage_status: 0
  language: []
  lastUpdate: '2024-11-24T20:36:55.533021Z'
  license: null
  link: []
  maturity: null
  name: Pharos
  operatingSystem: []
  otherID:
  - type: rrid
    value: 'RRID: SCR_016924'
    version: null
  owner: zsmag19
  publication:
  - doi: 10.1093/nar/gkaa993
    metadata:
      abstract: 'In 2014, the National Institutes of Health (NIH) initiated the Illuminating
        the Druggable Genome (IDG) program to identify and improve our understanding
        of poorly characterized proteins that can potentially be modulated using small
        molecules or biologics. Two resources produced from these efforts are: The
        Target Central Resource Database (TCRD) (http://juniper.health.unm.edu/tcrd/)
        and Pharos (https://pharos.nih.gov/), a web interface to browse the TCRD.
        The ultimate goal of these resources is to highlight and facilitate research
        into currently understudied proteins, by aggregating a multitude of data sources,
        and ranking targets based on the amount of data available, and presenting
        data in machine learning ready format. Since the 2017 release, both TCRD and
        Pharos have produced two major releases, which have incorporated or expanded
        an additional 25 data sources. Recently incorporated data types include human
        and viral-human protein-protein interactions, protein-disease and protein-phenotype
        associations, and drug-induced gene signatures, among others. These aggregated
        data have enabled us to generate new visualizations and content sections in
        Pharos, in order to empower users to find new areas of study in the druggable
        genome.'
      authors:
      - name: Sheils T.K.
      - name: Mathias S.L.
      - name: Kelleher K.J.
      - name: Siramshetty V.B.
      - name: Nguyen D.-T.
      - name: Bologa C.G.
      - name: Jensen L.J.
      - name: Vidovic D.
      - name: Koleti A.
      - name: Schurer S.C.
      - name: Waller A.
      - name: Yang J.J.
      - name: Holmes J.
      - name: Bocci G.
      - name: Southall N.
      - name: Dharkar P.
      - name: Mathe E.
      - name: Simeonov A.
      - name: Oprea T.I.
      citationCount: 93
      date: '2021-01-08T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'TCRD and Pharos 2021: Mining the human proteome for disease biology'
    note: null
    pmcid: PMC7778974
    pmid: '33156327'
    type: []
    version: null
  relation: []
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  topic:
  - term: Proteomics
    uri: http://edamontology.org/topic_0121
  - term: Genotype and phenotype
    uri: http://edamontology.org/topic_0625
  - term: Sequence analysis
    uri: http://edamontology.org/topic_0080
  - term: Pathology
    uri: http://edamontology.org/topic_0634
  - term: Machine learning
    uri: http://edamontology.org/topic_3474
  validated: 1
  version: []
- accessibility: null
  additionDate: '2017-08-03T18:55:38Z'
  biotoolsCURIE: biotools:phenoman
  biotoolsID: phenoman
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  confidence_flag: null
  cost: null
  credit:
  - email: sleal@bcm.edu
    fundrefid: null
    gridid: null
    name: null
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  description: Freeware that provides approaches for efficient exploration and management
    of phenotype data.
  documentation:
  - note: null
    type:
    - General
    url: https://storage.googleapis.com/google-code-archive-downloads/v2/code.google.com/phenoman/doc_phenoman.pdf
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  function:
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    input: []
    note: null
    operation:
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      uri: http://edamontology.org/operation_2428
    - term: Statistical calculation
      uri: http://edamontology.org/operation_2238
    output: []
  homepage: https://code.google.com/p/phenoman/
  homepage_status: 0
  language:
  - R
  - Python
  lastUpdate: '2024-11-24T20:36:54.133767Z'
  license: GPL-3.0
  link:
  - note: null
    type:
    - Software catalogue
    url: http://www.mybiosoftware.com/phenoman-1-0rc-exploration-and-management-of-phenotype-data.html
  maturity: null
  name: PhenoMan
  operatingSystem:
  - Linux
  - Mac
  otherID:
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    value: 'RRID: SCR_005249'
    version: null
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  publication:
  - doi: 10.1093/bioinformatics/btt682
    metadata:
      abstract: 'Motivation:Next-generation sequencing and other high-throughput technology
        advances have promoted great interest in detecting associations between complex
        traits and genetic variants. Phenotype selection, quality control (QC) and
        control of confounders are crucial and can have a great impact on the ability
        to detect associations. Although there are programs to perform association
        analyses, e.g. PLINK and GenABEL, they cannot be used for comprehensive management
        and QC of phenotype data. To address this need PhenoMan was developed: to
        select individuals based on multiple phenotype criteria or population membership;
        control for missing covariate data; remove related individuals, duplicate
        samples and individuals with incorrect sex specification; recode primary traits
        and covariates; transform data; remove or winsorize outliers; select covariates
        for analysis; and create residuals. To ensure consistency and harmonization
        between analyses, a report is generated for every dataset. Summary statistics
        are also provided in graphical or text format. PhenoMan can be used for selection
        and manipulation of quantitative, disease and control data.Summary:Phenoman
        is freeware that provides approaches for efficient exploration and management
        of phenotype data. Proper QC of phenotypes before proceeding to the association
        analysis is critical to ensure control of type I and II errors, reliable effect
        estimates and consistent results between studies. PhenoMan is highly beneficial
        for the preparation of qualitative and quantitative trait data for association
        studies using new datasets as well as those obtained from public repositories.
        © 2013 The Author 2013.'
      authors:
      - name: Li B.
      - name: Wang G.
      - name: Leal S.M.
      citationCount: 2
      date: '2014-02-01T00:00:00Z'
      journal: Bioinformatics
      title: 'PhenoMan: Phenotypic data exploration, selection, management and quality
        control for association studies of rare and common variants'
    note: null
    pmcid: PMC3904519
    pmid: '24336645'
    type: []
    version: null
  relation: []
  toolType:
  - Command-line tool
  topic:
  - term: Genetics
    uri: http://edamontology.org/topic_3053
  - term: Genotype and phenotype
    uri: http://edamontology.org/topic_0625
  validated: 1
  version: []
- accessibility: null
  additionDate: '2017-12-18T00:10:55Z'
  biotoolsCURIE: biotools:philius
  biotoolsID: philius
  collectionID: []
  confidence_flag: null
  cost: null
  credit:
  - email: null
    fundrefid: null
    gridid: null
    name: null
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: http://noble.gs.washington.edu/
  description: Philius predicts protein transmembrane topology and signal peptides.
  documentation:
  - note: null
    type:
    - General
    url: https://noble.gs.washington.edu/proj/philius/README
  download: []
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  function:
  - cmd: null
    input: []
    note: null
    operation:
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      uri: http://edamontology.org/operation_2479
    output: []
  homepage: http://noble.gs.washington.edu/proj/philius/
  homepage_status: 0
  language:
  - Python
  lastUpdate: '2024-11-24T20:36:52.933224Z'
  license: null
  link:
  - note: null
    type:
    - Software catalogue
    url: http://www.mybiosoftware.com/philius-predict-protein-transmembrane-topology-signal-peptides.html
  maturity: null
  name: Philius
  operatingSystem:
  - Linux
  otherID:
  - type: rrid
    value: 'RRID: SCR_004625'
    version: null
  owner: mbs_import
  publication:
  - doi: 10.1371/journal.pcbi.1000213
    metadata:
      abstract: Hidden Markov models (HMMs) have been successfully applied to the
        tasks of transmembrane protein topology prediction and signal peptide prediction.
        In this paper we expand upon this work by making use of the more powerful
        class of dynamic Bayesian networks (DBNs). Our model, Philius, is inspired
        by a previously published HMM, Phobius, and combines a signal peptide submodel
        with a transmembrane submodel. We introduce a two-stage DBN decoder that combines
        the power of posterior decoding with the grammar constraints of Viterbi-style
        decoding. Philius also provides protein type, segment, and topology confidence
        metrics to aid in the interpretation of the predictions. We report a relative
        improvement of 13% over Phobius in full-topology prediction accuracy on transmembrane
        proteins, and a sensitivity and specificity of 0.96 in detecting signal peptides.
        We also show that our confidence metrics correlate well with the observed
        precision. In addition, we have made predictions on all 6.3 million proteins
        in the Yeast Resource Center (YRC) database. This large-scale study provides
        an overall picture of the relative numbers of proteins that include a signal-peptide
        and/or one or more transmembrane segments as well as a valuable resource for
        the scientific community. All DBNs are implemented using the Graphical Models
        Toolkit. Source code for the models described here is available at http://noble.gs.washington.edu/proj/philius.
        A Philius Web server is available at http://www.yeastrc.org/philius, and the
        predictions on the YRC database are available at http://www.yeastrc.org/pdr.
        © 2008 Reynolds et al.
      authors:
      - name: Reynolds S.M.
      - name: Kall L.
      - name: Riffle M.E.
      - name: Bilmes J.A.
      - name: Noble W.S.
      citationCount: 206
      date: '2008-01-01T00:00:00Z'
      journal: PLoS Computational Biology
      title: Transmembrane topology and signal peptide prediction using dynamic Bayesian
        networks
    note: null
    pmcid: PMC2570248
    pmid: '18989393'
    type:
    - Primary
    version: null
  relation: []
  toolType:
  - Command-line tool
  topic:
  - term: Peptides
    uri: http://edamontology.org/topic_0154
  validated: 1
  version: []
- accessibility: null
  additionDate: '2017-12-18T00:03:07Z'
  biotoolsCURIE: biotools:abner
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  collectionID: []
  confidence_flag: null
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  credit:
  - email: null
    fundrefid: null
    gridid: null
    name: null
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: http://www.cs.cmu.edu/~bsettles/index.html
  description: ABNER (A Biomedical Named Entity Recognizer) is a software tool for
    molecular biology text analysis.
  documentation:
  - note: null
    type:
    - API documentation
    url: http://pages.cs.wisc.edu/~bsettles/abner/javadoc/
  download: []
  editPermission:
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  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Text mining
      uri: http://edamontology.org/operation_0306
    output: []
  homepage: http://pages.cs.wisc.edu/~bsettles/abner/
  homepage_status: 0
  language:
  - Java
  lastUpdate: '2024-11-24T20:36:50.416529Z'
  license: null
  link:
  - note: null
    type:
    - Software catalogue
    url: http://www.mybiosoftware.com/abner-1-5-molecular-biology-text-analysis.html
  maturity: null
  name: ABNER
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  - Windows
  - Mac
  otherID:
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    value: RRID:SCR_011868
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  publication:
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    metadata:
      abstract: 'Summary: ABNER (A Biomedical Named Entity Recognizer) is an open
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        learning system using conditional random fields with a variety of orthographic
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        graphical interface and includes two modules for tagging entities (e.g. protein
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        state of the art. It also includes a Java application programming interface
        allowing users to incorporate ABNER into their own systems and train models
        on new corpora. © The Author 2005. Published by Oxford University Press. All
        rights reserved.'
      authors:
      - name: Settles B.
      citationCount: 361
      date: '2005-07-15T00:00:00Z'
      journal: Bioinformatics
      title: 'ABNER: An open source tool for automatically tagging genes, proteins
        and other entity names in text'
    note: null
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    version: null
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  - term: Molecular biology
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  validated: 1
  version:
  - '1.5'
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  description: This database is dedicated to the collection, analysis and classification
    of sequenced mobile genetic elements (MGEs, in particular phages and plasmids).
    In addition to providing information on the MGEs content, classifications are
    available at various levels of organization.
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    - General
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    - term: Query and retrieval
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    - term: Genetic variation analysis
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  - doi: 10.1093/nar/gkp938
    metadata:
      abstract: The ACLAME database is dedicated to the collection, analysis and classification
        of sequenced mobile genetic elements (MGEs, in particular phages and plasmids).
        In addition to providing information on the MGEs content, classifications
        are available at various levels of organization. At the gene/protein level,
        families group similar sequences that are expected to share the same function.
        Families of four or more proteins are manually assigned with a functional
        annotation using the GeneOntology and the locally developed ontology MeGO
        dedicated to MGEs. At the genome level, evolutionary cohesive modules group
        sets of protein families shared among MGEs. At the population level, networks
        display the reticulate evolutionary relationships among MGEs. To increase
        the coverage of the phage sequence space, ACLAME version 0.4 incorporates
        760 high-quality predicted prophages selected from the Prophinder database.
