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  description: Charge state determination and molecular weight calculation for low
    resolution electrospray ionization data.
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      citationCount: 75
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  description: It systematizes the association evaluation between exposures and omic
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      citationCount: 112
      date: '2022-12-01T00:00:00Z'
      journal: Nature Communications
      title: Multi-omics signatures of the human early life exposome
    note: null
    pmcid: PMC9678903
    pmid: '36411288'
    type:
    - Usage
    version: null
  relation:
  - biotoolsID: rexposome
    type: uses
  toolType:
  - Library
  topic:
  - term: Epigenetics
    uri: http://edamontology.org/topic_3295
  - term: Gene expression
    uri: http://edamontology.org/topic_0203
  - term: Gene regulation
    uri: http://edamontology.org/topic_0204
  - term: Proteomics
    uri: http://edamontology.org/topic_0121
  - term: Statistics and probability
    uri: http://edamontology.org/topic_2269
  - term: Transcriptomics
    uri: http://edamontology.org/topic_3308
  validated: 1
  version:
  - 1.2.0
- accessibility: null
  additionDate: '2017-01-17T15:07:56Z'
  biotoolsCURIE: biotools:metfusion
  biotoolsID: metfusion
  collectionID: []
  confidence_flag: null
  cost: null
  credit:
  - email: mgerlich@ipb-halle.de
    fundrefid: null
    gridid: null
    name: null
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  description: 'Approach to combine the knowledge from spectral databases like MassBank
    with the multitude of candidates generated by fragmenters such as MetFrag.

    The functionality of the original MetFusion application has been integrated into
    MetFrag, MetFusion itself has been deactivated.'
  documentation:
  - note: null
    type:
    - General
    url: https://msbi.ipb-halle.de/MetFusion/
  download: []
  editPermission:
    authors:
    - proteomics.bio.tools
    - recetox-specdatri
    type: group
  elixirCommunity: []
  elixirNode: []
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  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Spectral analysis
      uri: http://edamontology.org/operation_3214
    output: []
  homepage: http://msbi.ipb-halle.de/MetFusion/
  homepage_status: 0
  language: []
  lastUpdate: '2025-11-16T16:31:08.158692Z'
  license: null
  link: []
  maturity: Legacy
  name: MetFusion
  operatingSystem:
  - Windows
  - Mac
  - Linux
  otherID: []
  owner: sneumann
  publication:
  - doi: 10.1002/jms.3123
    metadata:
      abstract: ''
      authors: []
      citationCount: 146
      date: '2013-03-01T00:00:00Z'
      journal: Journal of Mass Spectrometry
      title: 'MetFusion: Integration of compound identification strategies'
    note: null
    pmcid: null
    pmid: '23494783'
    type: []
    version: null
  relation: []
  toolType:
  - Web application
  topic:
  - term: Proteomics
    uri: http://edamontology.org/topic_0121
  - term: Metabolomics
    uri: http://edamontology.org/topic_3172
  validated: 1
  version: []
- accessibility: Open access
  additionDate: '2019-06-18T19:35:41Z'
  biotoolsCURIE: biotools:ComplexBrowser
  biotoolsID: ComplexBrowser
  collectionID:
  - Proteomics
  confidence_flag: null
  cost: null
  credit:
  - email: veits@bmb.sdu.dk
    fundrefid: null
    gridid: null
    name: Veit Schwämmle
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  description: ComplexBrowser is a R based software for supervised analysis of changes
    in protein complex abundance and subunit co-expression in proteomic datasets.
    It uses information contained in CORUM and EBI Complex Portal databases to provide
    the user with visualizations helping with biological interpretation of obtained
    results. ComplexBrowser also incorporates a normalization and quality control
    steps.
  documentation:
  - note: null
    type:
    - User manual
    url: https://bitbucket.org/michalakw/complexbrowser/raw/dc9d8f0c8dff610e2f58e3cb5f5087d050df26f2/Manual.pdf
  download:
  - note: null
    type: Source code
    url: https://bitbucket.org/michalakw/complexbrowser/
    version: '1.0'
  editPermission:
    authors: []
    type: private
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Expression data
        uri: http://edamontology.org/data_2603
      format:
      - term: CSV
        uri: http://edamontology.org/format_3752
      - term: Textual format
        uri: http://edamontology.org/format_2330
    - data:
        term: Protein interaction data
        uri: http://edamontology.org/data_0906
      format:
      - term: CSV
        uri: http://edamontology.org/format_3752
    note: null
    operation:
    - term: Statistical calculation
      uri: http://edamontology.org/operation_2238
    - term: Principal component visualisation
      uri: http://edamontology.org/operation_2939
    - term: Expression analysis
      uri: http://edamontology.org/operation_2495
    - term: Quantification
      uri: http://edamontology.org/operation_3799
    - term: Validation
      uri: http://edamontology.org/operation_2428
    - term: Pathway or network visualisation
      uri: http://edamontology.org/operation_3083
    - term: Scatter plot plotting
      uri: http://edamontology.org/operation_2940
    - term: ID mapping
      uri: http://edamontology.org/operation_3282
    - term: Dendrogram visualisation
      uri: http://edamontology.org/operation_2938
    - term: Protein interaction network analysis
      uri: http://edamontology.org/operation_0276
    - term: Heat map generation
      uri: http://edamontology.org/operation_0531
    - term: Regression analysis
      uri: http://edamontology.org/operation_3659
    - term: Expression correlation analysis
      uri: http://edamontology.org/operation_3463
    - term: Standardisation and normalisation
      uri: http://edamontology.org/operation_3435
    - term: Query and retrieval
      uri: http://edamontology.org/operation_0224
    - term: Expression data visualisation
      uri: http://edamontology.org/operation_0571
    output:
    - data:
        term: Protein report
        uri: http://edamontology.org/data_0896
      format:
      - term: CSV
        uri: http://edamontology.org/format_3752
    - data:
        term: Report
        uri: http://edamontology.org/data_2048
      format:
      - term: PDF
        uri: http://edamontology.org/format_3508
    - data:
        term: Plot
        uri: http://edamontology.org/data_2884
      format:
      - term: PNG
        uri: http://edamontology.org/format_3603
      - term: PDF
        uri: http://edamontology.org/format_3508
  homepage: https://computproteomics.bmb.sdu.dk/app_direct/ComplexBrowser/
  homepage_status: 0
  language:
  - R
  lastUpdate: '2025-11-13T06:12:35.324351Z'
  license: null
  link:
  - note: null
    type:
    - Software catalogue
    url: http://computproteomics.bmb.sdu.dk/
  - note: null
    type:
    - Repository
    url: https://bitbucket.org/michalakw/complexbrowser/src/master/
  maturity: null
  name: ComplexBrowser
  operatingSystem:
  - Windows
  - Mac
  - Linux
  otherID: []
  owner: vtsiamis
  publication:
  - doi: 10.1101/573774
    metadata: null
    note: null
    pmcid: null
    pmid: null
    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: Protein interactions
    uri: http://edamontology.org/topic_0128
  - term: Data visualisation
    uri: http://edamontology.org/topic_0092
  - term: Statistics and probability
    uri: http://edamontology.org/topic_2269
  validated: 1
  version:
  - '1.0'
- accessibility: Open access
  additionDate: '2019-07-04T14:05:39Z'
  biotoolsCURIE: biotools:CliqueMS
  biotoolsID: CliqueMS
  collectionID: []
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: oriol.senan@urv.cat
    fundrefid: null
    gridid: null
    name: Oriol Senan
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  description: Computational tool for annotating in-source metabolite ions from LC-MS
    untargeted metabolomics data based on a coelution similarity network.
  documentation:
  - note: Tutorial material
    type:
    - Training material
    url: https://github.com/osenan/cliqueMS/blob/master/vignettes/annotate_features.Rmd
  download:
  - note: null
    type: Source code
    url: https://cran.r-project.org/src/contrib/Archive/cliqueMS/
    version: null
  editPermission:
    authors:
    - recetox-specdatri
    type: group
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Read binning
      uri: http://edamontology.org/operation_3798
    - term: Natural product identification
      uri: http://edamontology.org/operation_3803
    output: []
  homepage: https://github.com/osenan/cliqueMS
  homepage_status: 0
  language:
  - R
  - C++
  lastUpdate: '2025-11-03T16:44:03.166147Z'
  license: GPL-3.0
  link:
  - note: null
    type:
    - Issue tracker
    url: https://github.com/osenan/cliqueMS/issues
  maturity: Mature
  name: CliqueMS
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: Ruta
  publication:
  - doi: 10.1093/bioinformatics/btz207
    metadata:
      abstract: 'The analysis of biological samples in untargeted metabolomic studies
        using LC-MS yields tens of thousands of ion signals. Annotating these features
        is of the utmost importance for answering questions as fundamental as, e.g.
        how many metabolites are there in a given sample.Results: Here, we introduce
        CliqueMS, a new algorithm for annotating in-source LC-MS1 data. CliqueMS is
        based on the similarity between coelution profiles and therefore, as opposed
        to most methods, allows for the annotation of a single spectrum. Furthermore,
        CliqueMS improves upon the state of the art in several dimensions: (i) it
        uses a more discriminatory feature similarity metric; (ii) it treats the similarities
        between features in a transparent way by means of a simple generativemodel;
        (iii) it uses a well-grounded maximum likelihood inference approach to group
        features; (iv) it uses empirical adduct frequencies to identify the parental
        mass and (v) it deals more flexibly with the identification of the parental
        mass by proposing and ranking alternative annotations. We validate our approach
        with simple mixtures of standards and with real complex biological samples.
        CliqueMS reduces the thousands of features typically obtained in complex samples
        to hundreds of metabolites, and it is able to correctly annotate more metabolites
        and adducts from a single spectrum than available tools.'
      authors:
      - name: Senan O.
      - name: Aguilar-Mogas A.
      - name: Navarro M.
      - name: Capellades J.
      - name: Noon L.
      - name: Burks D.
      - name: Yanes O.
      - name: Guimera R.
      - name: Sales-Pardo M.