        Most of the data can be downloaded from the freely accessible ACLAME web site
        (http://aclame.ulb.ac.be). The BLAST interface for querying the database has
        been extended and numerous tools for in-depth analysis of the results have
        been added. © The Author(s) 2009. Published by Oxford University Press.
      authors:
      - name: Leplae R.
      - name: Lima-Mendez G.
      - name: Toussaint A.
      citationCount: 242
      date: '2009-11-23T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'ACLAME: A CLAssification of mobile genetic elements, update 2010'
    note: null
    pmcid: PMC2808911
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    version: null
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  - term: Gene and protein families
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  - term: Model organisms
    uri: http://edamontology.org/topic_0621
  - term: Genetics
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  - term: Protein interaction experiment
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  version: []
- accessibility: null
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  description: 'Implements five methods to analyze admixture: the three-population
    test, D-statistics, F4-ratio estimation, admixture graph fitting, and rolloff.
    In addition, it computes lower and upper bounds on admixture proportions based
    on f3-statistics. Contains 6 programs: convertf, qp3Pop, qpBound, qpDstat, qpF4Ratio,
    and rolloff.'
  documentation:
  - note: null
    type:
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  language:
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  - Perl
  - C
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  link: []
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  publication:
  - doi: 10.1534/genetics.112.145037
    metadata:
      abstract: Population mixture is an important process in biology. We present
        a suite of methods for learning about population mixtures, implemented in
        a software package called ADMIXTOOLS, that support formal tests for whether
        mixture occurred and make it possible to infer proportions and dates of mixture.
        We also describe the development of a new single nucleotide polymorphism (SNP)
        array consisting of 629,433 sites with clearly documented ascertainment that
        was specifically designed for population genetic analyses and that we genotyped
        in 934 individuals from 53 diverse populations. To illustrate the methods,
        we give a number of examples that provide new insights about the history of
        human admixture. The most striking finding is a clear signal of admixture
        into northern Europe, with one ancestral population related to present-day
        Basques and Sardinians and the other related to present-day populations of
        northeast Asia and the Americas. This likely reflects a history of admixture
        between Neolithic migrants and the indigenous Mesolithic population of Europe,
        consistent with recent analyses of ancient bones from Sweden and the sequencing
        of the genome of the Tyrolean "Iceman." © 2012 by the Genetics Society of
        America.
      authors:
      - name: Patterson N.
      - name: Moorjani P.
      - name: Luo Y.
      - name: Mallick S.
      - name: Rohland N.
      - name: Zhan Y.
      - name: Genschoreck T.
      - name: Webster T.
      - name: Reich D.
      citationCount: 1605
      date: '2012-11-01T00:00:00Z'
      journal: Genetics
      title: Ancient admixture in human history
    note: null
    pmcid: PMC3522152
    pmid: '22960212'
    type:
    - Primary
    version: null
  relation: []
  toolType:
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  topic:
  - term: Population genetics
    uri: http://edamontology.org/topic_3056
  validated: 1
  version: []
- accessibility: null
  additionDate: '2017-12-18T00:03:10Z'
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    url: http://alchemy.sourceforge.net/
  description: ALCHEMY is a method for automated calling of diploid genotypes from
    raw intensity data produced by various high-throughput multiplexed SNP genotyping
    methods.
  documentation:
  - note: null
    type:
    - General
    url: http://alchemy.sourceforge.net/
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    operation:
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  language:
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  lastUpdate: '2024-11-24T20:36:46.685521Z'
  license: null
  link:
  - note: null
    type:
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    url: http://www.mybiosoftware.com/alchemy-1-07-an-automated-population-genetic-model-driven-snp-genotype-calling-method.html
  maturity: null
  name: ALCHEMY
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  publication:
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    metadata:
      abstract: 'Motivation: The development of new high-throughput genotyping products
        requires a significant investment in testing and training samples to evaluate
        and optimize the product before it can be used reliably on new samples. One
        reason for this is current methods for automated calling of genotypes are
        based on clustering approaches which require a large number of samples to
        be analyzed simultaneously, or an extensive training dataset to seed clusters.
        In systems where inbred samples are of primary interest, current clustering
        approaches perform poorly due to the inability to clearly identify a heterozygote
        cluster. Results: As part of the development of two custom single nucleotide
        polymorphism genotyping products for Oryza sativa (domestic rice), we have
        developed a new genotype calling algorithm called ''ALCHEMY'' based on statistical
        modeling of the raw intensity data rather than modelless clustering. A novel
        feature of the model is the ability to estimate and incorporate inbreeding
        information on a per sample basis allowing accurate genotyping of both inbred
        and heterozygous samples even when analyzed simultaneously. Since clustering
        is not used explicitly, ALCHEMY performs well on small sample sizes with accuracy
        exceeding 99% with as few as 18 samples. © The Author(s) 2010. Published by
        Oxford University Press.'
      authors:
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      - name: Tung C.-W.
      - name: Zhao K.
      - name: Reynolds A.
      - name: McCouch S.R.
      - name: Bustamante C.D.
      citationCount: 40
      date: '2010-12-01T00:00:00Z'
      journal: Bioinformatics
      title: 'ALCHEMY: A reliable method for automated SNP genotype calling for small
        batch sizes and highly homozygous populations'
    note: null
    pmcid: PMC2982150
    pmid: '20926420'
    type:
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    version: null
  relation: []
  toolType:
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  topic:
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    uri: http://edamontology.org/topic_0625
  - term: DNA polymorphism
    uri: http://edamontology.org/topic_2885
  - term: Genetics
    uri: http://edamontology.org/topic_3053
  validated: 1
  version:
  - '1.07'
- accessibility: null
  additionDate: '2017-03-30T21:27:33Z'
  biotoolsCURIE: biotools:allele_frequency_net
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    fundrefid: null
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    name: Support
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    orcidid: null
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    typeEntity: Person
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    url: null
  description: The allele frequency net database is an online repository that contains
    information on the frequencies of immune genes and their corresponding alleles
    in different populations. At present, the system contains data on the frequency
    of genes from different polymorphic regions such as human leukocyte antigens,
    killer-cell immunoglobulin-like receptors, major histocompatibility complex Class
    I chain-related genes and a number of cytokine gene polymorphisms.
  documentation: []
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    operation:
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      uri: http://edamontology.org/operation_3221
    - term: Haplotype mapping
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    - term: Genotyping
      uri: http://edamontology.org/operation_3196
    - term: Phylogenetic tree generation (from gene frequencies)
      uri: http://edamontology.org/operation_0542
    - term: Variant calling
      uri: http://edamontology.org/operation_3227
    output: []
  homepage: http://www.allelefrequencies.net
  homepage_status: 0
  language:
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  lastUpdate: '2024-11-24T20:36:45.470688Z'
  license: null
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  name: Allele frequency net
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  publication:
  - doi: 10.1093/nar/gkq1128
    metadata:
      abstract: The allele frequency net database (http://www.allelefrequencies.net)
        is an online repository that contains information on the frequencies of immune
        genes and their corresponding alleles in different populations. The extensive
        variability observed in genes and alleles related to the immune system response
        and its significance in transplantation, disease association studies and diversity
        in populations led to the development of this electronic resource. At present,
        the system contains data from 1133 populations in 608 813 individuals on the
        frequency of genes from different polymorphic regions such as human leukocyte
        antigens, killer-cell immunoglobulin-like receptors, major histocompatibility
        complex Class I chainrelated genes and a number of cytokine gene polymorphisms.
        The project was designed to create a central source for the storage of frequency
        data and provide individuals with a set of bioinformatics tools to analyze
        the occurrence of these variants in worldwide populations. The resource has
        been used in a wide variety of contexts, including clinical applications (histocompatibility,
        immunology, epidemiology and pharmacogenetics) and population genetics. Demographic
        information, frequency data and searching tools can be freely accessed through
        the website. © The Author(s) 2010.
      authors:
      - name: Gonzalez-Galarza F.F.
      - name: Christmas S.
      - name: Middleton D.
      - name: Jones A.R.
      citationCount: 618
      date: '2011-01-01T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'Allele frequency net: A database and online repository for immune gene
        frequencies in worldwide populations'
    note: null
    pmcid: PMC3013710
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  toolType:
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  - term: Population genetics
    uri: http://edamontology.org/topic_3056
  - term: Public health and epidemiology
    uri: http://edamontology.org/topic_3305
  - term: Pharmacogenomics
    uri: http://edamontology.org/topic_0208
  validated: 1
  version: []
- accessibility: null
  additionDate: '2017-12-18T00:03:31Z'
  biotoolsCURIE: biotools:alohomora
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  description: Alohomora was designed to facilitate genome-wide linkage studies performed
    with high-density single nucleotide polymorphism (SNP) marker panels such as the
    Affymetrix GeneChip(R) Human Mapping 10K Array
  documentation:
  - note: null
    type:
    - General
    url: https://gmc.mdc-berlin.de/alohomora/
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    input: []
    note: null
    operation:
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      uri: http://edamontology.org/operation_2429
    output: []
  - cmd: null
    input: []
    note: null
    operation:
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      uri: http://edamontology.org/operation_0283
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  homepage: http://gmc.mdc-berlin.de/alohomora/
  homepage_status: 0
  language:
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  lastUpdate: '2024-11-24T20:36:43.983149Z'
  license: null
  link:
  - note: null
    type:
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    url: http://www.mybiosoftware.com/alohomora-0-33-linkage-analysis-tools-affymetrix-mapping.html
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  name: Alohomora
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  publication:
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    metadata:
      abstract: 'Summary: ALOHOMORA is a software tool designed to facilitate genome-wide
        linkage studies performed with high-density single nucleotide polymorphism
        (SNP) marker panels such as the Affymetrix GeneChip® Human Mapping 10K Array.
        Genotype data are converted into appropriate formats for a number of common
        linkage programs and subjected to standard quality control routines before
        linkage runs are started. ALOHOMORA is written in Perl and may be used to
        perform state-of-the-art linkage scans in small and large families with any
        genetic model. Options for using different genetic maps or ethnicity-specific
        allele frequencies are implemented. Graphic outputs of whole-genome multipoint
        LOD score values are provided for the entire dataset as well as for individual
        families. © The Author 2005. Published by Oxford University Press. All rights
        reserved.'
      authors:
      - name: Ruschendorf F.
      - name: Nurnberg P.
      citationCount: 155
      date: '2005-05-01T00:00:00Z'
      journal: Bioinformatics
      title: 'ALOHOMORA: A tool for linkage analyisi using 10K SNP array data'
    note: null
    pmcid: null
    pmid: '15647291'
    type:
    - Primary
    version: null
  relation: []
  toolType:
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  topic:
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    uri: http://edamontology.org/topic_2885
  - term: Mapping
    uri: http://edamontology.org/topic_0102
  - term: Studies
    uri: http://edamontology.org/topic_3678
  - term: SNP
    uri: http://edamontology.org/topic_2885
  - term: Genetics
    uri: http://edamontology.org/topic_3053
  - term: Linkage
    uri: http://edamontology.org/topic_0102
  - term: Polymorphism
    uri: http://edamontology.org/topic_0199
  validated: 1
  version:
  - '0.33'
- accessibility: null
  additionDate: '2017-01-13T13:13:31Z'
  biotoolsCURIE: biotools:alta-cyclic
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  credit:
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    fundrefid: null
    gridid: null
    name: Yaniv Erlich
    note: null
    orcidid: null
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    typeEntity: Person
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    url: null
  description: Alta-Cyclic is a Illumina Genome-Analyzer (Solexa) base caller.
  documentation:
  - note: null
    type:
    - General
    url: http://hannonlab.cshl.edu/Alta-Cyclic/usage.html
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    input: []
    note: null
    operation:
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  homepage: http://hannonlab.cshl.edu/Alta-Cyclic/main.html
  homepage_status: 0
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  license: null
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  maturity: Legacy
  name: Alta-Cyclic
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  owner: seqwiki_import
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    metadata:
      abstract: Next-generation sequencing is limited to short read lengths and by
        high error rates. We systematically analyzed sources of noise in the Illumina
        Genome Analyzer that contribute to these high error rates and developed a
        base caller, Alta-Cyclic, that uses machine learning to compensate for noise
        factors. Alta-Cyclic substantially improved the number of accurate reads for
        sequencing runs up to 78 bases and reduced systematic biases, facilitating
        confident identification of sequence variants.
      authors:
      - name: Erlich Y.
      - name: Mitra P.P.
      - name: delaBastide M.
      - name: McCombie W.R.
      - name: Hannon G.J.
      citationCount: 156
      date: '2008-08-01T00:00:00Z'
      journal: Nature Methods
      title: 'Alta-Cyclic: A self-optimizing base caller for next-generation sequencing'
    note: null
    pmcid: PMC2978646
    pmid: '18604217'
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    version: null
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  validated: 1
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  additionDate: '2017-03-30T21:27:46Z'
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    fundrefid: null
    gridid: null
    name: Steffen Heber
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
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    url: null
  - email: leipzig@med.upenn.edu
    fundrefid: null
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    name: Jeremy Leipzig
    note: null
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  description: The Alternative Splicing Gallery (ASG) takes an identifier such as
    an EnsEMBL gene ID or a RefSeq ID as input, and provides a graph mapping splice
    events to transcript information. The user can also view GO information for the
    record, and select one or more exons and download the resulting sequence. ASG
    also links out to other alternative splicing databases like ProSplicer.
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    - term: Splice site prediction
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    - term: Splicing model analysis
      uri: http://edamontology.org/operation_2499
    - term: Sequence merging
      uri: http://edamontology.org/operation_0232
    - term: EST assembly
      uri: http://edamontology.org/operation_0526
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  homepage: http://statgen.ncsu.edu/asg/
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  - type: rrid
    value: RRID:SCR_008129
    version: null
  owner: ELIXIR-EE
  publication:
  - doi: 10.1093/nar/gkh731
    metadata:
      abstract: Alternative splicing essentially increases the diversity of the transcriptome
        and has important implications for physiology, development and the genesis
        of diseases. Conventionally, alternative splicing is investigated in a case-by-case
        fashion, but this becomes cumbersome and error prone if genes show a huge
        abundance of different splice variants. We use a different approach and integrate
        all transcripts derived from a gene into a single splicing graph. Each transcript
        corresponds to a path in the graph, and alternative splicing is displayed
        by bifurcations. This representation preserves the relationships between different
        splicing variants and allows us to investigate systematically all possible
        putative transcripts. We built a database of splicing graphs for human genes,
        using transcript information from various major sources (Ensembl, RefSeq,
        STACK, TIGR and UniGene). A Web interface allows users to display the splicing
        graphs, to interactively assemble transcripts and to access their sequences
        as well as neighboring genomic regions. We also provide for each gene an exhaustive
        pre-computed catalog of putative transcripts - in total more than 1.2 million
        sequences. We found that ∼65% of the investigated genes show evidence for
        alternative splicing, and in 5% of the cases, a single gene might produce
        over 100 transcripts. © Oxford University Press 2004; all rights reserved.
      authors:
      - name: Leipzig J.
      - name: Pevzner P.
      - name: Heber S.
      citationCount: 72
      date: '2004-09-21T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'The Alternative Splicing Gallery (ASG): Bridging the gap between genome
        and transcriptome'
    note: null
    pmcid: PMC506815
    pmid: '15292448'
    type: []
    version: null
  relation: []
  toolType:
  - Database portal
  topic:
  - term: RNA splicing
    uri: http://edamontology.org/topic_3320
  - term: Gene transcripts
    uri: http://edamontology.org/topic_3512
  - term: Gene expression
    uri: http://edamontology.org/topic_0203
  - term: Mapping
    uri: http://edamontology.org/topic_0102
  - term: Protein variants
    uri: http://edamontology.org/topic_3120
  validated: 1
  version: []
- accessibility: null
  additionDate: '2017-12-18T00:03:15Z'
  biotoolsCURIE: biotools:andes
  biotoolsID: andes
  collectionID: []
  confidence_flag: null
  cost: null
  credit:
  - email: null
    fundrefid: null
    gridid: null
    name: null
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: http://www.jcvi.org/
  description: The fundamental data structure underlying, is the position profile,
    which contains the nucleotide distributions for each genomic position resultant
    from a multiple sequence alignment. They include the root mean square deviation
    plot and the computation of base conversion frequencies, variation, inter-sample
    clustering and visualization, threshold-driven consensus sequence generation and
    polymorphism detection, and the estimation of empirically determined sequencing
    quality values.
  documentation:
  - note: null
    type:
    - User manual
    url: http://andestools.sourceforge.net/OnlineManual.htm
  download: []
  editPermission:
    authors: []
    type: private
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  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Polymorphism detection
      uri: http://edamontology.org/operation_3202
    output: []
  - cmd: null
    input: []
    note: null
    operation:
    - term: Conversion
      uri: http://edamontology.org/operation_3434
    output: []
  - cmd: null
    input: []
    note: null
    operation:
    - term: Multiple sequence alignment
      uri: http://edamontology.org/operation_0492
    output: []
  - cmd: null
    input: []
    note: null
    operation:
    - term: Comparison
      uri: http://edamontology.org/operation_2424
    output: []
  - cmd: null
    input: []
    note: null
    operation:
    - term: Sequence generation
      uri: http://edamontology.org/operation_0230
    output: []
  - cmd: null
    input: []
    note: null
    operation:
    - term: Generation
      uri: http://edamontology.org/operation_3429
    output: []
  - cmd: null
    input: []
    note: null
    operation:
    - term: Sequence alignment
      uri: http://edamontology.org/operation_0292
    output: []
  - cmd: null
    input: []
    note: null
    operation:
    - term: Prediction and recognition
      uri: http://edamontology.org/operation_2423
    output: []
  - cmd: null
    input: []
    note: null
    operation:
    - term: Clustering
      uri: http://edamontology.org/operation_3432
    output: []
  homepage: http://andestools.sourceforge.net/
  homepage_status: 0
  language:
  - R
  - Perl
  lastUpdate: '2024-11-24T20:36:40.094706Z'
  license: null
  link:
  - note: null
    type:
    - Software catalogue
    url: http://www.mybiosoftware.com/andes-20100709-analysis-deep-sequencing.html
  maturity: null
  name: ANDES
  operatingSystem:
  - Linux
  otherID:
  - type: rrid
    value: RRID:SCR_002791
    version: null
  owner: mbs_import
  publication:
  - doi: 10.1186/1756-0500-3-199
    metadata:
      abstract: 'Background: The advancements in DNA sequencing technologies have
        allowed researchers to progress from the analyses of a single organism towards
        the deep sequencing of a sample of organisms. With sufficient sequencing depth,
        it is now possible to detect subtle variations between members of the same
        species, or between mixed species with shared biomarkers, such as the 16S
        rRNA gene. However, traditional sequencing analyses of samples from largely
        homogeneous populations are often still based on multiple sequence alignments
        (MSA), where each sequence is placed along a separate row and similarities
        between aligned bases can be followed down each column. While this visual
        format is intuitive for a small set of aligned sequences, the representation
        quickly becomes cumbersome as sequencing depths cover loci hundreds or thousands
        of reads deep. Findings: We have developed ANDES, a software library and a
        suite of applications, written in Perl and R, for the statistical ANalyses
        of DEep Sequencing. The fundamental data structure underlying ANDES is the
        position profile, which contains the nucleotide distributions for each genomic
        position resultant from a multiple sequence alignment (MSA). Tools include
        the root mean square deviation (RMSD) plot, which allows for the visual comparison
        of multiple samples on a position-by-position basis, and the computation of
        base conversion frequencies (transition/transversion rates), variation (Shannon
        entropy), inter-sample clustering and visualization (dendrogram and multidimensional
        scaling (MDS) plot), threshold-driven consensus sequence generation and polymorphism
        detection, and the estimation of empirically determined sequencing quality
        values. Conclusions: As new sequencing technologies evolve, deep sequencing
        will become increasingly cost-efficient and the inter and intra-sample comparisons
        of largely homogeneous sequences will become more common. We have provided
        a software package and demonstrated its application on various empirically-derived
        datasets. Investigators may download the software from Sourceforge at https://sourceforge.net/projects/andestools.
        © 2010 Li et al; licensee BioMed Central Ltd.'
      authors:
      - name: Li K.
      - name: Venter E.
      - name: Yooseph S.
      - name: Stockwell T.B.
      - name: Eckerle L.D.
      - name: Denison M.R.
      - name: Spiro D.J.
      - name: Methe B.A.
      citationCount: 20
      date: '2010-08-27T00:00:00Z'
      journal: BMC Research Notes
      title: 'ANDES: Statistical tools for the analyses of deep sequencing'
    note: null
    pmcid: PMC2921379
    pmid: '20633290'
    type:
    - Primary
    version: null
  relation: []
  toolType:
  - Command-line tool
  topic:
  - term: Sequencing
    uri: http://edamontology.org/topic_3168
  - term: Genetic variation
    uri: http://edamontology.org/topic_0199
  - term: DNA
    uri: http://edamontology.org/topic_0654
  - term: Sample collections
    uri: http://edamontology.org/topic_3277
  validated: 1
  version:
  - '20120225'
- accessibility: null
  additionDate: '2017-08-03T19:04:59Z'
  biotoolsCURIE: biotools:aroma.affymetrix
  biotoolsID: aroma.affymetrix
  collectionID: []
  confidence_flag: null
  cost: null
  credit:
  - email: null
    fundrefid: null
    gridid: null
    name: null
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: http://aroma-project.org/about
  description: R package for analyzing large Affymetrix data sets which allows to
    analyze 100-1,000s of arrays of various chip types, e.g. expression arrays, SNP
    chips, exon arrays and so on.
  documentation:
  - note: null
    type:
    - General
    url: http://aroma-project.org/docs/
  download: []
  editPermission:
    authors: []
    type: private
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Expression data rendering
      uri: http://edamontology.org/operation_0571
    - term: Gene expression analysis
      uri: http://edamontology.org/operation_2495
    output: []
  homepage: http://aroma-project.org/
  homepage_status: 0
  language:
  - R
  lastUpdate: '2024-11-24T20:36:38.680706Z'
  license: null
  link:
  - note: null
    type:
    - Software catalogue
    url: http://www.mybiosoftware.com/aroma-affymetrix-v2-10-0-open-source-framework-microarray-analysis.html
  maturity: null
  name: aroma.affymetrix
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID:
  - type: rrid
    value: RRID:SCR_010919
    version: null
  owner: mbs_import
  publication:
  - doi: 10.1093/bioinformatics/btq300
    metadata:
      abstract: 'Motivation: Current algorithms for estimating DNA copy numbers (CNs)
        borrow concepts from gene expression analysis methods. However, single nucleotide
        polymorphism (SNP) arrays have special characteristics that, if taken into
        account, can improve the overall performance. For example, cross hybridization
        between alleles occurs in SNP probe pairs. In addition, most of the current
        CN methods are focused on total CNs, while it has been shown that allele-specific
        CNs are of paramount importance for some studies. Therefore, we have developed
        a summarization method that estimates high-quality allele-specific CNs. Results:
        The proposed method estimates the allele-specific DNA CNs for all Affymetrix
        SNP arrays dealing directly with the cross hybridization between probes within
        SNP probesets. This algorithm outperforms (or at least it performs as well
        as) other state-of-the-art algorithms for computing DNA CNs. It better discerns
        an aberration from a normal state and it also gives more precise allele-specific
        CNs. © The Author 2010. Published by Oxford University Press. All rights reserved.'
      authors:
      - name: Ortiz-Estevez M.
      - name: Bengtsson H.