      citationCount: 48
      date: '2019-10-15T00:00:00Z'
      journal: Bioinformatics
      title: 'CliqueMS: A computational tool for annotating in-source metabolite ions
        from LC-MS untargeted metabolomics data based on a coelution similarity network'
    note: null
    pmcid: PMC6792096
    pmid: '30903689'
    type:
    - Primary
    version: null
  relation: []
  toolType:
  - Library
  topic:
  - term: Small molecules
    uri: http://edamontology.org/topic_0154
  - term: Metabolomics
    uri: http://edamontology.org/topic_3172
  - term: Proteomics experiment
    uri: http://edamontology.org/topic_3520
  validated: 1
  version:
  - 0.3.2
- accessibility: Open access
  additionDate: '2016-10-20T10:31:19Z'
  biotoolsCURIE: biotools:peptideshaker
  biotoolsID: peptideshaker
  collectionID:
  - de.NBI
  - Proteomics
  - BioInfra.Prot
  confidence_flag: null
  cost: null
  credit:
  - email: null
    fundrefid: null
    gridid: null
    name: BioInfra.Prot
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
    - Provider
    url: null
  - email: dominik.kopczynski@isas.de
    fundrefid: null
    gridid: null
    name: Dominik Kopczynsk
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: http://compomics.github.io/projects/peptide-shaker.html
  description: PeptideShaker is a search engine independent platform for interpretation
    of proteomics identification results from multiple search engines, currently supporting
    X!Tandem, MS-GF+, MS Amanda, OMSSA, MyriMatch, Comet, Tide, Mascot, Andromeda
    and mzIdentML. By combining the results from multiple search engines, while re-calculating
    PTM localization scores and redoing the protein inference, PeptideShaker attempts
    to give you the best possible understanding of your proteomics data
  documentation:
  - note: null
    type:
    - General
    url: http://compomics.github.io/projects/peptide-shaker.html#read-me
  download:
  - note: null
    type: Source code
    url: https://github.com/compomics/peptide-shaker
    version: null
  editPermission:
    authors:
    - proteomics.bio.tools
    - veits@bmb.sdu.dk
    type: group
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Protein sequence
        uri: http://edamontology.org/data_2976
      format:
      - term: FASTA
        uri: http://edamontology.org/format_1929
    - data:
        term: Peptide identification
        uri: http://edamontology.org/data_0945
      format:
      - term: mzIdentML
        uri: http://edamontology.org/format_3247
    - data:
        term: Mass spectrometry data
        uri: http://edamontology.org/data_2536
      format:
      - term: MGF
        uri: http://edamontology.org/format_3651
    note: null
    operation:
    - term: Mass spectrum visualisation
      uri: http://edamontology.org/operation_3694
    - term: Peptide identification
      uri: http://edamontology.org/operation_3631
    - term: Validation
      uri: http://edamontology.org/operation_2428
    - term: PTM localisation
      uri: http://edamontology.org/operation_3755
    - term: Enrichment analysis
      uri: http://edamontology.org/operation_3501
    - term: Structure visualisation
      uri: http://edamontology.org/operation_0570
    - term: Protein identification
      uri: http://edamontology.org/operation_3767
    output:
    - data:
        term: Protein structure image
        uri: http://edamontology.org/data_2992
      format:
      - term: JPG
        uri: http://edamontology.org/format_3579
      - term: SVG
        uri: http://edamontology.org/format_3604
    - data:
        term: GO-term enrichment data
        uri: http://edamontology.org/data_3754
      format:
      - term: Textual format
        uri: http://edamontology.org/format_2330
    - data:
        term: Sequence image
        uri: http://edamontology.org/data_2969
      format:
      - term: Image format
        uri: http://edamontology.org/format_3547
    - data:
        term: Protein report
        uri: http://edamontology.org/data_0896
      format:
      - term: TSV
        uri: http://edamontology.org/format_3475
  homepage: http://compomics.github.io/projects/peptide-shaker.html
  homepage_status: 0
  language:
  - Java
  lastUpdate: '2025-11-01T15:59:45.423975Z'
  license: Apache-2.0
  link: []
  maturity: null
  name: PeptideShaker
  operatingSystem:
  - Mac
  - Linux
  otherID: []
  owner: BioInfra.Prot
  publication:
  - doi: 10.1038/nbt.3109
    metadata:
      abstract: ''
      authors: []
      citationCount: 449
      date: '2015-01-01T00:00:00Z'
      journal: Nature Biotechnology
      title: 'PeptideShaker enables reanalysis of MS-derived proteomics data sets:
        To the editor'
    note: null
    pmcid: null
    pmid: '25574629'
    type:
    - Primary
    version: null
  relation: []
  toolType:
  - Desktop application
  - Command-line tool
  topic:
  - term: Proteomics
    uri: http://edamontology.org/topic_0121
  - term: Proteomics experiment
    uri: http://edamontology.org/topic_3520
  - term: Proteome
    uri: http://edamontology.org/topic_0644
  validated: 1
  version:
  - 3.0.11
- accessibility: null
  additionDate: '2017-01-17T14:50:39Z'
  biotoolsCURIE: biotools:openchrom
  biotoolsID: openchrom
  collectionID:
  - ms-utils
  confidence_flag: null
  cost: null
  credit:
  - email: philip.wenig@gmx.net
    fundrefid: null
    gridid: null
    name: Philip Wenig
    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
  - email: null
    fundrefid: null
    gridid: null
    name: Matthias Mailänder
    note: null
    orcidid: https://orcid.org/0000-0001-6114-0304
    rorid: null
    typeEntity: Person
    typeRole:
    - Contributor
    url: null
  description: Open source tool for mass spectrometry and chromatography.
  documentation:
  - note: null
    type:
    - User manual
    url: https://lablicate.com/marketplace/extensions/handbook
  - note: null
    type:
    - FAQ
    url: https://github.com/OpenChrom/openchrom/wiki/faq
  download:
  - note: null
    type: Downloads page
    url: https://openchrom.net/download
    version: null
  - note: null
    type: Source code
    url: https://github.com/OpenChrom/openchrom
    version: null
  editPermission:
    authors:
    - proteomics.bio.tools
    - Mailaender
    - n.m.palmblad@lumc.nl
    type: group
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Mass spectrometry spectra
        uri: http://edamontology.org/data_0943
      format:
      - term: dat
        uri: http://edamontology.org/format_1637
      - term: Thermo RAW
        uri: http://edamontology.org/format_3712
      - term: mzXML
        uri: http://edamontology.org/format_3654
      - term: CSV
        uri: http://edamontology.org/format_3752
      - term: mzML
        uri: http://edamontology.org/format_3244
      - term: NetCDF
        uri: http://edamontology.org/format_3650
    note: null
    operation:
    - term: Chromatogram visualisation
      uri: http://edamontology.org/operation_3203
    - term: Spectral analysis
      uri: http://edamontology.org/operation_3214
    - term: Comparison
      uri: http://edamontology.org/operation_2424
    - term: Peak detection
      uri: http://edamontology.org/operation_3215
    - term: Mass spectrum visualisation
      uri: http://edamontology.org/operation_3694
    output:
    - data:
        term: Peptide mass fingerprint
        uri: http://edamontology.org/data_0944
      format:
      - term: xlsx
        uri: http://edamontology.org/format_3620
      - term: CSV
        uri: http://edamontology.org/format_3752
      - term: NetCDF
        uri: http://edamontology.org/format_3650
      - term: mzML
        uri: http://edamontology.org/format_3244
    - data:
        term: Image
        uri: http://edamontology.org/data_2968
      format:
      - term: PDF
        uri: http://edamontology.org/format_3508
  homepage: https://www.openchrom.net/
  homepage_status: 0
  language:
  - Java
  lastUpdate: '2025-09-24T15:20:41.738330Z'
  license: EPL-1.0
  link:
  - note: null
    type:
    - Software catalogue
    url: http://ms-utils.org
  maturity: Mature
  name: OpenChrom
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: msutils_import
  publication:
  - doi: 10.1186/1471-2105-11-405
    metadata:
      abstract: ''
      authors: []
      citationCount: 155
      date: '2010-07-30T00:00:00Z'
      journal: BMC Bioinformatics
      title: 'OpenChrom: A cross-platform open source software for the mass spectrometric
        analysis of chromatographic data'
    note: null
    pmcid: null
    pmid: '20673335'
    type: []
    version: null
  relation: []
  toolType:
  - Desktop application
  topic:
  - term: Data visualisation
    uri: http://edamontology.org/topic_0092
  - term: Analytical chemistry
    uri: http://edamontology.org/topic_3370
  validated: 1
  version: []
- accessibility: null
  additionDate: '2017-01-17T14:51:18Z'
  biotoolsCURIE: biotools:proteinprospector
  biotoolsID: proteinprospector
  collectionID:
  - ms-utils
  - Proteomics
  confidence_flag: tool
  cost: null
  credit:
  - email: ppadmin@cgl.ucsf.edu
    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:
    authors:
    - proteomics.bio.tools
    - n.m.palmblad@lumc.nl
    type: group
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  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
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        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:
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      - name: Baker P.R.
      - name: Huang L.
      - name: Hansen K.C.
      - name: Allen N.P.
      - name: Rexach M.
      - name: Burlingame A.L.
      citationCount: 165
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        cells, time-of-flight mass spectrometer: II New developments in protein prospector
        allow for reliable and comprehensive automatic analysis of large datasets'
    note: null
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        [Figure not available: see fulltext.] © 2013 American Society for Mass Spectrometry.'
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      - name: Ivanov M.V.
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        engines; a large part of routine data processing is performed manually or
        with custom scripts that remain unpublished. Facilitating the development
        of reproducible data-processing workflows becomes essential for increasing
        the efficiency of proteomic research. To assist in overcoming the bioinformatics
        challenges in the daily practice of proteomic laboratories, 5 years ago we
        developed and announced Pyteomics, a freely available open-source library
        providing Python interfaces to proteomic data. We summarize the new functionality
        of Pyteomics developed during the time since its introduction.
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      - name: Klein J.A.
      - name: Ivanov M.V.
      - name: Gorshkov M.V.
      citationCount: 117
      date: '2019-02-01T00:00:00Z'
      journal: Journal of Proteome Research
      title: 'Pyteomics 4.0: Five Years of Development of a Python Proteomics Framework'
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    metadata:
      abstract: A statistical model is presented for computing probabilities that
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  description: The main focus lays on the integrated inference algorithms, concluding
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    url: https://hub.docker.com/r/julianusz/pia
    version: null
  editPermission:
    authors: []
    type: private
  elixirCommunity:
  - Proteomics
  elixirNode:
  - Germany
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Mass spectrometry spectra
        uri: http://edamontology.org/data_0943
      format:
      - term: Mascot .dat file
        uri: http://edamontology.org/format_3713
      - term: mzIdentML
        uri: http://edamontology.org/format_3247
      - term: TSV
        uri: http://edamontology.org/format_3475
      - term: PRIDE XML
        uri: http://edamontology.org/format_3684
      - term: X!Tandem XML
        uri: http://edamontology.org/format_3711
      - term: MSF
        uri: http://edamontology.org/format_3702
      - term: mzTab
        uri: http://edamontology.org/format_3681
    note: PIA allows you to inspect the results of common proteomics spectrum identification
      search engines, combine them seamlessly and conduct statistical analyses. The
      main focus of PIA lays on the integrated inference algorithms, i.e. concluding
      the proteins from a set of identified spectra. But it also allows you to inspect
      your peptide spectrum matches, calculate FDR values across different search
      engine results and visualize the correspondence between PSMs, peptides and proteins.
      Search engine results in several formats peptide spectrum matches (PSMs) and
      peptides Inferred Proteins
    operation:
    - term: Protein identification
      uri: http://edamontology.org/operation_3767
    - term: Target-Decoy
      uri: http://edamontology.org/operation_3649
    output:
    - data:
        term: Peptide identification
        uri: http://edamontology.org/data_0945
      format:
      - term: Sequence feature table format (text)
        uri: http://edamontology.org/format_2206
      - term: KNIME datatable format
        uri: http://edamontology.org/format_3765
      - term: idXML
        uri: http://edamontology.org/format_3764
      - term: TSV
        uri: http://edamontology.org/format_3475
      - term: mzTab
        uri: http://edamontology.org/format_3681
      - term: mzIdentML
        uri: http://edamontology.org/format_3247
    - data:
        term: Protein identifier
        uri: http://edamontology.org/data_0989
      format:
      - term: Sequence feature table format (text)
        uri: http://edamontology.org/format_2206
      - term: KNIME datatable format
        uri: http://edamontology.org/format_3765
      - term: idXML
        uri: http://edamontology.org/format_3764
      - term: TSV
        uri: http://edamontology.org/format_3475
      - term: mzTab
        uri: http://edamontology.org/format_3681
      - term: mzIdentML
        uri: http://edamontology.org/format_3247
  homepage: https://github.com/medbioinf/pia
  homepage_status: 0
  language:
  - Java
  lastUpdate: '2025-05-02T13:15:26.717477Z'
  license: BSD-3-Clause
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/medbioinf/pia
  maturity: Mature
  name: PIA - Protein Inference Algorithms
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: julianu
  publication:
  - doi: 10.1021/acs.jproteome.5b00121
    metadata:
      abstract: Protein inference connects the peptide spectrum matches (PSMs) obtained
        from database search engines back to proteins, which are typically at the
        heart of most proteomics studies. Different search engines yield different
        PSMs and thus different protein lists. Analysis of results from one or multiple
        search engines is often hampered by different data exchange formats and lack
        of convenient and intuitive user interfaces. We present PIA, a flexible software
        suite for combining PSMs from different search engine runs and turning these
        into consistent results. PIA can be integrated into proteomics data analysis
        workflows in several ways. A user-friendly graphical user interface can be
        run either locally or (e.g., for larger core facilities) from a central server.
        For automated data processing, stand-alone tools are available. PIA implements
        several established protein inference algorithms and can combine results from
        different search engines seamlessly. On several benchmark data sets, we show
        that PIA can identify a larger number of proteins at the same protein FDR
        when compared to that using inference based on a single search engine. PIA
        supports the majority of established search engines and data in the mzIdentML
        standard format. It is implemented in Java and freely available at https://github.com/mpc-bioinformatics/pia.
      authors:
      - name: Uszkoreit J.
      - name: Maerkens A.
      - name: Perez-Riverol Y.
      - name: Meyer H.E.
      - name: Marcus K.
      - name: Stephan C.
      - name: Kohlbacher O.
      - name: Eisenacher M.
      citationCount: 57
      date: '2015-07-02T00:00:00Z'
      journal: Journal of Proteome Research
      title: 'PIA: An Intuitive Protein Inference Engine with a Web-Based User Interface'
    note: null
    pmcid: null
    pmid: '25938255'
    type:
    - Primary
    version: null
  - doi: 10.1021/acs.jproteome.8b00723
    metadata:
      abstract: Proteomics using LC-MS/MS has become one of the main methods to analyze
        the proteins in biological samples in high-throughput. But the existing mass-spectrometry
        instruments are still limited with respect to resolution and measurable mass
        ranges, which is one of the main reasons why shotgun proteomics is the major
        approach. Here proteins are digested, which leads to the identification and
        quantification of peptides instead. While often neglected, the important step
        of protein inference needs to be conducted to infer from the identified peptides
        to the actual proteins in the original sample. In this work, we highlight
        some of the previously published and newly added features of the tool PIA
        - Protein Inference Algorithms, which helps the user with the protein inference
        of measured samples. We also highlight the importance of the usage of PSI
        standard file formats, as PIA is the only current software supporting all
        available standards used for spectrum identification and protein inference.
        Additionally, we briefly describe the benefits of working with workflow environments
        for proteomics analyses and show the new features of the PIA nodes for the
        KNIME Analytics Platform. Finally, we benchmark PIA against a recently published
        data set for isoform detection. PIA is open source and available for download
        on GitHub (https://github.com/mpc-bioinformatics/pia) or directly via the
        community extensions inside the KNIME analytics platform.
      authors:
      - name: Uszkoreit J.
      - name: Perez-Riverol Y.
      - name: Eggers B.
      - name: Marcus K.
      - name: Eisenacher M.
      citationCount: 30
      date: '2019-02-01T00:00:00Z'
      journal: Journal of Proteome Research
      title: Protein Inference Using PIA Workflows and PSI Standard File Formats
    note: null
    pmcid: null
    pmid: '30474983'
    type: []
    version: null
  relation:
  - biotoolsID: knime
    type: uses
  toolType:
  - Command-line tool
  - Library
  - Desktop application
  - Workflow
  topic:
  - term: Proteomics
    uri: http://edamontology.org/topic_0121
  - term: Proteomics experiment
    uri: http://edamontology.org/topic_3520
  - term: Protein variants
    uri: http://edamontology.org/topic_3120
  validated: 1
  version:
  - '1.5'
- accessibility: null
  additionDate: '2016-01-19T16:39:56Z'
  biotoolsCURIE: biotools:openms
  biotoolsID: openms
  collectionID:
  - KNIME
  - de.NBI
  - Proteomics
  - OpenMS
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: null
    fundrefid: null
    gridid: null
    name: ETH Zürich
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
    - Provider
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Eberhard-Karls-Universität Tübingen
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
    - Provider
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Freie Universität Berlin
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
    - Provider
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Center for Integrative Bioinformatics (CiBi)
    note: null
    orcidid: null
    rorid: null
    typeEntity: Consortium
    typeRole: []
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: cibi
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
    - Provider
    url: null
  - email: open-ms-general@lists.sourceforge.net
    fundrefid: null
    gridid: null
    name: General Mailinglist
    note: null
    orcidid: null
    rorid: null
    typeEntity: null
    typeRole:
    - Support
    url: null
  - email: open-ms-general@lists.sourceforge.net
    fundrefid: null
    gridid: null
    name: General Mailinglist
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Hannes Röst
    note: null
    orcidid: http://orcid.org/0000-0003-0990-7488
    rorid: null
    typeEntity: Person
    typeRole:
    - Contributor
    url: null
  description: Open source library and a collection of tools and interfaces for the
    analysis of mass spectrometry data. Includes over 200 standalone (TOPP) tools
    that can be combined to a workflow with the integrated workflow editor TOPPAS.
    Raw and intermediate mass spectrometry data can be visualised with the included
    viewer TOPPView.
  documentation:
  - note: null
    type:
    - General
    url: http://ftp.mi.fu-berlin.de/pub/OpenMS/release-documentation/html/index.html
  download:
  - note: null
    type: Source code
    url: https://github.com/OpenMS/OpenMS
    version: null
  - note: null
    type: Binaries
    url: http://sourceforge.net/projects/open-ms/files/OpenMS/OpenMS-2.0/
    version: null
  - note: null
    type: Source code
    url: https://github.com/OpenMS/OpenMS
    version: null
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  - cmd: null
    input:
    - data:
        term: Mass spectrometry data
        uri: http://edamontology.org/data_2536
      format:
      - term: pepXML
        uri: http://edamontology.org/format_3655
      - term: mzQuantML
        uri: http://edamontology.org/format_3248
      - term: dta
        uri: http://edamontology.org/format_3652
      - term: FASTA
        uri: http://edamontology.org/format_1929
      - term: protXML
        uri: http://edamontology.org/format_3747
      - term: idXML
        uri: http://edamontology.org/format_3764
      - term: OBO
        uri: http://edamontology.org/format_2549
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        uri: http://edamontology.org/format_2332
      - term: TraML
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      - term: mzML
        uri: http://edamontology.org/format_3244
      - term: mzIdentML
        uri: http://edamontology.org/format_3247
      - term: mzXML
        uri: http://edamontology.org/format_3654
      - term: MGF
        uri: http://edamontology.org/format_3651
      - term: qcML
        uri: http://edamontology.org/format_3683
    - data:
        term: Sequence record
        uri: http://edamontology.org/data_0849
      format:
      - term: pepXML
        uri: http://edamontology.org/format_3655
      - term: mzQuantML
        uri: http://edamontology.org/format_3248
      - term: dta
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      - term: FASTA
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      - term: protXML
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      - term: idXML
        uri: http://edamontology.org/format_3764
      - term: OBO
        uri: http://edamontology.org/format_2549
      - term: XML
        uri: http://edamontology.org/format_2332
      - term: TraML
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      - term: mzML
        uri: http://edamontology.org/format_3244
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      - term: MGF
        uri: http://edamontology.org/format_3651
      - term: qcML
        uri: http://edamontology.org/format_3683
    - data:
        term: Peptide identification
        uri: http://edamontology.org/data_0945
      format:
      - term: pepXML
        uri: http://edamontology.org/format_3655
      - term: mzQuantML
        uri: http://edamontology.org/format_3248
      - term: dta
        uri: http://edamontology.org/format_3652
      - term: FASTA
        uri: http://edamontology.org/format_1929
      - term: protXML
        uri: http://edamontology.org/format_3747
      - term: idXML
        uri: http://edamontology.org/format_3764
      - term: OBO
        uri: http://edamontology.org/format_2549
      - term: XML
        uri: http://edamontology.org/format_2332
      - term: TraML
        uri: http://edamontology.org/format_3246
      - term: mzML
        uri: http://edamontology.org/format_3244
      - term: mzIdentML
        uri: http://edamontology.org/format_3247
      - term: mzXML
        uri: http://edamontology.org/format_3654
      - term: MGF
        uri: http://edamontology.org/format_3651
      - term: qcML
        uri: http://edamontology.org/format_3683
    note: null
    operation:
    - term: Protein identification
      uri: http://edamontology.org/operation_3767
    - term: Parsing
      uri: http://edamontology.org/operation_1812
    - term: Data handling
      uri: http://edamontology.org/operation_2409
    - term: Chromatographic alignment
      uri: http://edamontology.org/operation_3628
    - term: Mass spectra calibration
      uri: http://edamontology.org/operation_3627
    - term: Formatting
      uri: http://edamontology.org/operation_0335
    - term: Protein quantification
      uri: http://edamontology.org/operation_3630
    - term: Retention time prediction
      uri: http://edamontology.org/operation_3633
    - term: Annotation
      uri: http://edamontology.org/operation_0226
    - term: Protein feature detection
      uri: http://edamontology.org/operation_3092
    - term: Isotope-coded protein label
      uri: http://edamontology.org/operation_3705
    - term: Label-free quantification
      uri: http://edamontology.org/operation_3634
    - term: iTRAQ
      uri: http://edamontology.org/operation_3639
    - term: Peptide identification
      uri: http://edamontology.org/operation_3631
    - term: Peak detection
      uri: http://edamontology.org/operation_3215
    - term: Mass spectrum visualisation
      uri: http://edamontology.org/operation_3694
    - term: Labeled quantification
      uri: http://edamontology.org/operation_3635
    - term: Splitting
      uri: http://edamontology.org/operation_3359
    - term: Spectral analysis
      uri: http://edamontology.org/operation_3214
    - term: Deisotoping
      uri: http://edamontology.org/operation_3629
    - term: Target-Decoy
      uri: http://edamontology.org/operation_3649
    - term: Prediction and recognition (protein)
      uri: http://edamontology.org/operation_3023
    - term: Comparison
      uri: http://edamontology.org/operation_2424
    - term: Standardisation and normalisation
      uri: http://edamontology.org/operation_3435
    output:
    - data:
        term: Peptide identification
        uri: http://edamontology.org/data_0945
      format:
      - term: pepXML
        uri: http://edamontology.org/format_3655
      - term: mzQuantML
        uri: http://edamontology.org/format_3248
      - term: dta
        uri: http://edamontology.org/format_3652
      - term: FASTA
        uri: http://edamontology.org/format_1929
      - term: idXML
        uri: http://edamontology.org/format_3764
      - term: mzXML
        uri: http://edamontology.org/format_3654
      - term: TraML
        uri: http://edamontology.org/format_3246
      - term: mzML
        uri: http://edamontology.org/format_3244
      - term: mzIdentML
        uri: http://edamontology.org/format_3247
      - term: MGF
        uri: http://edamontology.org/format_3651
      - term: qcML
        uri: http://edamontology.org/format_3683
    - data:
        term: Expression data
        uri: http://edamontology.org/data_2603
      format:
      - term: pepXML
        uri: http://edamontology.org/format_3655
      - term: mzQuantML
        uri: http://edamontology.org/format_3248
      - term: dta
        uri: http://edamontology.org/format_3652
      - term: FASTA
        uri: http://edamontology.org/format_1929
      - term: idXML
        uri: http://edamontology.org/format_3764
      - term: mzXML
        uri: http://edamontology.org/format_3654
      - term: TraML
        uri: http://edamontology.org/format_3246
      - term: mzML
        uri: http://edamontology.org/format_3244
      - term: mzIdentML
        uri: http://edamontology.org/format_3247
      - term: MGF
        uri: http://edamontology.org/format_3651
      - term: qcML
        uri: http://edamontology.org/format_3683
  homepage: http://www.openms.de
  homepage_status: 0
  language:
  - C++
  lastUpdate: '2025-04-30T11:39:30.251890Z'
  license: BSD-3-Clause
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/OpenMS/OpenMS
  maturity: Mature
  name: OpenMS
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: samwein
  publication:
  - doi: 10.1038/nmeth.3959
    metadata:
      abstract: © 2016 Nature America, Inc. All rights reserved.High-resolution mass
        spectrometry (MS) has become an important tool in the life sciences, contributing
        to the diagnosis and understanding of human diseases, elucidating biomolecular
        structural information and characterizing cellular signaling networks. However,
        the rapid growth in the volume and complexity of MS data makes transparent,
        accurate and reproducible analysis difficult. We present OpenMS 2.0 (http://www.openms.de),
        a robust, open-source, cross-platform software specifically designed for the
        flexible and reproducible analysis of high-throughput MS data. The extensible
        OpenMS software implements common mass spectrometric data processing tasks
        through a well-defined application programming interface in C++ and Python
        and through standardized open data formats. OpenMS additionally provides a
        set of 185 tools and ready-made workflows for common mass spectrometric data
        processing tasks, which enable users to perform complex quantitative mass
        spectrometric analyses with ease.
      authors:
      - name: Rost H.L.
      - name: Sachsenberg T.
      - name: Aiche S.
      - name: Bielow C.
      - name: Weisser H.
      - name: Aicheler F.
      - name: Andreotti S.
      - name: Ehrlich H.-C.
      - name: Gutenbrunner P.
      - name: Kenar E.
      - name: Liang X.
      - name: Nahnsen S.
      - name: Nilse L.
      - name: Pfeuffer J.
      - name: Rosenberger G.
      - name: Rurik M.
      - name: Schmitt U.
      - name: Veit J.
      - name: Walzer M.
      - name: Wojnar D.
      - name: Wolski W.E.
      - name: Schilling O.
      - name: Choudhary J.S.
      - name: Malmstrom L.
      - name: Aebersold R.
      - name: Reinert K.