      - name: Rubio A.
      citationCount: 17
      date: '2010-06-06T00:00:00Z'
      journal: Bioinformatics
      title: 'ACNE: A summarization method to estimate allele-specific copy numbers
        for Affymetrix SNP arrays'
    note: null
    pmcid: PMC2913655
    pmid: '20529889'
    type: []
    version: null
  relation: []
  toolType:
  - Script
  topic:
  - term: ChIP-seq
    uri: http://edamontology.org/topic_3169
  - term: DNA polymorphism
    uri: http://edamontology.org/topic_2885
  - term: Population genetics
    uri: http://edamontology.org/topic_3056
  validated: 1
  version: []
- accessibility: null
  additionDate: '2017-03-24T09:34:10Z'
  biotoolsCURIE: biotools:arraypipe
  biotoolsID: arraypipe
  collectionID: []
  confidence_flag: null
  cost: null
  credit:
  - email: karsten.hokamp@tcd.ie
    fundrefid: null
    gridid: null
    name: Karsten Hokamp
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  description: ArrayPipe allows users to customize a processing pipeline for the analysis
    of microarray data. Includes methods for quality assessment of slides, data visualization,
    normalization, and detection of differentially expressed genes.  Output consists
    of reports formatted as standard web pages and tab-delimited lists of calculated
    values.
  documentation:
  - note: null
    type:
    - General
    url: http://www.pathogenomics.ca/arraypipe/info/
  download: []
  editPermission:
    authors: []
    type: private
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Data handling
      uri: http://edamontology.org/operation_2409
    - term: Differential gene expression analysis
      uri: http://edamontology.org/operation_3223
    - term: Gene expression profiling
      uri: http://edamontology.org/operation_0314
    - term: Gene expression analysis
      uri: http://edamontology.org/operation_2495
    output: []
  homepage: http://koch.pathogenomics.ca/cgi-bin/pub/arraypipe.pl
  homepage_status: 0
  language: []
  lastUpdate: '2024-11-24T20:36:37.459362Z'
  license: null
  link: []
  maturity: null
  name: ArrayPipe
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID:
  - type: rrid
    value: RRID:SCR_010934
    version: null
  owner: ELIXIR-EE
  publication:
  - doi: 10.1093/nar/gkh446
    metadata:
      abstract: A number of microarray analysis software packages exist already; however,
        none combines the user-friendly features of a web-based interface with potential
        ability to analyse multiple arrays at once using flexible analysis steps.
        The ArrayPipe web server (freely available at www.pathogenomics.ca/arraypipe)
        allows the automated application of complex analyses to microarray data which
        can range from single slides to large data sets including replicates and dye-swaps.
        It handles output from most commonly used quantification software packages
        for dual-labelled arrays. Application features range from quality assessment
        of slides through various data visualizations to multi-step analyses including
        normalization, detection of differentially expressed genes, and comparison
        and highlighting of gene lists. A highly customizable action set-up facilitates
        unrestricted arrangement of functions, which can be stored as action profiles.
        A unique combination of web-based and command-line functionality enables comfortable
        configuration of processes that can be repeatedly applied to large data sets
        in high throughput. The output consists of reports formatted as standard web
        pages and tab-delimited lists of calculated values that can be inserted into
        other analysis programs. Additional features, such as web-based spreadsheet
        functionality, auto-parallelization and password protection make this a powerful
        tool in microarray research for individuals and large groups alike. © Oxford
        University Press 2004; all rights reserved.
      authors:
      - name: Hokamp K.
      - name: Roche F.M.
      - name: Acab M.
      - name: Rousseau M.-E.
      - name: Kuo B.
      - name: Goode D.
      - name: Aeschliman D.
      - name: Bryan J.
      - name: Babiuk L.A.
      - name: Hancock R.E.W.
      - name: Brinkman F.S.L.
      citationCount: 66
      date: '2004-07-01T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'ArrayPipe: A flexible processing pipeline for microarray data'
    note: null
    pmcid: PMC441584
    pmid: '15215429'
    type: []
    version: null
  relation: []
  toolType:
  - Web application
  topic:
  - term: Microarray experiment
    uri: http://edamontology.org/topic_3518
  - term: Gene expression
    uri: http://edamontology.org/topic_0203
  - term: Workflows
    uri: http://edamontology.org/topic_0769
  - term: Data architecture, analysis and design
    uri: http://edamontology.org/topic_3365
  - term: ChIP-on-chip
    uri: http://edamontology.org/topic_3179
  validated: 1
  version: []
- accessibility: null
  additionDate: '2017-08-03T18:35:58Z'
  biotoolsCURIE: biotools:aspex
  biotoolsID: aspex
  collectionID: []
  confidence_flag: null
  cost: null
  credit:
  - email: dahinds@users.sourceforge.net
    fundrefid: null
    gridid: null
    name: David Hinds
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  description: 'ASPEX is a set of programs for performing multipoint exclusion mapping
    of affected sibling pair data for discrete traits.There are five main analysis
    programs: sib_ibd, sib_phase, sib_map, sib_tdt, and sib_kin.'
  documentation:
  - note: null
    type:
    - User manual
    url: http://aspex.sourceforge.net/usage.pdf
  download: []
  editPermission:
    authors: []
    type: private
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Mapping
      uri: http://edamontology.org/operation_2429
    output: []
  homepage: http://aspex.sourceforge.net/
  homepage_status: 0
  language:
  - Perl
  lastUpdate: '2024-11-24T20:36:36.096556Z'
  license: null
  link:
  - note: null
    type:
    - Software catalogue
    url: http://www.mybiosoftware.com/aspex-2-5-affected-sib-pair-exclusion-mapping.html
  maturity: null
  name: ASPEX
  operatingSystem:
  - Linux
  otherID:
  - type: rrid
    value: RRID:SCR_008414
    version: null
  owner: mbs_import
  publication:
  - doi: 10.1002/gepi.1370170732
    metadata:
      abstract: Nonparametric sib-pair analysis was performed on the Collaborative
        Study on the Genetics of Alcoholism data set. Concordant and discordant pair
        groups were examined using the ASPEX package of programs. Allele sharing and
        multipoint lod scores for six comparison groups were obtained. Sharing and
        lod score patterns were not consistent with a simple genetic interpretation.
      authors:
      - name: Jorgenson E.
      - name: Hinds D.
      - name: Risch N.
      citationCount: 2
      date: '1999-01-01T00:00:00Z'
      journal: Genetic Epidemiology
      title: Sib-pair analysis of the Collaborative Study on the Genetics of Alcoholism
        data set
    note: null
    pmcid: null
    pmid: '10597434'
    type: []
    version: null
  relation: []
  toolType:
  - Command-line tool
  topic:
  - term: Mapping
    uri: http://edamontology.org/topic_0102
  - term: Genetics
    uri: http://edamontology.org/topic_3053
  validated: 1
  version: []
- accessibility: null
  additionDate: '2017-12-06T18:14:07Z'
  biotoolsCURIE: biotools:association_viewer
  biotoolsID: association_viewer
  collectionID: []
  confidence_flag: null
  cost: null
  credit:
  - email: null
    fundrefid: null
    gridid: null
    name: Olivier Martin
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: https://sourceforge.net/u/voltigeur/profile/
  description: AssociationViewer is a Java application used to display SNPs in a genetic
    context. Supplementary data (such as genes or LD plots) is downloaded from various
    public data sources on the fly and saved locally in a cache. Custom data can be
    added as supplementary tracks.
  documentation:
  - note: null
    type:
    - General
    url: http://associationviewer.vital-it.ch/usage.php
  download: []
  editPermission:
    authors: []
    type: private
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Annotation
      uri: http://edamontology.org/operation_0226
    output: []
  homepage: http://associationviewer.vital-it.ch/
  homepage_status: 0
  language:
  - Java
  lastUpdate: '2024-11-24T20:36:34.942698Z'
  license: null
  link: []
  maturity: null
  name: Association Viewer
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID:
  - type: rrid
    value: RRID:SCR_009063
    version: null
  owner: admin
  publication:
  - doi: 10.1093/bioinformatics/btp017
    metadata:
      abstract: 'We present a tool designed for visualization of large-scale genetic
        and genomic data exemplified by results from genome-wide association studies.
        This software provides an integrated framework to facilitate the interpretation
        of SNP association studies in genomic context. Gene annotations can be retrieved
        from Ensembl, linkage disequilibrium data downloaded from HapMap and custom
        data imported in BED or WIG format. AssociationViewer integrates functionalities
        that enable the aggregation or intersection of data tracks. It implements
        an efficient cache system and allows the display of several, very large-scale
        genomic datasets. Availability: The Java code for AssociationViewer is distributed
        under the GNU General Public Licence and has been tested on Microsoft Windows
        XP, MacOSX and GNU/Linux operating systems. It is available from the SourceForge
        repository. This also includes Java webstart, documentation and example datafiles.
        © 2009 The Author(s).'
      authors:
      - name: Martin O.
      - name: Valsesia A.
      - name: Telenti A.
      - name: Xenarios I.
      - name: Stevenson B.J.
      citationCount: 1
      date: '2009-03-01T00:00:00Z'
      journal: Bioinformatics
      title: 'AssociationViewer: A scalable and integrated software tool for visualization
        of large-scale variation data in genomic context'
    note: null
    pmcid: PMC2647839
    pmid: '19168913'
    type:
    - Primary
    version: null
  relation: []
  toolType:
  - Web application
  topic:
  - term: Genomics
    uri: http://edamontology.org/topic_0622
  validated: 1
  version: []
- accessibility: null
  additionDate: '2015-01-21T13:56:26Z'
  biotoolsCURIE: biotools:astd
  biotoolsID: astd
  collectionID:
  - DRCAT
  confidence_flag: null
  cost: null
  credit:
  - email: null
    fundrefid: null
    gridid: null
    name: DRCAT
    note: null
    orcidid: null
    rorid: null
    typeEntity: Project
    typeRole:
    - Documentor
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Contact List
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: http://www.ensembl.org/info/about/contact/index.html
  description: 'AltSplice and AltExtron provide information on alternative intron/exons,
    alternative splice events, and isoform splice patterns. AEdb contains: AEdb-Sequence
    (sequence and properties of alternatively splice exons), AEdb-Function (data on
    functional aspects of alternative splicing), AEdb-motif (data and sequence of
    known splice regulatory motifs), and AEdb-minigene (a collection of known minigene
    constructs for alternative splice events).'
  documentation:
  - note: null
    type:
    - General
    url: https://www.ebi.ac.uk/asd
  download: []
  editPermission:
    authors: []
    type: private
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Ensembl gene ID
        uri: http://edamontology.org/data_1033
      format: []
    note: null
    operation:
    - term: Query and retrieval
      uri: http://edamontology.org/operation_0224
    output:
    - data:
        term: Gene report
        uri: http://edamontology.org/data_0916
      format:
      - term: HTML
        uri: http://edamontology.org/format_2331
  - cmd: null
    input:
    - data:
        term: Ensembl gene ID
        uri: http://edamontology.org/data_1033
      format: []
    note: null
    operation:
    - term: Query and retrieval
      uri: http://edamontology.org/operation_0224
    output:
    - data:
        term: Gene report
        uri: http://edamontology.org/data_0916
      format:
      - term: EMBL format
        uri: http://edamontology.org/format_1927
  - cmd: null
    input:
    - data:
        term: Ensembl gene ID
        uri: http://edamontology.org/data_1033
      format: []
    note: null
    operation:
    - term: Query and retrieval
      uri: http://edamontology.org/operation_0224
    output:
    - data:
        term: Gene report
        uri: http://edamontology.org/data_0916
      format:
      - term: FASTA
        uri: http://edamontology.org/format_1929
  - cmd: null
    input:
    - data:
        term: Ensembl gene ID
        uri: http://edamontology.org/data_1033
      format: []
    note: null
    operation:
    - term: Query and retrieval
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    metadata:
      abstract: 'New technologies are revolutionising biological research and its
        applications by making it easier and cheaper to generate ever-greater volumes
        and types of data. In response, the services and infrastructure of the European
        Bioinformatics Institute (EMBL-EBI, www.ebi.ac.UK) are continually expanding:
        total disk capacity increases significantly every year to keep pace with demand
        (75 petabytes as of December 2015), and interoperability between resources
        remains a strategic priority. Since 2014 we have launched two new resources:
        the European Variation Archive for genetic variation data and EMPIAR for two-dimensional
        electron microscopy data, as well as a Resource Description Framework platform.
        We also launched the Embassy Cloud service, which allows users to run large
        analyses in a virtual environment next to EMBL-EBI''s vast public data resources.'
      authors:
      - name: Cook C.E.
      - name: Bergman M.T.
      - name: Finn R.D.
      - name: Cochrane G.
      - name: Birney E.
      - name: Apweiler R.
      citationCount: 98
      date: '2016-01-01T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'The European Bioinformatics Institute in 2016: Data growth and integration'
    note: null
    pmcid: PMC4702932
    pmid: '26673705'
    type:
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  relation: []
  toolType:
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  topic:
  - term: Gene structure
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  validated: 1
  version: []
- accessibility: null
  additionDate: '2017-03-24T11:31:28Z'
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    fundrefid: null
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    note: null
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    typeEntity: Person
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    url: null
  description: AthaMap is a genome-wide map of putative transcription factor binding
    sites in Arabidopsis thaliana
  documentation:
  - note: null
    type:
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    - term: Transcriptional regulatory element prediction
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    metadata: null
    note: null
    pmcid: PMC308752
    pmid: '14681436'
    type: []
    version: null
  - doi: 10.1093/nar/gki395
    metadata:
      abstract: The AthaMap database generates a map of cis-regulatory elements for
        the Arabidopsis thaliana genome. AthaMap contains more than 7.4 × 106 putative
        binding sites for 36 transcription factors (TFs) from 16 different TF families.