      - name: Kohlbacher O.
      citationCount: 246
      date: '2016-08-30T00:00:00Z'
      journal: Nature Methods
      title: 'OpenMS: A flexible open-source software platform for mass spectrometry
        data analysis'
    note: null
    pmcid: null
    pmid: '27575624'
    type:
    - Primary
    version: null
  - doi: 10.1007/978-1-60761-987-1_23
    metadata:
      abstract: Proteomics experiments based on state-of-the-art mass spectrometry
        produce vast amounts of data, which cannot be analyzed manually. Hence, software
        is needed which is able to analyze the data in an automated fashion. The need
        for robust and reusable software tools triggered the development of libraries
        implementing different algorithms for the various analysis steps. OpenMS is
        such a software library and provides a wealth of data structures and algorithms
        for the analysis of mass spectrometric data. For users unfamiliar with programming,
        TOPP ("The OpenMS Proteomics Pipeline") offers a wide range of already implemented
        tools sharing the same interface and designed for a specific analysis task
        each. TOPP thus makes the sophisticated algorithms of OpenMS accessible to
        nonprogrammers. The individual TOPP tools can be strung together into pipelines
        for analyzing mass spectrometry-based experiments starting from the raw output
        of the mass spectrometer. These analysis pipelines can be constructed using
        a graphical editor. Even complex analytical workflows can thus be analyzed
        with ease.
      authors:
      - name: Bertsch A.
      - name: Gropl C.
      - name: Reinert K.
      - name: Kohlbacher O.
      citationCount: 65
      date: '2011-01-01T00:00:00Z'
      journal: Methods in molecular biology (Clifton, N.J.)
      title: 'OpenMS and TOPP: open source software for LC-MS data analysis.'
    note: null
    pmcid: null
    pmid: null
    type:
    - Other
    version: null
  relation: []
  toolType:
  - Library
  - Workbench
  topic:
  - term: Proteomics experiment
    uri: http://edamontology.org/topic_3520
  - term: Proteomics
    uri: http://edamontology.org/topic_0121
  - term: Metabolomics
    uri: http://edamontology.org/topic_3172
  validated: 1
  version:
  - 2.0.0
- accessibility: Open access
  additionDate: '2019-06-18T11:06:01Z'
  biotoolsCURIE: biotools:OpenSWATH
  biotoolsID: OpenSWATH
  collectionID:
  - ms-utils
  - Proteomics
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: hroest@stanford.edu
    fundrefid: null
    gridid: null
    name: Hannes Röst
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  - email: gr2578@cumc.columbia.edu
    fundrefid: null
    gridid: null
    name: George Rosenberger
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  description: OpenSWATH is a proteomics software that allows analysis of LC-MS/MS
    DIA (data independent acquisition) and implemented as part of OpenMS.
  documentation:
  - note: null
    type:
    - User manual
    url: https://buildmedia.readthedocs.org/media/pdf/openswath/latest/openswath.pdf
  download:
  - note: null
    type: Software package
    url: http://www.openswath.org/en/latest/docs/binaries.html
    version: null
  - note: null
    type: Source code
    url: http://www.openswath.org/en/latest/docs/sources.html
    version: null
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  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Experimental measurement
        uri: http://edamontology.org/data_3108
      format:
      - term: WIFF format
        uri: http://edamontology.org/format_3710
      - term: Mass spectrometry data format
        uri: http://edamontology.org/format_3245
    note: null
    operation:
    - term: Formatting
      uri: http://edamontology.org/operation_0335
    output:
    - data:
        term: Mass spectrometry data
        uri: http://edamontology.org/data_2536
      format:
      - term: mzML
        uri: http://edamontology.org/format_3244
      - term: SQLite format
        uri: http://edamontology.org/format_3621
      - term: mzXML
        uri: http://edamontology.org/format_3654
  - cmd: null
    input:
    - data:
        term: Mass spectrometry data
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      format:
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    output:
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      - term: TSV
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      - term: SQLite format
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  homepage: http://www.openswath.org
  homepage_status: 0
  language:
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  license: BSD-3-Clause
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  - doi: null
    metadata:
      abstract: ''
      authors:
      - name: Rost H.L.
      - name: Rosenberger G.
      - name: Navarro P.
      - name: Gillet L.
      - name: Miladinovia S.M.
      - name: Schubert O.T.
      - name: Wolski W.
      - name: Collins B.C.
      - name: Malmstrom J.
      - name: Malmstrom L.
      - name: Aebersold R.
      citationCount: 409
      date: '2014-01-01T00:00:00Z'
      journal: Nature Biotechnology
      title: OpenSWATH enables automated, targeted analysis of data-independent acquisition
        MS data
    note: null
    pmcid: null
    pmid: '24727770'
    type: []
    version: null
  relation: []
  toolType:
  - Command-line tool
  topic:
  - term: Proteomics
    uri: http://edamontology.org/topic_0121
  - term: Proteomics experiment
    uri: http://edamontology.org/topic_3520
  validated: 1
  version:
  - OpenMS 2.4.0
- accessibility: null
  additionDate: '2016-04-15T11:52:42Z'
  biotoolsCURIE: biotools:comparems2
  biotoolsID: comparems2
  collectionID:
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  - Proteomics
  confidence_flag: tool
  cost: Free of charge
  credit:
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    fundrefid: null
    gridid: null
    name: lumc.nl
    note: null
    orcidid: null
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    typeEntity: Institute
    typeRole:
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    url: https://www.lumc.nl
  - email: magnus.palmblad@gmail.com
    fundrefid: null
    gridid: null
    name: Magnus Palmblad
    note: null
    orcidid: http://orcid.org/0000-0002-5865-8994
    rorid: null
    typeEntity: Person
    typeRole:
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    - Primary contact
    - Documentor
    url: https://github.com/magnuspalmblad
  - email: null
    fundrefid: null
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    name: Rob Marissen
    note: null
    orcidid: https://orcid.org/0000-0002-1220-9173
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: https://github.com/524D
  description: compareMS2 is a tool for comparing sets of (tandem) mass spectra for
    clustering samples, molecular phylogenetics, identification of biological species
    or tissues, and quality control. compareMS2 currently consumes Mascot Generic
    Format, or MGF, and produces output in a variety of common image and distance
    matrix formats.
  documentation:
  - note: null
    type:
    - General
    - Command-line options
    url: http://www.ms-utils.org/compareMS2.html
  - note: null
    type:
    - General
    - User manual
    - Command-line options
    - Installation instructions
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    url: http://www.ms-utils.org/compareMS2.c
    version: '1.0'
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    url: https://github.com/524D/compareMS2/tree/main/src
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    url: https://github.com/524D/compareMS2/tree/main
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    note: null
    operation:
    - term: Comparison
      uri: http://edamontology.org/operation_2424
    - term: Phylogenetic tree visualisation
      uri: http://edamontology.org/operation_0567
    output:
    - data:
        term: Species tree
        uri: http://edamontology.org/data_3272
      format:
      - term: PNG
        uri: http://edamontology.org/format_3603
      - term: SVG
        uri: http://edamontology.org/format_3604
    - data:
        term: Distance matrix
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      format:
      - term: mega
        uri: http://edamontology.org/format_1991
      - term: Nexus format
        uri: http://edamontology.org/format_1912
      - term: newick
        uri: http://edamontology.org/format_1910
  homepage: https://github.com/524D/compareMS2
  homepage_status: 0
  language:
  - C
  - JavaScript
  lastUpdate: '2025-04-16T14:22:04.957317Z'
  license: MIT
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/524D/compareMS2
  - note: null
    type:
    - Software catalogue
    url: https://www.ms-utils.org/compareMS2.html
  - note: null
    type:
    - Software catalogue
    url: https://research-software-directory.org/software/comparems2
  maturity: Mature
  name: compareMS2
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  publication:
  - doi: 10.1002/rcm.6162
    metadata:
      abstract: 'Rationale: Molecular phylogenetics is the study of evolution and
        relatedness of organisms or genes. Mass spectrometry is used routinely for
        bacterial identification and has also been used for phylogenetic analysis,
        for instance from bone material. Unfortunately, only a small fraction of the
        acquired tandem mass spectra allow direct interpretation. Methods: We describe
        a new algorithm and software for molecular phylogenetics using pairwise comparisons
        of tandem mass spectra from enzymatically digested proteins. The spectra need
        not be annotated and all acquired data is used in the analysis. To demonstrate
        the method, we analyzed tryptic digests of sera from four great apes and two
        other primates. Results: The distribution of spectra dot products for thousands
        of tandem mass spectra collected from two samples provides a measure on the
        fraction of shared peptides between the two samples. When inverted, this becomes
        a distance metric. By pairwise comparison between species and averaging over
        four individuals per species, it was possible to reconstruct the unique correct
        phylogenetic tree for the great apes and other primates. Conclusions: The
        new method described here has several attractive features compared with existing
        methods, among them simplicity, the unbiased use of all acquired data rather
        than a small subset of spectra, and the potential use of heavily degraded
        proteins or proteins with a priori unknown modifications. © 2012 John Wiley
        & Sons, Ltd.'
      authors:
      - name: Palmblad M.
      - name: Deelder A.M.
      citationCount: 30
      date: '2012-04-15T00:00:00Z'
      journal: Rapid Communications in Mass Spectrometry
      title: Molecular phylogenetics by direct comparison of tandem mass spectra
    note: null
    pmcid: null
    pmid: '22368051'
    type:
    - Primary
    version: '1.0'
  - doi: 10.1021/acs.jproteome.2c00457
    metadata:
      abstract: It has long been known that biological species can be identified from
        mass spectrometry data alone. Ten years ago, we described a method and software
        tool, compareMS2, for calculating a distance between sets of tandem mass spectra,
        as routinely collected in proteomics. This method has seen use in species
        identification and mixture characterization in food and feed products, as
        well as other applications. Here, we present the first major update of this
        software, including a new metric, a graphical user interface and additional
        functionality. The data have been deposited to ProteomeXchange with dataset
        identifier PXD034932.
      authors:
      - name: Marissen R.
      - name: Varunjikar M.S.
      - name: Laros J.F.J.
      - name: Rasinger J.D.
      - name: Neely B.A.
      - name: Palmblad M.
      citationCount: 7
      date: '2023-02-03T00:00:00Z'
      journal: Journal of Proteome Research
      title: 'compareMS2 2.0: An Improved Software for Comparing Tandem Mass Spectrometry
        Datasets'
    note: null
    pmcid: PMC9903320
    pmid: '36173614'
    type:
    - Primary
    version: '2.0'
  - doi: 10.1021/acs.jproteome.1c00528
    metadata:
      abstract: Science is full of overlooked and undervalued research waiting to
        be rediscovered. Proteomics is no exception. In this perspective, we follow
        the ripples from a 1960 study of Zuckerkandl, Jones, and Pauling comparing
        tryptic peptides across animal species. This pioneering work directly led
        to the molecular clock hypothesis and the ensuing explosion in molecular phylogenetics.
        In the decades following, proteins continued to provide essential clues on
        evolutionary history. While technology has continued to improve, contemporary
        proteomics has strayed from this larger biological context, rarely comparing
        species or asking how protein structure, function, and interactions have evolved.
        Here we recombine proteomics with molecular phylogenetics, highlighting the
        value of framing proteomic results in a larger biological context and how
        almost forgotten research, though technologically surpassed, can still generate
        new ideas and illuminate our work from a different perspective. Though it
        is infeasible to read all research published on a large topic, looking up
        older papers can be surprisingly rewarding when rediscovering a "gem"at the
        end of a long citation chain, aided by digital collections and perpetually
        helpful librarians. Proper literature study reduces unnecessary repetition
        and allows research to be more insightful and impactful by truly standing
        on the shoulders of giants. All data was uploaded to MassIVE (https://massive.ucsd.edu/)
        as dataset MSV000087993.
      authors:
      - name: Neely B.A.
      - name: Palmblad M.
      citationCount: 1
      date: '2021-10-01T00:00:00Z'
      journal: Journal of Proteome Research
      title: 'Rewinding the Molecular Clock: Looking at Pioneering Molecular Phylogenetics
        Experiments in the Light of Proteomics'
    note: null
    pmcid: PMC8491155
    pmid: '34523928'
    type:
    - Review
    version: '2.0'
  relation: []
  toolType:
  - Command-line tool
  - Desktop application
  topic:
  - term: Phylogeny
    uri: http://edamontology.org/topic_0084
  - term: Proteomics
    uri: http://edamontology.org/topic_0121
  - term: Metabolomics
    uri: http://edamontology.org/topic_3172
  - term: Proteomics experiment
    uri: http://edamontology.org/topic_3520
  validated: 1
  version:
  - '1.0'
  - '2.0'
- accessibility: null
  additionDate: '2015-01-21T13:30:06Z'
  biotoolsCURIE: biotools:nextprot
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    name: SIB Swiss Institute of Bioinformatics
    note: null
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    name: Pascale Gaudet
    note: null
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    rorid: null
    typeEntity: Person
    typeRole:
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    url: null
  description: neXtProt was an innovative knowledge platform dedicated to human proteins.
    This resource contained a wealth of high-quality data on all the human proteins
    that are produced by the 20'000 protein-coding genes found in the human genome.
    The content of neXtProt was continuously extended so as to provide many more carefully
    selected data sets and analysis tools. neXtProt data and tools have been archived.
  documentation: []
  download: []
  editPermission:
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    note: null
    operation:
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    - term: Protein sequence analysis
      uri: http://edamontology.org/operation_2479
    - term: Query and retrieval
      uri: http://edamontology.org/operation_0224
    - term: Protein structure analysis
      uri: http://edamontology.org/operation_2406
    output: []
  homepage: https://www.expasy.org/archives/nextprot
  homepage_status: 0
  language: []
  lastUpdate: '2025-04-02T08:05:19.163091Z'
  license: CC-BY-4.0
  link:
  - note: neXtProt software repository with issue tracking
    type:
    - Repository
    url: https://github.com/calipho-sib/
  - note: neXtProt release news, publications, presentations, tips and more. DM us
      with feedback!
    type:
    - Social media
    url: https://twitter.com/nextprot_news
  - note: neXtProt entry in Expasy
    type:
    - Software catalogue
    url: https://www.expasy.org/resources/nextprot
  maturity: Legacy
  name: neXtProt
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: SIB
  publication:
  - doi: 10.1093/nar/gkz995
    metadata:
      abstract: The neXtProt knowledgebase (https://www.nextprot.org) is an integrative
        resource providing both data on human protein and the tools to explore these.
        In order to provide comprehensive and up-to-date data, we evaluate and add
        new data sets. We describe the incorporation of three new data sets that provide
        expression, function, protein-protein binary interaction, post-translational
        modifications (PTM) and variant information. New SPARQL query examples illustrating
        uses of the new data were added. neXtProt has continued to develop tools for
        proteomics. We have improved the peptide uniqueness checker and have implemented
        a new protein digestion tool. Together, these tools make it possible to determine
        which proteases can be used to identify trypsin-resistant proteins by mass
        spectrometry. In terms of usability, we have finished revamping our web interface
        and completely rewritten our API. Our SPARQL endpoint now supports federated
        queries. All the neXtProt data are available via our user interface, API,
        SPARQL endpoint and FTP site, including the new PEFF 1.0 format files. Finally,
        the data on our FTP site is now CC BY 4.0 to promote its reuse.
      authors:
      - name: Zahn-Zabal M.
      - name: Michel P.-A.
      - name: Gateau A.
      - name: Nikitin F.
      - name: Schaeffer M.
      - name: Audot E.
      - name: Gaudet P.
      - name: Duek P.D.
      - name: Teixeira D.
      - name: De Laval V.R.
      - name: Samarasinghe K.
      - name: Bairoch A.
      - name: Lane L.
      citationCount: 155
      date: '2020-01-01T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'The neXtProt knowledgebase in 2020: Data, tools and usability improvements'
    note: null
    pmcid: null
    pmid: '31724716'
    type:
    - Primary
    version: null
  - doi: 10.1093/nar/gkr1179
    metadata:
      abstract: neXtProt (http://www.nextprot.org/) is a new human protein-centric
        knowledge platform. Developed at the Swiss Institute of Bioinformatics (SIB),
        it aims to help researchers answer questions relevant to human proteins. To
        achieve this goal, neXtProt is built on a corpus containing both curated knowledge
        originating from the UniProtKB/Swiss-Prot knowledgebase and carefully selected
        and filtered high-throughput data pertinent to human proteins. This article
        presents an overview of the database and the data integration process. We
        also lay out the key future directions of neXtProt that we consider the necessary
        steps to make neXtProt the one-stop-shop for all research projects focusing
        on human proteins. © The Author(s) 2011.
      authors:
      - name: Lane L.
      - name: Argoud-Puy G.
      - name: Britan A.
      - name: Cusin I.
      - name: Duek P.D.
      - name: Evalet O.
      - name: Gateau A.
      - name: Gaudet P.
      - name: Gleizes A.
      - name: Masselot A.
      - name: Zwahlen C.
      - name: Bairoch A.
      citationCount: 168
      date: '2012-01-01T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'NeXtProt: A knowledge platform for human proteins'
    note: null
    pmcid: PMC3245017
    pmid: '22139911'
    type:
    - Primary
    version: null
  relation: []
  toolType:
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  topic:
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    uri: http://edamontology.org/topic_0621
  - term: Proteomics
    uri: http://edamontology.org/topic_0121
  - term: Proteins
    uri: http://edamontology.org/topic_0078
  - term: Protein modifications
    uri: http://edamontology.org/topic_0601
  - term: Protein variants
    uri: http://edamontology.org/topic_3120
  - term: Rare diseases
    uri: http://edamontology.org/topic_3325
  validated: 1
  version: []
- accessibility: null
  additionDate: '2015-09-11T17:01:36Z'
  biotoolsCURIE: biotools:2d-page
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  collectionID:
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  - Proteomics
  confidence_flag: null
  cost: null
  credit:
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    fundrefid: null
    gridid: null
    name: University of Siena, Italy
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
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    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: DRCAT
    note: null
    orcidid: null
    rorid: null
    typeEntity: Project
    typeRole:
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    url: null
  - email: bini@unisi.it
    fundrefid: null
    gridid: null
    name: Luca Bini
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
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    url: null
  description: 2D-PAGE database.
  documentation:
  - note: null
    type:
    - General
    url: http://www.bio-mol.unisi.it/cgi-bin/2d/2d.cgi
  download: []
  editPermission:
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    type: group
  elixirCommunity: []
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  function:
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    input:
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      format: []
    - data:
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        uri: http://edamontology.org/data_2373
      format: []
    - data:
        term: Accession
        uri: http://edamontology.org/data_2091
      format: []
    - data:
        term: Peptide molecular weights
        uri: http://edamontology.org/data_1519
      format: []
    - data:
        term: Protein isoelectric point
        uri: http://edamontology.org/data_1528
      format: []
    note: 'This is the main interface of the Make2D-DB II tool to query SIENA 2D-DATABASE.
      Search by accession number or entry name (AC or ID),

      by description, or UniProtKB/Swiss-Prot keywords. General information, 2D-gel
      spot location and picture of gel.'
    operation:
    - term: Query and retrieval
      uri: http://edamontology.org/operation_0224
    output:
    - data:
        term: Protein property
        uri: http://edamontology.org/data_0897
      format:
      - term: HTML
        uri: http://edamontology.org/format_2331
    - data:
        term: 2D PAGE image
        uri: http://edamontology.org/data_0942
      format: []
    - data:
        term: Protein isoelectric point
        uri: http://edamontology.org/data_1528
      format: []
  homepage: http://www.bio-mol.unisi.it/cgi-bin/2d/2d.cgi
  homepage_status: 0
  language: []
  lastUpdate: '2024-11-25T14:17:26.650772Z'
  license: null
  link: []
  maturity: null
  name: 2D-PAGE
  operatingSystem:
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  - Mac
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  owner: DRCAT
  publication:
  - doi: 10.1002/pmic.200300483
    metadata:
      abstract: The Make 2D-DB tool has been previously developed to help build federated
        two-dimensional gel electrophoresis (2-DE) databases on one's own web site.
        The purpose of our work is to extend the strength of the first package and
        to build a more efficient environment. Such an environment should be able
        to fulfill the different needs and requirements arising from both the growing
        use of 2-DE techniques and the increasing amount of distributed experimental
        data.
      authors:
      - name: Mostaguir K.
      - name: Hoogland C.
      - name: Binz P.-A.
      - name: Appel R.D.
      citationCount: 27
      date: '2003-08-01T00:00:00Z'
      journal: Proteomics
      title: 'The Make 2D-DB II package: Conversion of federated two-dimensional gel
        electrophoresis databases into a relational format and interconnection of
        distributed databases'
    note: null
    pmcid: null
    pmid: '12923769'
    type:
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    version: null
  relation: []
  toolType:
  - Database portal
  topic:
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    uri: http://edamontology.org/topic_0121
  validated: 1
  version: []
- accessibility: null
  additionDate: '2017-02-14T09:34:42Z'
  biotoolsCURIE: biotools:3dlogo
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  collectionID:
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  confidence_flag: null
  cost: null
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  description: 3dLOGO is a server for the identification and analysis of conserved
    protein three-dimensional (3D) substructures.
  documentation: []
  download: []
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  function:
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    input: []
    note: null
    operation:
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      uri: http://edamontology.org/operation_0448
    - term: Protein structural motif recognition
      uri: http://edamontology.org/operation_0245
    - term: Protein identification
      uri: http://edamontology.org/operation_3767
    - term: Protein sequence analysis
      uri: http://edamontology.org/operation_2479
    - term: Protein structure analysis
      uri: http://edamontology.org/operation_2406
    output: []
  homepage: http://3dlogo.uniroma2.it/3dLOGO/home.html
  homepage_status: 0
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  publication:
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    metadata:
      abstract: 3dLOGO is a web server for the identification and analysis of conserved
        protein 3D substructures. Given a set of residues in a PDB (Protein Data Bank)
        chain, the server detects the matching substructure(s) in a set of user-provided
        protein structures, generates a multiple structure alignment centered on the
        input substructures and highlights other residues whose structural conservation
        becomes evident after the defined superposition. Conserved residues are proposed
        to the user for highlighting functional areas, deriving refined structural
        motifs or building sequence patterns. Residue structural conservation can
        be visualized through an expressly designed Java application, 3dProLogo, which
        is a 3D implementation of a sequence logo. The 3dLOGO server, with related
        documentation, is available at http://3dlogo.uniroma2.it/. © 2007 The Author(s).
      authors:
      - name: Via A.
      - name: Peluso D.
      - name: Gherardini P.F.
      - name: De Rinaldis E.
      - name: Colombo T.
      - name: Ausiello G.
      - name: Helmer-Citterich M.
      citationCount: 6
      date: '2007-07-01T00:00:00Z'
      journal: Nucleic Acids Research
      title: '3dLOGO: A web server for the identification, analysis and use of conserved
        protein substructures'
    note: null
    pmcid: PMC1933223
    pmid: '17488847'
    type: []
    version: null
  - doi: 10.1006/jmbi.1998.2248
    metadata:
      abstract: We report a procedure for the description and comparison of protein
        surfaces, which is based on a three-dimensional (3D) transposition of the
        profile method for sensitive protein homology sequence searches. Although
        the principle of the method can be applied to detect similarities to a single
        protein surface, the possibility of extending this approach to protein families
        displaying common structural and/or functional properties, makes it a more
        powerful tool. In analogy to profiles derived from the multiple alignment
        of protein sequences, we derive a 3D surface profile from a protein structure
        or from a multiple structure alignment of several proteins. The 3D profile
        is used to screen the protein structure database, searching for similar protein
        surfaces. The application of the procedure to SH2 and SH3 binding pockets
        and to the nucleotide binding pocket associated with the p-loop structural
        motif is described. The SH2 and SH3 3D profiles can identify all the SH2 and
        SH3 binding regions present in the test dataset; the p-loop 3D profile is
        able to recognize all the p-loop-containing proteins present in the test dataset.
        Analysis of the p-loop 3D profile allowed the identification of a positive
        charge whose position is conserved in space but not in sequence. The best
        ranking non-p-loop-containing protein is an ADP-forming succinyl coenzyme
        A synthetase, whose nucleotide-binding region has not yet been identified.
      authors:
      - name: De Rinaldis M.
      - name: Ausiello G.
      - name: Cesareni G.