        A newly implemented functionality allows the display of subsets of higher
        conserved transcription factor binding sites (TFBSs). Furthermore, a web tool
        was developed that permits a user-defined search for co-localizing cis-regulatory
        elements. The user can specify individually the level of conservation for
        each TFBS and a spacer range between them. This web tool was employed for
        the identification of co-localizing sites of known interacting TFs and TFs
        containing two DNA-binding domains. More than 1.8 × 105 combinatorial elements
        were annotated in the AthaMap database. These elements can also be used to
        identify more complex co-localizing elements consisting of up to four TFBSs.
        The AthaMap database and the connected web tools are a valuable resource for
        the analysis and the prediction of gene expression regulation at http://www.athamap.de.
        © 2005 Oxford University Press.
      authors:
      - name: Steffens N.O.
      - name: Galuschka C.
      - name: Schindler M.
      - name: Bulow L.
      - name: Hehl R.
      citationCount: 37
      date: '2005-07-01T00:00:00Z'
      journal: Nucleic Acids Research
      title: AthaMap web tools for database-assisted identification of combinatorial
        cis-regulatory elements and the display of highly conserved transcription
        factor binding sites in Arabidopsis thaliana
    note: null
    pmcid: PMC1160156
    pmid: '15980498'
    type: []
    version: null
  - doi: 10.1093/nar/gkl1006
    metadata:
      abstract: The AthaMap database generates a map of cis-regulatory elements for
        the whole Arabidopsis thaliana genome. This database has been extended by
        new tools to identify common cis-regulatory elements in specific regions of
        user-provided gene sets. A resulting table displays all cis-regulatory elements
        annotated in AthaMap including positional information relative to the respective
        gene. Further tables show overviews with the number of individual transcription
        factor binding sites (TFBS) present and TFBS common to the whole set of genes.
        Over represented cis-elements are easily identified. These features were used
        to detect specific enrichment of drought-responsive elements in cold-induced
        genes. For identification of co-regulated genes, the output table of the colocalization
        function was extended to show the closest genes and their relative distances
        to the colocalizing TFBS. Gene sets determined by this function can be used
        for a co-regulation analysis in microarray gene expression databases such
        as Genevestigator or PathoPlant. Additional improvements of AthaMap include
        display of the gene structure in the sequence window and a significant data
        increase. AthaMap is freely available at http://www.athamap.de/. © 2007 Oxford
        University Press.
      authors:
      - name: Galuschka C.
      - name: Schindler M.
      - name: Bulow L.
      - name: Hehl R.
      citationCount: 41
      date: '2007-01-01T00:00:00Z'
      journal: Nucleic Acids Research
      title: AthaMap web tools for the analysis and identification of co-regulated
        genes
    note: null
    pmcid: PMC1761422
    pmid: '17148485'
    type: []
    version: null
  - doi: 10.1093/nar/gkn709
    metadata:
      abstract: The AthaMap database generates a map of predicted transcription factor
        binding sites (TFBS) for the whole Arabidopsis thaliana genome. AthaMap has
        now been extended to include data on post-transcriptional regulation. A total
        of 403 173 genomic positions of small RNAs have been mapped in the A. thaliana
        genome. These identify 5772 putative post-transcriptionally regulated target
        genes. AthaMap tools have been modified to improve the identification of common
        TFBS in co-regulated genes by subtracting post-transcriptionally regulated
        genes from such analyses. Furthermore, AthaMap was updated to the TAIR7 genome
        annotation, a graphic display of gene analysis results was implemented, and
        the TFBS data content was increased. AthaMap is freely available at http://www.athamap.de/.
        © 2008 The Author(s).
      authors:
      - name: Bulow L.
      - name: Engelmann S.
      - name: Schindler M.
      - name: Hehl R.
      citationCount: 44
      date: '2009-01-09T00:00:00Z'
      journal: Nucleic Acids Research
      title: AthaMap, integrating transcriptional and post-transcriptional data
    note: null
    pmcid: PMC2686474
    pmid: '18842622'
    type: []
    version: null
  - doi: 10.1093/database/baq034
    metadata:
      abstract: 'The AthaMap database generates a map of potential transcription factor
        binding sites (TFBS) and small RNA target sites in the Arabidopsis thaliana
        genome. The database contains sites for 115 different transcription factors
        (TFs). TFBS were identified with positional weight matrices (PWMs) or with
        single binding sites. With the new web tool ''Gene Identification'', it is
        possible to identify potential target genes for selected TFs. For these analyses,
        the user can define a region of interest of up to 6000bp in all annotated
        genes. For TFBS determined with PWMs, the search can be restricted to high-quality
        TFBS. The results are displayed in tables that identify the gene, position
        of the TFBS and, if applicable, individual score of the TFBS. In addition,
        data files can be downloaded that harbour positional information of TFBS of
        all TFs in a region between -2000 and +2000bp relative to the transcription
        or translation start site. Also, data content of AthaMap was increased and
        the database was updated to the TAIR8 genome release. Database URL: http://www.athamap.de/gene_ident.php.'
      authors:
      - name: Bulow L.
      - name: Brill Y.
      - name: Hehl R.
      citationCount: 26
      date: '2010-01-01T00:00:00Z'
      journal: 'Database : the journal of biological databases and curation'
      title: AthaMap-assisted transcription factor target gene identification in Arabidopsis
        thaliana.
    note: null
    pmcid: PMC3011983
    pmid: '21177332'
    type: []
    version: null
  relation: []
  toolType:
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  topic:
  - term: Transcription factors and regulatory sites
    uri: http://edamontology.org/topic_0749
  - term: Gene expression
    uri: http://edamontology.org/topic_0203
  - term: Mapping
    uri: http://edamontology.org/topic_0102
  - term: Gene transcripts
    uri: http://edamontology.org/topic_3512
  - term: DNA binding sites
    uri: http://edamontology.org/topic_3125
  validated: 1
  version: []
- accessibility: null
  additionDate: '2017-08-03T18:36:33Z'
  biotoolsCURIE: biotools:autoassemblyd
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    url: http://sourceforge.net/projects/autoassemblyd/
  description: A software which performed the local and remote genome assembly by
    several assemblers based on an XML Template which can replace the large command
    lines required by most assemblers.
  documentation:
  - note: null
    type:
    - User manual
    url: https://sourceforge.net/projects/autoassemblyd/files/release/version_0.1/AutoAssemblyD_USER%20GUIDE.pdf/download
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    metadata: null
    note: null
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    type: []
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  topic:
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  - term: Sequence analysis
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  - term: Genomics
    uri: http://edamontology.org/topic_0622
  validated: 1
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  additionDate: '2017-12-18T00:03:47Z'
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    url: http://blog.cryos.net/
  description: Avogadro is an advanced molecule editor and visualizer designed for
    cross-platform use in computational chemistry, molecular modeling, bioinformatics,
    materials science, and related areas. It offers flexible high quality rendering
    and a powerful plugin architecture.
  documentation:
  - note: null
    type:
    - User manual
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  lastUpdate: '2024-11-24T20:36:22.622810Z'
  license: null
  link:
  - note: null
    type:
    - Software catalogue
    url: http://www.mybiosoftware.com/avogadro-1-0-3-molecule-editor-visualizer.html
  maturity: null
  name: Avogadro
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  publication:
  - doi: 10.1186/1758-2946-4-17
    metadata:
      abstract: 'Background: The Avogadro project has developed an advanced molecule
        editor and visualizer designed for cross-platform use in computational chemistry,
        molecular modeling, bioinformatics, materials science, and related areas.
        It offers flexible, high quality rendering, and a powerful plugin architecture.
        Typical uses include building molecular structures, formatting input files,
        and analyzing output of a wide variety of computational chemistry packages.
        By using the CML file format as its native document type, Avogadro seeks to
        enhance the semantic accessibility of chemical data types. Results: The work
        presented here details the Avogadro library, which is a framework providing
        a code library and application programming interface (API) with three-dimensional
        visualization capabilities; and has direct applications to research and education
        in the fields of chemistry, physics, materials science, and biology. The Avogadro
        application provides a rich graphical interface using dynamically loaded plugins
        through the library itself. The application and library can each be extended
        by implementing a plugin module in C++ or Python to explore different visualization
        techniques, build/manipulate molecular structures, and interact with other
        programs. We describe some example extensions, one which uses a genetic algorithm
        to find stable crystal structures, and one which interfaces with the PackMol
        program to create packed, solvated structures for molecular dynamics simulations.
        The 1.0 release series of Avogadro is the main focus of the results discussed
        here. Conclusions: Avogadro offers a semantic chemical builder and platform
        for visualization and analysis. For users, it offers an easy-to-use builder,
        integrated support for downloading from common databases such as PubChem and
        the Protein Data Bank, extracting chemical data from a wide variety of formats,
        including computational chemistry output, and native, semantic support for
        the CML file format. For developers, it can be easily extended via a powerful
        plugin mechanism to support new features in organic chemistry, inorganic complexes,
        drug design, materials, biomolecules, and simulations. Avogadro is freely
        available under an open-source license from http://avogadro.openmolecules.net.'
      authors:
      - name: Hanwell M.D.
      - name: Curtis D.E.
      - name: Lonie D.C.
      - name: Vandermeerschd T.
      - name: Zurek E.
      - name: Hutchison G.R.
      citationCount: 6783
      date: '2012-08-01T00:00:00Z'
      journal: Journal of Cheminformatics
      title: 'Avogadro: An advanced semantic chemical editor, visualization, and analysis
        platform'
    note: null
    pmcid: PMC3542060
    pmid: '22889332'
    type:
    - Primary
    version: null
  relation: []
  toolType:
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  topic:
  - term: Molecular modelling
    uri: http://edamontology.org/topic_2275
  - term: Computational chemistry
    uri: http://edamontology.org/topic_3332
  - term: Chemistry
    uri: http://edamontology.org/topic_3314
  validated: 1
  version:
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- accessibility: null
  additionDate: '2017-01-13T13:13:37Z'
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    name: BamView development team
    note: null
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    typeEntity: Person
    typeRole:
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    url: null
  description: Interactive Java application for visualising the large amounts of data
    stored for sequence reads which are aligned against a reference genome sequence
  documentation:
  - note: null
    type:
    - General
    url: http://bamview.sourceforge.net
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    operation:
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      uri: http://edamontology.org/operation_0564
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  homepage: http://bamview.sourceforge.net/
  homepage_status: 0
  language:
  - Java
  lastUpdate: '2024-11-24T20:36:21.221611Z'
  license: GPL-3.0
  link: []
  maturity: null
  name: BamView
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  owner: seqwiki_import
  publication:
  - doi: 10.1093/bib/bbr073
    metadata:
      abstract: 'So-called next-generation sequencing (NGS) has provided the ability
        to sequence on a massive scale at low cost, enabling biologists to perform
        powerful experiments and gain insight into biological processes. BamView has
        been developed to visualize and analyse sequence reads from NGS platforms,
        which have been aligned to a reference sequence. It is a desktop application
        for browsing the aligned or mapped reads [Ruffalo, M, LaFramboise, T, Koyutürk,
        M. Comparative analysis of algorithms for next-generation sequencing read
        alignment. Bioinformatics 2011;27:2790-6] at different levels of magnification,
        from nucleotide level, where the base qualities can be seen, to genome or
        chromosome level where overall coverage is shown. To enable in-depth investigation
        of NGS data, various views are provided that can be configured to highlight
        interesting aspects of the data. Multiple read alignment files can be overlaid
        to compare results from different experiments, and filters can be applied
        to facilitate the interpretation of the aligned reads. As well as being a
        standalone application it can be used as an integrated part of the Artemis
        genome browser, BamView allows the user to study NGS data in the context of
        the sequence and annotation of the reference genome. Single nucleotide polymorphism
        (SNP) density and candidate SNP sites can be highlighted and investigated,
        and read-pair information can be used to discover large structural insertions
        and deletions. The application will also calculate simple analyses of the
        read mapping, including reporting the read counts and reads per kilobase per
        million mapped reads (RPKM) for genes selected by the user. Availability:
        BamView and Artemis are freely available software. These can be downloaded
        from their home pages: http://bamview.sourceforge.net/; http://www.sanger.ac.uk/resources/software/artemis/.