      - name: Helmer-Citterich M.
      citationCount: 42
      date: '1998-12-11T00:00:00Z'
      journal: Journal of Molecular Biology
      title: 'Three-dimensional profiles: A new tool to identify protein surface similarities'
    note: null
    pmcid: null
    pmid: '9837739'
    type: []
    version: null
  - doi: 10.1186/1471-2105-5-50
    metadata:
      abstract: 'Background. A large number of PROSITE patterns select false positives
        and/or miss known true positives. It is possible that - at least in some cases
        - the weak specificity and/or sensitivity of a pattern is due to the fact
        that one, or maybe more, functional and/or structural key residues are not
        represented in the pattern. Multiple sequence alignments are commonly used
        to build functional sequence patterns. If residues structurally conserved
        in proteins sharing a function cannot be aligned in a multiple sequence alignment,
        they are likely to be missed in a standard pattern construction procedure.
        Results. Here we present a new procedure aimed at improving the sensitivity
        and/ or specificity of poorly-performing patterns. The procedure can be summarised
        as follows: 1. residues structurally conserved in different proteins, that
        are true positives for a pattern, are identified by means of a computational
        technique and by visual inspection. 2. the sequence positions of the structurally
        conserved residues falling outside the pattern are used to build extended
        sequence patterns. 3. the extended patterns are optimised on the SWISS-PROT
        database for their sensitivity and specificity. The method was applied to
        eight PROSITE patterns. Whenever structurally conserved residues are found
        in the surface region close to the pattern (seven out of eight cases), the
        addition of information inferred from structural analysis is shown to improve
        pattern selectivity and in some cases selectivity and sensitivity as well.
        In some of the cases considered the procedure allowed the identification of
        functionally interesting residues, whose biological role is also discussed.
        Conclusion. Our method can be applied to any type of functional motif or pattern
        (not only PROSITE ones) which is not able to select all and only the true
        positive hits and for which at least two true positive structures are available.
        The computational technique for the identification of structurally conserved
        residues is already available on request and will be soon accessible on our
        web server. The procedure is intended for the use of pattern database curators
        and of scientists interested in a specific protein family for which no specific
        or selective patterns are yet available. © 2004 Via and Helmer-Citterich,
        licensee BioMed Central Ltd.'
      authors:
      - name: Via A.
      - name: Helmer-Citterich M.
      citationCount: 7
      date: '2004-04-30T00:00:00Z'
      journal: BMC Bioinformatics
      title: A structural study for the optimisation of functional motifs encoded
        in protein sequences
    note: null
    pmcid: PMC420233
    pmid: '15119965'
    type: []
    version: null
  - doi: 10.1186/1471-2105-6-s4-s5
    metadata:
      abstract: 'Background: The identification of local similarities between two
        protein structures can provide clues of a common function. Many different
        methods exist for searching for similar subsets of residues in proteins of
        known structure. However, the lack of functional and structural information
        on single residues, together with the low level of integration of this information
        in comparison methods, is a limitation that prevents these methods from being
        fully exploited in high-throughput analyses. Results: Here we describe Query3d,
        a program that is both a structural DBMS (Database Management System) and
        a local comparison method. The method conserves a copy of all the residues
        of the Protein Data Bank annotated with a variety of functional and structural
        information. New annotations can be easily added from a variety of methods
        and known databases. The algorithm makes it possible to create complex queries
        based on the residues'' function and then to compare only subsets of the selected
        residues. Functional information is also essential to speed up the comparison
        and the analysis of the results. Conclusion: With Query3d, users can easily
        obtain statistics on how many and which residues share certain properties
        in all proteins of known structure. At the same time, the method also finds
        their structural neighbours in the whole PDB. Programs and data can be accessed
        through the PdbFun web interface.'
      authors:
      - name: Ausiello G.
      - name: Via A.
      - name: Helmer-Citterich M.
      citationCount: 50
      date: '2005-12-01T00:00:00Z'
      journal: BMC Bioinformatics
      title: 'Query3d: A new method for high-throughput analysis of functional residues
        in protien structures'
    note: null
    pmcid: PMC1866380
    pmid: '16351754'
    type: []
    version: null
  relation: []
  toolType:
  - Web application
  topic:
  - term: Protein structural motifs and surfaces
    uri: http://edamontology.org/topic_0166
  - term: Proteins
    uri: http://edamontology.org/topic_0078
  - term: Proteomics
    uri: http://edamontology.org/topic_0121
  validated: 1
  version: []
- accessibility: null
  additionDate: '2018-08-17T19:04:18Z'
  biotoolsCURIE: biotools:3omics
  biotoolsID: 3omics
  collectionID:
  - Proteomics
  confidence_flag: null
  cost: null
  credit:
  - email: yjtseng@csie.ntu.edu.tw
    fundrefid: null
    gridid: null
    name: Yufeng Jane Tseng
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  description: A web based systems biology visualization tool for integrating human
    transcriptomic, proteomic and metabolomic data.
  documentation:
  - note: null
    type:
    - General
    url: https://3omics.cmdm.tw/help.php
  download: []
  editPermission:
    authors:
    - proteomics.bio.tools
    type: group
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Sequence analysis
      uri: http://edamontology.org/operation_2403
    - term: Genome visualisation
      uri: http://edamontology.org/operation_3208
    output: []
  homepage: https://3omics.cmdm.tw/
  homepage_status: 0
  language:
  - PHP
  - Perl
  lastUpdate: '2024-11-25T14:17:20.979256Z'
  license: null
  link: []
  maturity: null
  name: 3Omics
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: d.gabrielaitis
  publication:
  - doi: 10.1186/1752-0509-7-64
    metadata:
      abstract: 'Background: Integrative and comparative analyses of multiple transcriptomics,
        proteomics and metabolomics datasets require an intensive knowledge of tools
        and background concepts. Thus, it is challenging for users to perform such
        analyses, highlighting the need for a single tool for such purposes. The 3Omics
        one-click web tool was developed to visualize and rapidly integrate multiple
        human inter- or intra-transcriptomic, proteomic, and metabolomic data by combining
        five commonly used analyses: correlation networking, coexpression, phenotyping,
        pathway enrichment, and GO (Gene Ontology) enrichment.Results: 3Omics generates
        inter-omic correlation networks to visualize relationships in data with respect
        to time or experimental conditions for all transcripts, proteins and metabolites.
        If only two of three omics datasets are input, then 3Omics supplements the
        missing transcript, protein or metabolite information related to the input
        data by text-mining the PubMed database. 3Omics'' coexpression analysis assists
        in revealing functions shared among different omics datasets. 3Omics'' phenotype
        analysis integrates Online Mendelian Inheritance in Man with available transcript
        or protein data. Pathway enrichment analysis on metabolomics data by 3Omics
        reveals enriched pathways in the KEGG/HumanCyc database. 3Omics performs statistical
        Gene Ontology-based functional enrichment analyses to display significantly
        overrepresented GO terms in transcriptomic experiments. Although the principal
        application of 3Omics is the integration of multiple omics datasets, it is
        also capable of analyzing individual omics datasets. The information obtained
        from the analyses of 3Omics in Case Studies 1 and 2 are also in accordance
        with comprehensive findings in the literature.Conclusions: 3Omics incorporates
        the advantages and functionality of existing software into a single platform,
        thereby simplifying data analysis and enabling the user to perform a one-click
        integrated analysis. Visualization and analysis results are downloadable for
        further user customization and analysis. The 3Omics software can be freely
        accessed at http://3omics.cmdm.tw. © 2013 Kuo et al.; licensee BioMed Central
        Ltd.'
      authors:
      - name: Kuo T.-C.
      - name: Tian T.-F.
      - name: Tseng Y.J.
      citationCount: 148
      date: '2013-07-13T00:00:00Z'
      journal: BMC Systems Biology
      title: '3Omics: A web-based systems biology tool for analysis, integration and
        visualization of human transcriptomic, proteomic and metabolomic data'
    note: null
    pmcid: PMC3723580
    pmid: '23875761'
    type: []
    version: null
  relation: []
  toolType:
  - Web application
  topic:
  - term: Systems biology
    uri: http://edamontology.org/topic_2259
  - term: Transcriptomics
    uri: http://edamontology.org/topic_3308
  - term: Human biology
    uri: http://edamontology.org/topic_2815
  - term: Proteomics
    uri: http://edamontology.org/topic_0121
  - term: Metabolomics
    uri: http://edamontology.org/topic_3172
  - term: Data visualisation
    uri: http://edamontology.org/topic_0092
  - term: Data visualisation
    uri: http://edamontology.org/topic_0092
  validated: 1
  version: []
- accessibility: null
  additionDate: '2017-08-03T18:35:34Z'
  biotoolsCURIE: biotools:adepts
  biotoolsID: adepts
  collectionID:
  - Proteomics
  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: https://cs.uwaterloo.ca/~l22he/
  description: Software package for peptide identification using two different types
    of MS/MS spectra.
  documentation: []
  download: []
  editPermission:
    authors:
    - proteomics.bio.tools
    type: group
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Peptide identification
      uri: http://edamontology.org/operation_3631
    output: []
  homepage: https://cs.uwaterloo.ca/~l22he/
  homepage_status: 0
  language: []
  lastUpdate: '2024-11-25T14:17:19.618187Z'
  license: null
  link:
  - note: null
    type:
    - Software catalogue
    url: http://www.mybiosoftware.com/adepts-advanced-peptide-de-novo-sequencing-with-a-pair-of-tandem-mass-spectra.html
  maturity: null
  name: ADEPTS
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: mbs_import
  publication:
  - doi: 10.1142/s0219720010005099
    metadata:
      abstract: De novo sequencing is an important task in proteomics to identify
        novel peptide sequences. Traditionally, only one MS/MS spectrum is used for
        the sequencing of a peptide; however, the use of multiple spectra of the same
        peptide with different types of fragmentation has the potential to significantly
        increase the accuracy and practicality of de novo sequencing. Research into
        the use of multiple spectra is in a nascent stage. We propose a general framework
        to combine the two different types of MS/MS data. Experiments demonstrate
        that our method significantly improves the de novo sequencing of existing
        software. © 2010 Imperial College Press.
      authors:
      - name: He L.
      - name: Ma B.
      citationCount: 29
      date: '2010-12-01T00:00:00Z'
      journal: Journal of Bioinformatics and Computational Biology
      title: 'Adepts: Advanced peptide de novo sequencing with a pair of tandem mass
        spectra'
    note: null
    pmcid: null
    pmid: '21121022'
    type: []
    version: null
  relation: []
  toolType:
  - Command-line tool
  topic:
  - term: Proteomics
    uri: http://edamontology.org/topic_0121
  - term: Proteomics experiment
    uri: http://edamontology.org/topic_3520
  validated: 1
  version: []
- accessibility: null
  additionDate: '2017-08-03T18:35:41Z'
  biotoolsCURIE: biotools:all-p
  biotoolsID: all-p
  collectionID:
  - Proteomics
  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.inra.fr/les_recherches/annuaires/autres/microbiologie/pappso_plate_forme_d_analyses_proteomiques_de_paris_sud_ouest
  description: Statistical framework based on a hierarchical modeling that takes into
    account shared peptide information for estimating protein abundances. It performs
    a simultaneous analysis of all the quantified peptides, handling the biological
    and technical errors as well as the peptide effect.
  documentation:
  - note: null
    type:
    - General
    url: http://pappso.inra.fr/bioinfo/all_p/download.php
  download: []
  editPermission:
    authors:
    - proteomics.bio.tools
    type: group
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Prediction and recognition
      uri: http://edamontology.org/operation_2423
    - term: Protein quantification
      uri: http://edamontology.org/operation_3630
    - term: Protein structure analysis
      uri: http://edamontology.org/operation_2406
    output: []
  homepage: http://pappso.inra.fr/bioinfo/all_p/index.php
  homepage_status: 0
  language: []
  lastUpdate: '2024-11-25T14:17:18.441827Z'
  license: null
  link:
  - note: null
    type:
    - Software catalogue
    url: http://www.mybiosoftware.com/all-p-including-shared-peptides-estimating-protein-abundances.html
  maturity: null
  name: ALL-P
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: mbs_import
  publication:
  - doi: 10.1002/pmic.201100660
    metadata:
      abstract: Inferring protein abundances from peptide intensities is the key step
        in quantitative proteomics. The inference is necessarily more accurate when
        many peptides are taken into account for a given protein. Yet, the information
        brought by the peptides shared by different proteins is commonly discarded.