        Requirements: Java 1.6 or higher. © The Author 2011. Published by Oxford University
        Press.'
      authors:
      - name: Carver T.
      - name: Harris S.R.
      - name: Otto T.D.
      - name: Berriman M.
      - name: Parkhill J.
      - name: McQuillan J.A.
      citationCount: 54
      date: '2013-03-01T00:00:00Z'
      journal: Briefings in Bioinformatics
      title: 'BamView: Visualizing and interpretation of next-generation sequencing
        read alignments'
    note: null
    pmcid: PMC3603209
    pmid: '22253280'
    type:
    - Primary
    version: null
  relation: []
  toolType:
  - Desktop application
  topic:
  - term: Sequence analysis
    uri: http://edamontology.org/topic_0080
  validated: 1
  version: []
- accessibility: null
  additionDate: '2017-01-13T13:13:38Z'
  biotoolsCURIE: biotools:barracuda
  biotoolsID: barracuda
  collectionID: []
  confidence_flag: null
  cost: null
  credit:
  - email: yhbl2@cam.ac.uk
    fundrefid: null
    gridid: null
    name: Klus P.
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  description: Barracuda is a high-speed sequence aligner based on BWA and uses the
    latest Nvidia CUDA architecture for accelerating alignments of sequence reads
    generated by the next-generation sequencers.
  documentation: []
  download: []
  editPermission:
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  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Read mapping
      uri: http://edamontology.org/operation_3198
    - term: Sequence alignment
      uri: http://edamontology.org/operation_0292
    output: []
  homepage: http://seqbarracuda.sourceforge.net/
  homepage_status: 0
  language:
  - C++
  - C
  lastUpdate: '2024-11-24T20:36:20.031054Z'
  license: MIT
  link: []
  maturity: Mature
  name: BarraCUDA
  operatingSystem:
  - Linux
  otherID:
  - type: rrid
    value: RRID:SCR_006881
    version: null
  owner: seqwiki_import
  publication:
  - doi: 10.1186/1756-0500-5-27
    metadata:
      abstract: 'Background: With the maturation of next-generation DNA sequencing
        (NGS) technologies, the throughput of DNA sequencing reads has soared to over
        600 gigabases from a single instrument run. General purpose computing on graphics
        processing units (GPGPU), extracts the computing power from hundreds of parallel
        stream processors within graphics processing cores and provides a cost-effective
        and energy efficient alternative to traditional high-performance computing
        (HPC) clusters. In this article, we describe the implementation of BarraCUDA,
        a GPGPU sequence alignment software that is based on BWA, to accelerate the
        alignment of sequencing reads generated by these instruments to a reference
        DNA sequence. Findings. Using the NVIDIA Compute Unified Device Architecture
        (CUDA) software development environment, we ported the most computational-intensive
        alignment component of BWA to GPU to take advantage of the massive parallelism.
        As a result, BarraCUDA offers a magnitude of performance boost in alignment
        throughput when compared to a CPU core while delivering the same level of
        alignment fidelity. The software is also capable of supporting multiple CUDA
        devices in parallel to further accelerate the alignment throughput. Conclusions:
        BarraCUDA is designed to take advantage of the parallelism of GPU to accelerate
        the alignment of millions of sequencing reads generated by NGS instruments.
        By doing this, we could, at least in part streamline the current bioinformatics
        pipeline such that the wider scientific community could benefit from the sequencing
        technology. BarraCUDA is currently available from. © 2012 Klus et al; licensee
        BioMed Central Ltd.'
      authors:
      - name: Klus P.
      - name: Lam S.
      - name: Lyberg D.
      - name: Cheung M.
      - name: Pullan G.
      - name: McFarlane I.
      - name: Yeo G.S.H.
      - name: Lam B.Y.H.
      citationCount: 109
      date: '2012-01-16T00:00:00Z'
      journal: BMC Research Notes
      title: BarraCUDA - A fast short read sequence aligner using graphics processing
        units
    note: null
    pmcid: PMC3278344
    pmid: '22244497'
    type: []
    version: null
  relation: []
  toolType:
  - Command-line tool
  topic:
  - term: Sequence analysis
    uri: http://edamontology.org/topic_0080
  validated: 1
  version: []
- accessibility: null
  additionDate: '2017-12-18T00:03:50Z'
  biotoolsCURIE: biotools:bars
  biotoolsID: bars
  collectionID: []
  confidence_flag: null
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  credit:
  - email: null
    fundrefid: null
    gridid: null
    name: null
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: http://wpicr.wpic.pitt.edu/WPICCompGen/
  description: BARS is a statistical method that bridges the gap between single-locus
    and haplotype-based tests of association. It is based on the non-parametric regression
    techniques embodied by Bayesian Adaptive Regression Splines.
  documentation:
  - note: null
    type:
    - General
    url: http://wpicr.wpic.pitt.edu/WPICCompGen/BARS/BARS_R_INSTRUCTIONS.htm
  download: []
  editPermission:
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  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Regression
      uri: http://edamontology.org/operation_3659
    output: []
  homepage: http://wpicr.wpic.pitt.edu/WPICCompGen/bars.htm
  homepage_status: 0
  language:
  - R
  lastUpdate: '2024-11-24T20:36:18.873362Z'
  license: null
  link:
  - note: null
    type:
    - Software catalogue
    url: http://www.mybiosoftware.com/bars-bayesian-adaptive-regression-splines.html
  maturity: null
  name: BARS
  operatingSystem:
  - Linux
  otherID:
  - type: rrid
    value: RRID:SCR_009123
    version: null
  owner: mbs_import
  publication:
  - doi: 10.1186/1479-7364-1-1-20
    metadata:
      abstract: In the search for genetic determinants of complex disease, two approaches
        to association analysis are most often employed, testing single loci or testing
        a small group of loci jointly via haplotypes for their relationship to disease
        status. It is still debatable which of these approaches is more favourable,
        and under what conditions. The former has the advantage of simplicity but
        suffers severely when alleles at the tested loci are not in linkage disequilibrium
        (LD) with liability alleles; the latter should capture more of the signal
        encoded in LD, but is far from simple. The complexity of haplotype analysis
        could be especially troublesome for association scans over large genomic regions,
        which, in fact, is becoming the standard design. For these reasons, the authors
        have been evaluating statistical methods that bridge the gap between single-locus
        and haplotype-based tests. In this article, they present one such method,
        which uses non-parametric regression techniques embodied by Bayesian adaptive
        regression splines (BARS). For a set of markers falling within a common genomic
        region and a corresponding set of single-locus association statistics, the
        BARS procedure integrates these results into a single test by examining the
        class of smooth curves consistent with the data. The non-parametric BARS procedure
        generally finds no signal when no liability allele exists in the tested region
        (ie it achieves the specified size of the test) and it is sensitive enough
        to pick up signals when a liability allele is present. The BARS procedure
        provides a robust and potentially powerful alternative to classical tests
        of association, diminishes the multiple testing problem inherent in those
        tests and can be applied to a wide range of data types, including genotype
        frequencies estimated from pooled samples.
      authors:
      - name: Zhang X.
      - name: Roeder K.
      - name: Wallstrom G.
      - name: Devlin B.
      citationCount: 20
      date: '2003-01-01T00:00:00Z'
      journal: Human genomics
      title: Integration of association statistics over genomic regions using Bayesian
        adaptive regression splines.
    note: null
    pmcid: PMC3525002
    pmid: '15601530'
    type:
    - Primary
    version: null
  relation: []
  toolType:
  - Command-line tool
  topic:
  - term: Genetics
    uri: http://edamontology.org/topic_3053
  validated: 1
  version: []
- accessibility: null
  additionDate: '2017-01-13T13:13:39Z'
  biotoolsCURIE: biotools:bayescall
  biotoolsID: bayescall
  collectionID: []
  confidence_flag: null
  cost: null
  credit:
  - email: wckao@eecs.berkeley.edu
    fundrefid: null
    gridid: null
    name: Wei-Chun Kao
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  - email: yss@eecs.berkeley.edu
    fundrefid: null
    gridid: null
    name: Yun S. Song
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  description: Bayesian basecaller
  documentation:
  - note: null
    type:
    - General
    url: http://bayescall.sourceforge.net/README.txt
  download: []
  editPermission:
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  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Base-calling
      uri: http://edamontology.org/operation_3185
    output: []
  homepage: http://bayescall.sourceforge.net/
  homepage_status: 0
  language:
  - C++
  - Python
  lastUpdate: '2024-11-24T20:36:17.804936Z'
  license: GPL-3.0
  link: []
  maturity: Legacy
  name: BayesCall
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID:
  - type: rrid
    value: RRID:SCR_011866
    version: null
  owner: seqwiki_import
  publication:
  - doi: 10.1101/gr.095299.109
    metadata:
      abstract: Extracting sequence information from raw images of fluorescence is
        the foundation underlying several high-throughput sequencing platforms. Some
        of the main challenges associated with this technology include reducing the
        error rate, assigning accurate base-specific quality scores, and reducing
        the cost of sequencing by increasing the throughput per run. To demonstrate
        how computational advancement can help to meet these challenges, a novel model-based
        base-calling algorithm, BayesCall, is introduced for the Illumina sequencing
        platform. Being founded on the tools of statistical learning, BayesCall is
        flexible enough to incorporate various features of the sequencing process.
        In particular, it can easily incorporate time-dependent parameters and model
        residual effects. This new approach significantly improves the accuracy over
        Illumina's base-caller Bustard, particularly in the later cycles of a sequencing
        run. For 76-cycle data on a standard viral sample, phiX174, BayesCall improves
        Bustard's average per-base error rate by ∼51%. The probability of observing
        each base can be readily computed in BayesCall, and this probability can be
        transformed into a useful basespecific quality score with a high discrimination
        ability. A detailed study of BayesCall's performance is presented here. ©
        2009 by Cold Spring Harbor Laboratory Press.
      authors:
      - name: Kao W.-C.
      - name: Stevens K.
      - name: Song Y.S.
      citationCount: 69
      date: '2009-10-01T00:00:00Z'
      journal: Genome Research
      title: 'BayesCall: A model-based base-calling algorithm for high-throughput
        short-read sequencing'
    note: null
    pmcid: PMC2765266
    pmid: '19661376'
    type: []
    version: null
  relation: []
  toolType:
  - Command-line tool
  topic:
  - term: Sequencing
    uri: http://edamontology.org/topic_3168
  validated: 1
  version: []
- accessibility: null
  additionDate: '2017-08-03T18:36:46Z'
  biotoolsCURIE: biotools:bayesfst
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  collectionID: []
  confidence_flag: null
  cost: null
  credit:
  - email: d.balding@ic.ac.uk
    fundrefid: null
    gridid: null
    name: D.J. Balding
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: http://www.reading.ac.uk/maths-and-stats/
  description: Bayesian estimation of the coancestry coefficient FST
  documentation:
  - note: null
    type:
    - General
    url: http://www.reading.ac.uk/Statistics/genetics/software.html
  download: []
  editPermission:
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  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Statistical inference
      uri: http://edamontology.org/operation_3658
    output: []
  homepage: http://www.reading.ac.uk/Statistics/genetics/software.html
  homepage_status: 0
  language: []
  lastUpdate: '2024-11-24T20:36:16.676331Z'
  license: null
  link:
  - note: null
    type:
    - Software catalogue
    url: http://www.mybiosoftware.com/bayesfst-bayesian-estimation-coancestry-coefficient-fst.html
  maturity: null
  name: BAYESFST
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  - Windows
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    value: RRID:SCR_013479
    version: null
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  publication:
  - doi: 10.1111/j.1365-294x.2004.02125.x
    metadata:
      abstract: The identification of signatures of natural selection in genomic surveys
        has become an area of intense research, stimulated by the increasing ease
        with which genetic markers can be typed. Loci identified as subject to selection
        may be functionally important, and hence (weak) candidates for involvement
        in disease causation. They can also be useful in determining the adaptive
        differentiation of populations, and exploring hypotheses about speciation.
        Adaptive differentiation has traditionally been identified from differences
        in allele frequencies among different populations, summarised by an estimate
        of F ST. Low outliers relative to an appropriate neutral population-genetics
        model indicate loci subject to balancing selection, whereas high outliers
        suggest adaptive (directional) selection. However, the problem of identifying
        statistically significant departures from neutrality is complicated by confounding
        effects on the distribution of F ST estimates, and current methods have not
        yet been tested in large-scale simulation experiments. Here, we simulate data
        from a structured population at many unlinked, diallelic loci that are predominantly
        neutral but with some loci subject to adaptive or balancing selection. We
        develop a hierarchical-Bayesian method, implemented via Markov chain Monte
        Carlo (MCMC), and assess its performance in distinguishing the loci simulated
        under selection from the neutral loci. We also compare this performance with
        that of a frequentist method, based on moment-based estimates of F ST. We
        find that both methods can identify loci subject to adaptive selection when
        the selection coefficient is at least five times the migration rate. Neither
        method could reliably distinguish loci under balancing selection in our simulations,
        even when the selection coefficient is twenty times the migration rate.
      authors:
      - name: Beaumont M.A.
      - name: Balding D.J.
      citationCount: 811
      date: '2004-04-01T00:00:00Z'
      journal: Molecular Ecology
      title: Identifying adaptive genetic divergence among populations from genome
        scans
    note: null
    pmcid: null
    pmid: '15012769'
    type: []
    version: null
  relation: []
  toolType:
  - Command-line tool
  topic:
  - term: Genetics
    uri: http://edamontology.org/topic_3053
  - term: Population genetics
    uri: http://edamontology.org/topic_3056
  - term: Statistics and probability
    uri: http://edamontology.org/topic_2269
  validated: 1
  version: []
- accessibility: null
  additionDate: '2017-01-13T13:13:41Z'
  biotoolsCURIE: biotools:bbseq
  biotoolsID: bbseq
  collectionID: []
  confidence_flag: null
  cost: null
  credit:
  - email: yzhou@bios.unc.edu
    fundrefid: null
    gridid: null
    name: Yi-Hui Zhou
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: http://www.bios.unc.edu/~yihuiz
  description: An R package for analyzing RNA-Seq transcriptional count data.
  documentation:
  - note: null
    type:
    - User manual
    url: http://www.bios.unc.edu/research/genomic_software/BBSeq/index_files/manual.pdf
  download: []
  editPermission:
    authors:
    - ELIXIR-EE
    type: group
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  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: RNA sequence
        uri: http://edamontology.org/data_3495
      format:
      - term: rna
        uri: http://edamontology.org/format_1213
    note: null
    operation:
    - term: RNA-Seq quantification
      uri: http://edamontology.org/operation_3800
    - term: RNA-seq read count analysis
      uri: http://edamontology.org/operation_3563
    - term: Gene expression analysis
      uri: http://edamontology.org/operation_2495
    - term: Statistical calculation
      uri: http://edamontology.org/operation_2238
    output:
    - data:
        term: Mathematical model
        uri: http://edamontology.org/data_0950
      format:
      - term: Workflow format
        uri: http://edamontology.org/format_2032
  homepage: http://www.bios.unc.edu/research/genomic_software/BBSeq/
  homepage_status: 0
  language:
  - R
  lastUpdate: '2024-11-24T20:36:15.513581Z'
  license: null
  link: []
  maturity: null
  name: BBSeq
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID:
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    value: RRID:SCR_011877
    version: null
  owner: seqwiki_import
  publication:
  - doi: 10.1093/bioinformatics/btr449
    metadata:
      abstract: 'Motivation: A number of penalization and shrinkage approaches have
        been proposed for the analysis of microarray gene expression data. Similar
        techniques are now routinely applied to RNA sequence transcriptional count
        data, although the value of such shrinkage has not been conclusively established.
        If penalization is desired, the explicit modeling of mean-variance relationships
        provides a flexible testing regimen that ''borrows'' information across genes,
        while easily incorporating design effects and additional covariates.Results:
        We describe BBSeq, which incorporates two approaches: (i) a simple beta-binomial
        generalized linear model, which has not been extensively tested for RNA-Seq
        data and (ii) an extension of an expression mean-variance modeling approach
        to RNA-Seq data, involving modeling of the overdispersion as a function of
        the mean. Our approaches are flexible, allowing for general handling of discrete
        experimental factors and continuous covariates. We report comparisons with
        other alternate methods to handle RNA-Seq data. Although penalized methods
        have advantages for very small sample sizes, the beta-binomial generalized
        linear model, combined with simple outlier detection and testing approaches,
        appears to have favorable characteristics in power and flexibility. © The
        Author 2011. Published by Oxford University Press. All rights reserved.'
      authors:
      - name: Zhou Y.-H.
      - name: Xia K.
      - name: Wright F.A.
      citationCount: 91
      date: '2011-10-01T00:00:00Z'
      journal: Bioinformatics
      title: A powerful and flexible approach to the analysis of RNA sequence count
        data
    note: null
    pmcid: PMC3179656
    pmid: '21810900'
    type: []
    version: null
  relation: []
  toolType:
  - Library
  topic:
  - term: RNA-Seq
    uri: http://edamontology.org/topic_3170
  - term: Statistics and probability
    uri: http://edamontology.org/topic_2269
  - term: Gene expression
    uri: http://edamontology.org/topic_0203
  validated: 1
  version: []
- accessibility: null
  additionDate: '2018-07-13T18:06:51Z'
  biotoolsCURIE: biotools:bcbtoolkit
  biotoolsID: bcbtoolkit
  collectionID: []
  confidence_flag: null
  cost: null
  credit:
  - email: michel.thiebaut@gmail.com
    fundrefid: null
    gridid: null
    name: Michel Thiebaut de Schotten
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  description: Aims to provide the scientific community with the several tools to
    indirectly assess brain disconnections.
  documentation:
  - note: null
    type:
    - General
    url: http://toolkit.bcblab.com/
  download: []
  editPermission:
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    type: private
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  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Pathway or network analysis
      uri: http://edamontology.org/operation_2497
    output: []
  homepage: http://toolkit.bcblab.com/
  homepage_status: 0
  language:
  - R
  - Java
  lastUpdate: '2024-11-24T20:36:14.041890Z'
  license: BSD-3-Clause
  link: []
  maturity: null
  name: BCBtoolkit
  operatingSystem:
  - Linux
  - Mac
  otherID:
  - type: rrid
    value: RRID:SCR_015519
    version: null
  owner: d.gabrielaitis
  publication:
  - doi: 10.1093/gigascience/giy004
    metadata:
      abstract: 'Background: Patients with brain lesions provide a unique opportunity
        to understand the functioning of the human mind. However, even when focal,
        brain lesions have local and remote effects that impact functionally and structurally
        connected circuits. Similarly, function emerges from the interaction between
        brain areas rather than their sole activity. For instance, category fluency
        requires the associations between executive, semantic, and language production
        functions. Findings: Here, we provide, for the first time, a set of complementary
        solutions for measuring the impact of a given lesion on the neuronal circuits.
        Our methods, which were applied to 37 patients with a focal frontal brain
        lesions, revealed a large set of directly and indirectly disconnected brain
        regions that had significantly impacted category fluency performance. The
        directly disconnected regions corresponded to areas that are classically considered
        as functionally engaged in verbal fluency and categorization tasks. These
        regions were also organized into larger directly and indirectly disconnected
        functional networks, including the left ventral fronto-parietal network, whose
        cortical thickness correlated with performance on category fluency. Conclusions:
        The combination of structural and functional connectivity together with cortical
        thickness estimates reveal the remote effects of brain lesions, provide for
        the identification of the affected networks, and strengthen our understanding
        of their relationship with cognitive and behavioral measures. The methods
        presented are available and freely accessible in the BCBtoolkit as supplementary
        software [1].'
      authors:
      - name: Foulon C.
      - name: Cerliani L.
      - name: Kinkingnehun S.
      - name: Levy R.
      - name: Rosso C.
      - name: Urbanski M.
      - name: Volle E.
      - name: de Schotten M.T.
      citationCount: 223
      date: '2018-03-01T00:00:00Z'
      journal: GigaScience
      title: Advanced lesion symptom mapping analyses and implementation as BCBtoolkit
    note: null
    pmcid: PMC5863218
    pmid: '29432527'
    type: []
    version: null
  relation: []
  toolType:
  - Command-line tool
  topic:
  - term: Neurology
    uri: http://edamontology.org/topic_3334
  - term: Neurobiology
    uri: http://edamontology.org/topic_3304
  - term: Molecular interactions, pathways and networks
    uri: http://edamontology.org/topic_0602
  validated: 1
  version: []
- accessibility: null
  additionDate: '2017-03-27T07:20:05Z'
  biotoolsCURIE: biotools:beetlebase
  biotoolsID: beetlebase
  collectionID: []
  confidence_flag: null
  cost: null
  credit:
  - email: bioinfo@ksu.edu
    fundrefid: null
    gridid: null
    name: Support
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  description: The database contains genomic sequence scaffolds mapped to 10 linkage
    groups, genetic linkage maps, the official gene set, Reference Sequences from
    NCBI (RefSeq), predicted gene models, ESTs and whole-genome tiling array data
    representing several developmental stages. The database was reconstructed using
    the upgraded Generic Model Organism Database (GMOD) modules, it has been updated
    to provide more comprehensive genomic information for the red flour beetle Tribolium
    castaneum.
  documentation:
  - note: null
    type:
    - General
    url: http://beetlebase.org/?q=home
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    operation:
    - term: Genome assembly
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    - term: Sequence tagged site (STS) mapping
      uri: http://edamontology.org/operation_2871
    - term: Genetic mapping
      uri: http://edamontology.org/operation_0282
    - term: Scaffolding
      uri: http://edamontology.org/operation_3216
    - term: Mapping
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    output: []
  homepage: http://beetlebase.org/
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  name: BeetleBase
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  publication:
  - doi: 10.1093/nar/gkp807
    metadata:
      abstract: BeetleBase (http://www.beetlebase.org) has been updated to provide
        more comprehensive genomic information for the red flour beetle Tribolium
        castaneum. The database contains genomic sequence scaffolds mapped to 10 linkage
        groups (genome assembly release Tcas_3.0), genetic linkage maps, the official
        gene set, Reference Sequences from NCBI (RefSeq), predicted gene models, ESTs
        and whole-genome tiling array data representing several developmental stages.
        The database was reconstructed using the upgraded Generic Model Organism Database
        (GMOD) modules. The genomic data is stored in a PostgreSQL relatational database
        using the Chado schema and visualized as tracks in GBrowse. The updated genetic
        map is visualized using the comparative genetic map viewer CMAP. To enhance
        the database search capabilities, the BLAST and BLAT search tools have been
        integrated with the GMOD tools. BeetleBase serves as a long-term repository
        for Tribolium genomic data, and is compatible with other model organism databases.
        © The Author(s) 2009. Published by Oxford University Press.
      authors:
      - name: Kim H.S.
      - name: Murphy T.
      - name: Xia J.
      - name: Caragea D.
      - name: Park Y.
      - name: Beeman R.W.
      - name: Lorenzen M.D.
      - name: Butcher S.
      - name: Manak J.R.