        We propose a statistical framework based on a hierarchical modeling to include
        that information. Our methodology, based on a simultaneous analysis of all
        the quantified peptides, handles the biological and technical errors as well
        as the peptide effect. In addition, we propose a practical implementation
        suitable for analyzing large data sets. Compared to a method based on the
        analysis of one protein at a time (that does not include shared peptides),
        our methodology proved to be far more reliable for estimating protein abundances
        and testing abundance changes. The source codes are available at http://pappso.inra.fr/bioinfo/all_p/.
        © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
      authors:
      - name: Blein-Nicolas M.
      - name: Xu H.
      - name: de Vienne D.
      - name: Giraud C.
      - name: Huet S.
      - name: Zivy M.
      citationCount: 19
      date: '2012-09-01T00:00:00Z'
      journal: Proteomics
      title: 'Including shared peptides for estimating protein abundances: A significant
        improvement for quantitative proteomics'
    note: null
    pmcid: null
    pmid: '22833229'
    type: []
    version: null
  relation: []
  toolType:
  - Command-line tool
  topic:
  - term: Molecular genetics
    uri: http://edamontology.org/topic_3321
  - term: Proteomics
    uri: http://edamontology.org/topic_0121
  validated: 1
  version: []
- accessibility: null
  additionDate: '2017-08-03T18:35:47Z'
  biotoolsCURIE: biotools:amylpred
  biotoolsID: amylpred
  collectionID:
  - Proteomics
  confidence_flag: null
  cost: null
  credit:
  - email: shamodr@biol.uoa.gr
    fundrefid: null
    gridid: null
    name: null
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: http://biophysics.biol.uoa.gr/
  description: Consensus prediction method for identifying possible amyloidogenic
    regions in protein sequences.
  documentation:
  - note: null
    type:
    - General
    url: http://aias.biol.uoa.gr/AMYLPRED/login.php
  download: []
  editPermission:
    authors:
    - proteomics.bio.tools
    type: group
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Protein sequence analysis
      uri: http://edamontology.org/operation_2479
    output: []
  - cmd: null
    input: []
    note: null
    operation:
    - term: Protein post-translation modification site prediction
      uri: http://edamontology.org/operation_0417
    output: []
  homepage: http://aias.biol.uoa.gr/AMYLPRED/
  homepage_status: 0
  language:
  - Python
  lastUpdate: '2024-11-25T14:17:16.586759Z'
  license: null
  link:
  - note: null
    type:
    - Software catalogue
    url: http://www.mybiosoftware.com/amylpred-a-consensus-method-for-amyloid-propensity-prediction.html
  maturity: null
  name: AMYLPRED
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: mbs_import
  publication:
  - doi: 10.1186/1472-6807-9-44
    metadata:
      abstract: 'Background. Amyloidoses are a group of usually fatal diseases, probably
        caused by protein misfolding and subsequent aggregation into amyloid fibrillar
        deposits. The mechanisms involved in amyloid fibril formation are largely
        unknown and are the subject of current, intensive research. In an attempt
        to identify possible amyloidogenic regions in proteins for further experimental
        investigation, we have developed and present here a publicly available online
        tool that utilizes five different and independently published methods, to
        form a consensus prediction of amyloidogenic regions in proteins, using only
        protein primary structure data. Results. It appears that the consensus prediction
        tool is slightly more objective than individual prediction methods alone and
        suggests several previously not identified amino acid stretches as potential
        amyloidogenic determinants, which (although several of them may be overpredictions)
        require further experimental studies. The tool is available at: http://biophysics.biol.uoa.gr/AMYLPRED.
        Utilizing molecular graphics programs, like O and PyMOL, as well as the algorithm
        DSSP, it was found that nearly all experimentally verified amyloidogenic determinants
        (short peptide stretches favouring aggregation and subsequent amyloid formation),
        and several predicted, with the aid of the tool AMYLPRED, but not experimentally
        verified amyloidogenic determinants, are located on the surface of the relevant
        amyloidogenic proteins. This finding may be important in efforts directed
        towards inhibiting amyloid fibril formation. Conclusion. The most significant
        result of this work is the observation that virtually all, to date, experimentally
        determined amyloidogenic determinants and the majority of predicted, but not
        yet experimentally verified short amyloidogenic stretches, lie ''exposed''
        on the surface of the relevant amyloidogenic proteins, and also several of
        them have the ability to act as conformational ''switches''. Experiments,
        focused on these fragments, should be performed to test this idea. © 2009
        Frousios et al; licensee BioMed Central Ltd.'
      authors:
      - name: Frousios K.K.
      - name: Iconomidou V.A.
      - name: Karletidi C.-M.
      - name: Hamodrakas S.J.
      citationCount: 128
      date: '2009-07-30T00:00:00Z'
      journal: BMC Structural Biology
      title: Amyloidogenic determinants are usually not buried
    note: null
    pmcid: PMC2714319
    pmid: '19589171'
    type: []
    version: null
  relation: []
  toolType:
  - Web application
  topic:
  - term: Proteomics
    uri: http://edamontology.org/topic_0121
  - term: Structure analysis
    uri: http://edamontology.org/topic_0081
  validated: 1
  version: []
- accessibility: null
  additionDate: '2017-08-03T18:35:48Z'
  biotoolsCURIE: biotools:anarci
  biotoolsID: anarci
  collectionID:
  - Proteomics
  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://opig.stats.ox.ac.uk/
  description: Tool for numbering amino-acid sequences of antibody and T-cell receptor
    variable domains.
  documentation:
  - note: null
    type:
    - General
    url: http://opig.stats.ox.ac.uk/webapps/sabdab-sabpred/ANARCI.php
  download: []
  editPermission:
    authors:
    - proteomics.bio.tools
    type: group
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Protein sequence analysis
      uri: http://edamontology.org/operation_2479
    output: []
  - cmd: null
    input: []
    note: null
    operation:
    - term: Protein binding site prediction
      uri: http://edamontology.org/operation_2575
    output: []
  homepage: http://opig.stats.ox.ac.uk/webapps/sabdab-sabpred/ANARCI.php
  homepage_status: 0
  language:
  - Python
  lastUpdate: '2024-11-25T14:17:15.343704Z'
  license: null
  link:
  - note: null
    type:
    - Software catalogue
    url: http://www.mybiosoftware.com/anarci-antigen-receptor-numbering-and-receptor-classification.html
  maturity: null
  name: ANARCI
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: mbs_import
  publication:
  - doi: 10.1093/bioinformatics/btv552
    metadata:
      abstract: 'Motivation: Antibody amino-acid sequences can be numbered to identify
        equivalent positions. Such annotations are valuable for antibody sequence
        comparison, protein structure modelling and engineering. Multiple different
        numbering schemes exist, they vary in the nomenclature they use to annotate
        residue positions, their definitions of position equivalence and their popularity
        within different scientific disciplines. However, currently no publicly available
        software exists that can apply all the most widely used schemes or for which
        an executable can be obtained under an open license. Results: ANARCI is a
        tool to classify and number antibody and T-cell receptor amino-acid variable
        domain sequences. It can annotate sequences with the five most popular numbering
        schemes: Kabat, Chothia, Enhanced Chothia, IMGT and AHo. Availability and
        implementation: ANARCI is available for download under GPLv3 license at opig.stats.ox.ac.uk/webapps/anarci.
        A web-interface to the program is available at the same address. Contact:'
      authors:
      - name: Dunbar J.
      - name: Deane C.M.
      citationCount: 193
      date: '2016-01-15T00:00:00Z'
      journal: Bioinformatics
      title: 'ANARCI: Antigen receptor numbering and receptor classification'
    note: null
    pmcid: PMC4708101
    pmid: '26424857'
    type: []
    version: null
  relation: []
  toolType:
  - Web application
  - Desktop application
  topic:
  - term: Proteomics
    uri: http://edamontology.org/topic_0121
  - term: Protein structure analysis
    uri: http://edamontology.org/topic_2814
  validated: 1
  version: []
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  additionDate: '2017-08-03T18:36:20Z'
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    name: Dominik Schaack & Steffen Schmidt
    note: null
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    typeEntity: Person
    typeRole:
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    url: http://www.bork.embl.de/
  description: Web tool that helps to assign structural domains to protein sequences
    and to classify them according to SCOP.
  documentation:
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    type:
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    url: http://andom.bioapps.biozentrum.uni-wuerzburg.de/Usage_new.html
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  homepage: http://andom.bioapps.biozentrum.uni-wuerzburg.de/index_new.html
  homepage_status: 0
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  lastUpdate: '2024-11-25T14:17:13.978877Z'
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  maturity: null
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  publication:
  - doi: 10.1021/ci010374r
    metadata:
      abstract: The WEB tool "AnDom" assigns to a given protein sequence all experimentally
        determined structural domains contained within it, including multidomain and
        large proteins. The server uses profile specific matrices from custom generated
        multiple sequence alignments of all known SCOP domains (SCOP version 1.50).
        Prediction time is short allowing numerous applications for structural genomics
        including investigation of complex eucaryotic protein families. The WWW server
        is at http://www.bork.embl-heidelberg.de/AnDom, and profiles can be downloaded
        at ftp.bork.embl-heidelberg.de/pub/users/schmidt/AnDom.
      authors:
      - name: Schmidt S.
      - name: Bork P.
      - name: Dandekar T.
      citationCount: 14
      date: '2002-03-01T00:00:00Z'
      journal: Journal of Chemical Information and Computer Sciences
      title: A versatile structural domain analysis server using profile weight matrices
    note: null
    pmcid: null
    pmid: '11911710'
    type: []
    version: null
  relation: []
  toolType:
  - Web application
  topic:
  - term: Proteomics
    uri: http://edamontology.org/topic_0121
  - term: Proteins
    uri: http://edamontology.org/topic_0078
  - term: Protein folds and structural domains
    uri: http://edamontology.org/topic_0736
  validated: 1
  version: []
- accessibility: null
  additionDate: '2017-08-03T18:35:49Z'
  biotoolsCURIE: biotools:anm
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    typeEntity: Person
    typeRole:
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    url: http://www.csb.pitt.edu/
  description: Simple NMA tool for analysis of vibrational motions in molecular systems.
    It uses Elastic Network (EN) methodology and represents the  system in the residue
    level.
  documentation:
  - note: null
    type:
    - General
    url: http://anm.csb.pitt.edu/anmdocs/Documentation2.1.html
  download: []
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  function:
  - cmd: null
    input: []
    note: null
    operation:
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      uri: http://edamontology.org/operation_0477
    - term: Molecular dynamics simulation
      uri: http://edamontology.org/operation_2476
    - term: Protein structure analysis
      uri: http://edamontology.org/operation_2406
    output: []
  homepage: http://anm.csb.pitt.edu/
  homepage_status: 0
  language:
  - MATLAB
  - Perl
  - C
  lastUpdate: '2024-11-25T14:17:12.623733Z'
  license: null
  link:
  - note: null
    type:
    - Software catalogue
    url: http://www.mybiosoftware.com/anm-2-0-aanm-1-1-adaptive-anisotropic-network-model-web-server.html
  maturity: null
  name: ANM
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  publication:
  - doi: 10.1093/bioinformatics/btu847
    metadata:
      abstract: The anisotropic network model (ANM) is one of the simplest yet powerful
        tools for exploring protein dynamics. Its main utility is to predict and visualize
        the collective motions of large complexes and assemblies near their equilibrium
        structures. The ANM server, introduced by us in 2006 helped making this tool
        more accessible to non-sophisticated users. We now provide a new version (ANM
        2.0), which allows inclusion of nucleic acids and ligands in the network model
        and thus enables the investigation of the collective motions of protein-DNA/RNA
        and-ligand systems. The new version offers the flexibility of defining the
        system nodes and the interaction types and cutoffs. It also includes extensive
        improvements in hardware, software and graphical interfaces.
      authors:
      - name: Eyal E.
      - name: Lum G.