      - name: Brown S.J.
      citationCount: 129
      date: '2009-10-09T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'BeetleBase in 2010: Revisions to provide comprehensive genomic information
        for Tribolium castaneum'
    note: null
    pmcid: PMC2808946
    pmid: '19820115'
    type: []
    version: null
  relation: []
  toolType:
  - Database portal
  topic:
  - term: Mapping
    uri: http://edamontology.org/topic_0102
  - term: Model organisms
    uri: http://edamontology.org/topic_0621
  - term: Gene transcripts
    uri: http://edamontology.org/topic_3512
  - term: Sequence assembly
    uri: http://edamontology.org/topic_0196
  - term: Genetics
    uri: http://edamontology.org/topic_3053
  validated: 1
  version: []
- accessibility: null
  additionDate: '2015-02-02T11:23:55Z'
  biotoolsCURIE: biotools:bingo
  biotoolsID: bingo
  collectionID:
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  - Plant Systems Biology
  - UGent
  confidence_flag: null
  cost: null
  credit:
  - email: null
    fundrefid: null
    gridid: null
    name: PSB
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
    - Provider
    url: null
  - email: steven.maere@psb.vib-ugent.be
    fundrefid: null
    gridid: null
    name: Steven Maere
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
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    url: http://www.psb.ugent.be/esb/ESB/Home.html
  description: A tool to determine which Gene Ontology (GO) categories are statistically
    overrepresented in a set of genes or a subgraph of a biological network.
  documentation:
  - note: null
    type:
    - General
    url: https://www.psb.ugent.be/cbd/papers/BiNGO/Tutorial.html
  download: []
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  function:
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    input:
    - data:
        term: Gene identifier
        uri: http://edamontology.org/data_1025
      format: []
    - data:
        term: Ontology identifier
        uri: http://edamontology.org/data_2338
      format: []
    note: GO enrichment analysis
    operation:
    - term: Enrichment analysis
      uri: http://edamontology.org/operation_3501
    output:
    - data:
        term: Ontology identifier
        uri: http://edamontology.org/data_2338
      format:
      - term: plain text format (unformatted)
        uri: http://edamontology.org/format_1964
    - data:
        term: P-value
        uri: http://edamontology.org/data_1669
      format: []
  homepage: http://www.psb.ugent.be/cbd/papers/BiNGO/Home.html
  homepage_status: 0
  language: []
  lastUpdate: '2024-11-24T20:36:11.478539Z'
  license: null
  link: []
  maturity: null
  name: BiNGO
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID:
  - type: rrid
    value: RRID:SCR_005736
    version: null
  owner: PSB
  publication:
  - doi: 10.1093/bioinformatics/bti551
    metadata:
      abstract: 'Summary: The Biological Networks Gene Ontology tool (BiNGO) is an
        open-source Java tool to determine which Gene Ontology (GO) terms are significantly
        overrepresented in a set of genes. BiNGO can be used either on a list of genes,
        pasted as text, or interactively on subgraphs of biological networks visualized
        in Cytoscape. BiNGO maps the predominant functional themes of the tested gene
        set on the GO hierarchy, and takes advantage of Cytoscape''s versatile visualization
        environment to produce an intuitive and customizable visual representation
        of the results. © The Author 2005. Published by Oxford University Press. All
        rights reserved.'
      authors:
      - name: Maere S.
      - name: Heymans K.
      - name: Kuiper M.
      citationCount: 3355
      date: '2005-08-15T00:00:00Z'
      journal: Bioinformatics
      title: 'BiNGO: A Cytoscape plugin to assess overrepresentation of Gene Ontology
        categories in Biological Networks'
    note: null
    pmcid: null
    pmid: '15972284'
    type:
    - Primary
    version: null
  relation: []
  toolType:
  - Desktop application
  topic:
  - term: Functional genomics
    uri: http://edamontology.org/topic_0085
  validated: 1
  version:
  - 3.0.2
- accessibility: null
  additionDate: '2017-05-16T12:57:23Z'
  biotoolsCURIE: biotools:bioanalres_bar
  biotoolsID: bioanalres_bar
  collectionID: []
  confidence_flag: null
  cost: null
  credit:
  - email: nicholas.provart@utoronto.ca
    fundrefid: null
    gridid: null
    name: Nicholas J. Provart
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  description: User-friendly web-based tools for working with functional genomics
    and other data. Most are designed with the plant (mainly Arabidopsis) reseacher
    in mind, but a couple of them can be useful to the wider research community.
  documentation: []
  download: []
  editPermission:
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  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Over-representation analysis
      uri: http://edamontology.org/operation_3501
    - term: Gene expression profiling
      uri: http://edamontology.org/operation_0314
    - term: Gene expression correlation analysis
      uri: http://edamontology.org/operation_3463
    - term: Protein-protein binding site prediction
      uri: http://edamontology.org/operation_2464
    output: []
  homepage: http://bar.utoronto.ca/welcome.htm
  homepage_status: 0
  language: []
  lastUpdate: '2024-11-24T20:36:09.173434Z'
  license: null
  link: []
  maturity: null
  name: Bio-Analytic Resource (BAR)
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID:
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    value: RRID:SCR_006748
    version: null
  owner: ELIXIR-EE
  publication:
  - doi: 10.1007/978-1-4939-6658-5_6
    metadata:
      abstract: Bioinformatic tools have become part of the way plant researchers
        undertake investigations. Large data sets encompassing genomes, transcriptomes,
        proteomes, epigenomes, and other “-omes” that have been generated in the past
        decade may be easily accessed with such tools, such that hypotheses may be
        generated at the click of a mouse. In this chapter, we’ll cover the use of
        bioinformatic tools available at the Bio-Analytic Resource for Plant Biology
        at http://bar.utoronto.ca for exploring gene expression and coexpression patterns,
        undertaking promoter analyses, performing functional classification enrichment
        analyses for sets of genes, and examining protein-protein interactions. We
        also touch on some newer bioinformatic tools that allow integration of data
        from several sources for improved hypothesis generation, both for Arabidopsis
        and translationally. Most of the data sets come from Arabidopsis, but useful
        BAR tools for other species will be mentioned where appropriate.
      authors:
      - name: Waese J.
      - name: Provart N.J.
      citationCount: 37
      date: '2017-01-01T00:00:00Z'
      journal: Methods in Molecular Biology
      title: The bio-analytic resource for plant biology
    note: null
    pmcid: null
    pmid: '27987167'
    type: []
    version: null
  - doi: 10.1111/tpj.13261
    metadata:
      abstract: Identifying sets of genes that are specifically expressed in certain
        tissues or in response to an environmental stimulus is useful for designing
        reporter constructs, generating gene expression markers, or for understanding
        gene regulatory networks. We have developed an easy-to-use online tool for
        defining a desired expression profile (a modification of our Expression Angler
        program), which can then be used to identify genes exhibiting patterns of
        expression that match this profile as closely as possible. Further, we have
        developed another online tool, Cistome, for predicting or exploring cis-elements
        in the promoters of sets of co-expressed genes identified by such a method,
        or by other methods. We present two use cases for these tools, which are freely
        available on the Bio-Analytic Resource at http://BAR.utoronto.ca.
      authors:
      - name: Austin R.S.
      - name: Hiu S.
      - name: Waese J.
      - name: Ierullo M.
      - name: Pasha A.
      - name: Wang T.T.
      - name: Fan J.
      - name: Foong C.
      - name: Breit R.
      - name: Desveaux D.
      - name: Moses A.
      - name: Provart N.J.
      citationCount: 41
      date: '2016-11-01T00:00:00Z'
      journal: Plant Journal
      title: New BAR tools for mining expression data and exploring Cis-elements in
        Arabidopsis thaliana
    note: null
    pmcid: null
    pmid: '27401965'
    type: []
    version: null
  relation: []
  toolType:
  - Web application
  topic:
  - term: Epigenomics
    uri: http://edamontology.org/topic_3173
  - term: Transcriptomics
    uri: http://edamontology.org/topic_3308
  - term: Molecular interactions, pathways and networks
    uri: http://edamontology.org/topic_0602
  - term: Gene expression
    uri: http://edamontology.org/topic_0203
  validated: 1
  version: []
- accessibility: null
  additionDate: '2017-05-02T07:18:39Z'
  biotoolsCURIE: biotools:genmapp
  biotoolsID: genmapp
  collectionID: []
  confidence_flag: null
  cost: null
  credit:
  - email: bconklin@gladstone.ucsf.edu
    fundrefid: null
    gridid: null
    name: Bruce R. Conklin
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
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    url: null
  description: Microarray expression data visualization tool, allowing data to be
    viewed on maps representing gene groupings and biological pathways.
  documentation: []
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  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Gene expression clustering
      uri: http://edamontology.org/operation_0313
    - term: Gene expression comparison
      uri: http://edamontology.org/operation_0315
    - term: Gene expression profiling
      uri: http://edamontology.org/operation_0314
    - term: Gene expression analysis
      uri: http://edamontology.org/operation_2495
    output: []
  homepage: http://www.genmapp.org/
  homepage_status: 0
  language: []
  lastUpdate: '2024-11-24T20:36:07.676279Z'
  license: null
  link: []
  maturity: null
  name: GenMAPP
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  - Linux
  - Windows
  - Mac
  otherID:
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    value: RRID:SCR_005094
    version: null
  owner: ELIXIR-EE
  publication:
  - doi: 10.1038/ng0502-19
    metadata:
      abstract: ''
      authors:
      - name: Dahlquist K.D.
      - name: Salomonis N.
      - name: Vranizan K.
      - name: Lawlor S.C.
      - name: Conklin B.R.
      citationCount: 818
      date: '2002-01-01T00:00:00Z'
      journal: Nature Genetics
      title: GenMAPP, a new tool for viewing and analyzing microarray data on biological
        pathways
    note: null
    pmcid: null
    pmid: '11984561'
    type: []
    version: null
  relation: []
  toolType:
  - Web application
  topic:
  - term: Molecular interactions, pathways and networks
    uri: http://edamontology.org/topic_0602
  - term: Gene expression
    uri: http://edamontology.org/topic_0203
  - term: Microarray experiment
    uri: http://edamontology.org/topic_3518
  - term: Model organisms
    uri: http://edamontology.org/topic_0621
  - term: Mapping
    uri: http://edamontology.org/topic_0102
  validated: 1
  version: []
- accessibility: null
  additionDate: '2017-08-03T18:45:26Z'
  biotoolsCURIE: biotools:genome_projector
  biotoolsID: genome_projector
  collectionID: []
  confidence_flag: null
  cost: null
  credit:
  - email: null
    fundrefid: null
    gridid: null
    name: null
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: http://www.g-language.org/GenomeProjector/members.html
  description: 'Searchable database browser with zoomable user interface using Google
    Map API. Genome Projector currently contains 4 views: Genome map, Plasmid map,
    Pathway map, and DNA walk.'
  documentation:
  - note: null
    type:
    - General
    url: http://www.g-language.org/GenomeProjector/wiki/
  download: []
  editPermission:
    authors: []
    type: private
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  elixirNode: []
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  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Genome visualisation
      uri: http://edamontology.org/operation_3208
    output: []
  homepage: http://www.g-language.org/GenomeProjector/
  homepage_status: 0
  language:
  - JavaScript
  - Perl
  lastUpdate: '2024-11-24T20:36:06.278615Z'
  license: null
  link:
  - note: null
    type:
    - Software catalogue
    url: http://www.mybiosoftware.com/genome-projector-zoomable-user-interface-molecular-biology.html
  maturity: null
  name: Genome Projector
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID:
  - type: rrid
    value: RRID:SCR_011790
    version: null
  owner: mbs_import
  publication:
  - doi: 10.1186/1471-2105-10-31
    metadata:
      abstract: 'BACKGROUND: Molecular biology data exist on diverse scales, from
        the level of molecules to -omics. At the same time, the data at each scale
        can be categorised into multiple layers, such as the genome, transcriptome,
        proteome, metabolome, and biochemical pathways. Due to the highly multi-layer
        and multi-dimensional nature of biological information, software interfaces
        for database browsing should provide an intuitive interface that allows for
        rapid migration across different views and scales. The Zoomable User Interface
        (ZUI) and tabbed browsing have proven successful for this purpose in other
        areas, especially to navigate the vast information in the World Wide Web.
        RESULTS: This paper presents Genome Projector, a Web-based gateway for genomics
        information with a zoomable user interface using Google Maps API, equipped
        with four seamlessly accessible and searchable views: a circular genome map,
        a traditional genome map, a biochemical pathways map, and a DNA walk map.
        The Web application for 320 bacterial genomes is available at http://www.g-language.org/GenomeProjector/.
        All data and software including the source code, documentations, and development
        API are freely available under the GNU General Public License. Zoomable maps
        can be easily created from any image file using the development API, and an
        online data mapping service for Genome Projector is also available at our
        Web site. CONCLUSION: Genome Projector is an intuitive Web application for
        browsing genomics information, implemented with a zoomable user interface
        and tabbed browsing utilising Google Maps API and Asynchronous JavaScript
        and XML (AJAX) technology.'
      authors:
      - name: Arakawa K.
      - name: Tamaki S.
      - name: Kono N.
      - name: Kido N.
      - name: Ikegami K.
      - name: Ogawa R.
      - name: Tomita M.
      citationCount: 34
      date: '2009-01-01T00:00:00Z'
      journal: BMC bioinformatics
      title: 'Genome Projector: zoomable genome map with multiple views.'
    note: null
    pmcid: PMC2636772
    pmid: '19166610'
    type: []
    version: null
  relation: []
  toolType:
  - Web application
  topic:
  - term: Biology
    uri: http://edamontology.org/topic_3070
  - term: Molecular biology
    uri: http://edamontology.org/topic_3047
  - term: DNA
    uri: http://edamontology.org/topic_0654
  - term: Sequence analysis
    uri: http://edamontology.org/topic_0080
  - term: Data visualisation
    uri: http://edamontology.org/topic_0092
  validated: 1
  version: []
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