      - name: Bahar I.
      citationCount: 136
      date: '2015-05-01T00:00:00Z'
      journal: Bioinformatics
      title: The anisotropic network model web server at 2015 (ANM 2.0)
    note: null
    pmcid: PMC4410662
    pmid: '25568280'
    type: []
    version: null
  relation: []
  toolType:
  - Web application
  topic:
  - term: Proteomics
    uri: http://edamontology.org/topic_0121
  - term: Molecular modelling
    uri: http://edamontology.org/topic_2275
  validated: 1
  version: []
- accessibility: null
  additionDate: '2017-08-03T18:36:25Z'
  biotoolsCURIE: biotools:aodpred
  biotoolsID: aodpred
  collectionID:
  - Proteomics
  confidence_flag: null
  cost: null
  credit:
  - email: null
    fundrefid: null
    gridid: null
    name: Hao Lin
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
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    url: http://lin.uestc.edu.cn/
  description: This tool was developed to identify antioxidant proteins based on the
    sequence information.
  documentation:
  - note: null
    type:
    - General
    url: http://lin.uestc.edu.cn/server/Aod/readme
  download: []
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  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Protein sequence analysis
      uri: http://edamontology.org/operation_2479
    - term: Protein structure prediction
      uri: http://edamontology.org/operation_0474
    output: []
  homepage: http://lin.uestc.edu.cn/server/AntioxiPred
  homepage_status: 0
  language: []
  lastUpdate: '2024-11-25T14:17:11.389141Z'
  license: null
  link:
  - note: null
    type:
    - Software catalogue
    url: http://www.mybiosoftware.com/aodpred-identifying-antioxidant-proteins-by-using-optimal-dipeptide-compositions.html
  maturity: null
  name: AodPred
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  - Windows
  - Mac
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  publication:
  - doi: 10.1007/s12539-015-0124-9
    metadata:
      abstract: Antioxidant proteins are a kind of molecules that can terminate cellular
        and DNA damages caused by free radical intermediates. The use of antioxidant
        proteins for prevention of diseases has been intensively studied in recent
        years. Thus, accurate identification of antioxidant proteins is essential
        for understanding their roles in pharmacology. In this study, a support vector
        machine-based predictor called AodPred was developed for identifying antioxidant
        proteins. In this predictor, the sequence was formulated by using the optimal
        3-gap dipeptides obtained by using feature selection method. It was observed
        by jackknife cross-validation test that AodPred can achieve an overall accuracy
        of 74.79 % in identifying antioxidant proteins. As a user-friendly tool, AodPred
        is freely accessible at http://lin.uestc.edu.cn/server/AntioxiPred. To maximize
        the convenience of the vast majority of experimental scientists, a step-by-step
        guide is provided on how to use the web server to obtain the desired results.
      authors:
      - name: Feng P.
      - name: Chen W.
      - name: Lin H.
      citationCount: 45
      date: '2016-06-01T00:00:00Z'
      journal: Interdisciplinary Sciences – Computational Life Sciences
      title: Identifying Antioxidant Proteins by Using Optimal Dipeptide Compositions
    note: null
    pmcid: null
    pmid: '26345449'
    type: []
    version: null
  relation: []
  toolType:
  - Web application
  topic:
  - term: Proteomics
    uri: http://edamontology.org/topic_0121
  - term: Structure prediction
    uri: http://edamontology.org/topic_0082
  - term: Sequence analysis
    uri: http://edamontology.org/topic_0080
  validated: 1
  version: []
- accessibility: null
  additionDate: '2017-01-17T15:04:02Z'
  biotoolsCURIE: biotools:apcomplex
  biotoolsID: apcomplex
  collectionID:
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  - BioConductor
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: dscholtens@northwestern.edu
    fundrefid: null
    gridid: null
    name: Denise Scholtens
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
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    url: null
  description: Functions to estimate a bipartite graph of protein complex membership
    using AP-MS data.
  documentation:
  - note: null
    type:
    - User manual
    url: http://bioconductor.org/packages/release/bioc/html/apComplex.html
  download:
  - note: null
    type: Source code
    url: http://bioconductor/packages/release/bioc/src/contrib/apComplex_2.40.0.tar.gz
    version: null
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  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Protein structure assignment
      uri: http://edamontology.org/operation_0320
    output: []
  homepage: http://bioconductor.org/packages/release/bioc/html/apComplex.html
  homepage_status: 0
  language:
  - R
  lastUpdate: '2024-11-25T14:17:10.116176Z'
  license: GPL-3.0
  link: []
  maturity: null
  name: apComplex
  operatingSystem:
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  owner: bioconductor_import
  publication:
  - doi: 10.1093/bioinformatics/bti567
    metadata:
      abstract: 'Motivation: Systems biology requires accurate models of protein complexes,
        including physical interactions that assemble and regulate these molecular
        machines. Yeast two-hybrid (Y2H) and affinity-purification/mass-spectrometry
        (AP-MS) technologies measure different protein-protein relationships, and
        issues of completeness, sensitivity and specificity fuel debate over which
        is best for high-throughput ''interactome'' data collection. Static graphs
        currently used to model Y2H and AP-MS data neglect dynamic and spatial aspects
        of macromolecular complexes and pleiotropic protein function. Results: We
        apply the local modeling methodology proposed by Scholtens and Gentleman (2004)
        to two publicly available datasets and demonstrate its uses, interpretation
        and limitations. Specifically, we use this technology to address four major
        issues pertaining to protein-protein networks. (1) We motivate the need to
        move from static global interactome graphs to local protein complex models.
        (2) We formally show that accurate local interactome models require both Y2H
        and AP-MS data, even in idealized situations. (3) We briefly discuss experimental
        design issues and how bait selection affects interpretability of results.
        (4) We point to the implications of local modeling for systems biology including
        functional annotation, new complex prediction, pathway interactivity and coordination
        with gene-expression data. © The Author 2005. Published by Oxford University
        Press. All rights reserved.'
      authors:
      - name: Scholtens D.
      - name: Vidal M.
      - name: Gentleman R.
      citationCount: 66
      date: '2005-09-01T00:00:00Z'
      journal: Bioinformatics
      title: Local modeling of global interactome networks
    note: null
    pmcid: null
    pmid: '15998662'
    type:
    - Primary
    version: null
  relation: []
  toolType:
  - Command-line tool
  - Library
  topic:
  - term: Proteins
    uri: http://edamontology.org/topic_0078
  - term: Protein structure analysis
    uri: http://edamontology.org/topic_2814
  - term: Structural biology
    uri: http://edamontology.org/topic_1317
  - term: Proteomics experiment
    uri: http://edamontology.org/topic_3520
  validated: 1
  version:
  - 2.40.0
- accessibility: null
  additionDate: '2017-08-03T18:35:51Z'
  biotoolsCURIE: biotools:apecs
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  collectionID:
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  confidence_flag: null
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  - email: null
    fundrefid: null
    gridid: null
    name: null
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
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    url: http://www.nbic.nl
  description: Proteomics method for intensity-based precursor ion selection, using
    a MALDI-TOF/TOF instrument, from a complex sample separated by 2D-LC.
  documentation:
  - note: null
    type:
    - General
    url: https://trac.nbic.nl/apecs/wiki#no1
  download: []
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  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Modelling and simulation
      uri: http://edamontology.org/operation_2426
    - term: Mass spectra calibration
      uri: http://edamontology.org/operation_3627
    output: []
  homepage: https://trac.nbic.nl/apecs/
  homepage_status: 0
  language:
  - Python
  lastUpdate: '2024-11-25T14:17:08.762850Z'
  license: null
  link:
  - note: null
    type:
    - Software catalogue
    url: http://www.mybiosoftware.com/apecs-intensity-based-peptide-selection.html
  maturity: null
  name: APECS
  operatingSystem:
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  - Windows
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  otherID: []
  owner: mbs_import
  publication:
  - doi: 10.1021/pr1006944
    metadata:
      abstract: LC-MALDI provides an often overlooked opportunity to exploit the separation
        between LC-MS and MS/MS stages of a 2D-LC-MS-based proteomics experiment,
        that is, by making a smarter selection for precursor fragmentation. Apex Peptide
        Elution Chain Selection (APECS) is a simple and powerful method for intensity-based
        peptide selection in a complex sample separated by 2D-LC, using a MALDI-TOF/TOF
        instrument. It removes the peptide redundancy present in the adjacent first-dimension
        (typically strong cation exchange, SCX) fractions by constructing peptide
        elution profiles that link the precursor ions of the same peptide across SCX
        fractions. Subsequently, the precursor ion most likely to fragment successfully
        in a given profile is selected for fragmentation analysis, selecting on precursor
        intensity and absence of adjacent ions that may cofragment. To make the method
        independent of experiment-specific tolerance criteria, we introduce the concept
        of the branching factor, which measures the likelihood of false clustering
        of precursor ions based on past experiments. By validation with a complex
        proteome sample of Arabidopsis thaliana, APECS identified an equivalent number
        of peptides as a conventional data-dependent acquisition method but with a
        35% smaller work load. Consequently, reduced sample depletion allowed further
        selection of lower signal-to-noise ratio precursor ions, leading to a larger
        number of identified unique peptides. © 2010 American Chemical Society.
      authors:
      - name: Gandhi T.
      - name: Fusetti F.
      - name: Wiederhold E.
      - name: Breitling R.
      - name: Poolman B.
      - name: Permentier H.P.
      citationCount: 3
      date: '2010-11-05T00:00:00Z'
      journal: Journal of Proteome Research
      title: 'Apex peptide elution chain selection: A new strategy for selecting precursors
        in 2D-LC-MALDI-TOF/TOF experiments on complex biological samples'
    note: null
    pmcid: null
    pmid: '20836568'
    type: []
    version: null
  relation: []
  toolType:
  - Command-line tool
  topic:
  - term: Proteomics
    uri: http://edamontology.org/topic_0121
  - term: Proteomics experiment
    uri: http://edamontology.org/topic_3520
  - term: Simulation experiment
    uri: http://edamontology.org/topic_3524
  validated: 1
  version: []
- accessibility: null
  additionDate: '2017-12-18T00:03:16Z'
  biotoolsCURIE: biotools:apex
  biotoolsID: apex
  collectionID:
  - Proteomics
  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.marcottelab.org/
  description: Absolute protein expression Quantitative Proteomics Tool, is a free
    and open source Java implementation of the APEX technique for the quantitation
    of proteins based on standard LC- MS/MS proteomics data. This technique uses machine
    learning algorithms to help correct for variable peptide detection related to
    certain peptide physicochemical properties which favor or hinder detection. A
    sample data set and descriptive tutorial help to acquaint users with the operation
    of the tool.
  documentation: []
  download: []
  editPermission:
    authors:
    - proteomics.bio.tools
    type: group
  elixirCommunity: []
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  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Spectral counting
      uri: http://edamontology.org/operation_3637
    output: []
  - cmd: null
    input: []
    note: null
    operation:
    - term: Protein quantitation
      uri: http://edamontology.org/operation_3630
    output: []
  - cmd: null
    input: []
    note: null
    operation:
    - term: Detection
      uri: http://edamontology.org/operation_2423
    output: []
  homepage: http://sourceforge.net/projects/apexqpt/
  homepage_status: 0
  language:
  - Java
  lastUpdate: '2024-11-25T14:17:07.451861Z'
  license: null
  link:
  - note: null
    type:
    - Software catalogue
    url: http://www.mybiosoftware.com/apex-1-1-0-quantitative-proteomics-tool.html
  maturity: null
  name: APEX
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: mbs_import
  publication:
  - doi: 10.1038/nbt1270
    metadata:
      abstract: We report a method for large-scale absolute protein expression measurements
        (APEX) and apply it to estimate the relative contributions of transcriptional-
        and translational-level gene regulation in the yeast and Escherichia coli
        proteomes. APEX relies upon correcting each protein's mass spectrometry sampling
        depth (observed peptide count) by learned probabilities for identifying the
        peptides. APEX abundances agree with measurements from controls, western blotting,
        flow cytometry and two-dimensional gels, as well as known correlations with
        mRNA abundances and codon bias, providing absolute protein concentrations
        across approximately three to four orders of magnitude. Using APEX, we demonstrate
        that 73% of the variance in yeast protein abundance (47% in E. coli) is explained
        by mRNA abundance, with the number of proteins per mRNA log-normally distributed
        about ∼5,600 (∼540 in E. coli) protein molecules/mRNA. Therefore, levels of
        both eukaryotic and prokaryotic proteins are set per mRNA molecule and independently
        of overall protein concentration, with >70% of yeast gene expression regulation
        occurring through mRNA-directed mechanisms. © 2007 Nature Publishing Group.
      authors:
      - name: Lu P.
      - name: Vogel C.
      - name: Wang R.
      - name: Yao X.
      - name: Marcotte E.M.
      citationCount: 941
      date: '2007-01-05T00:00:00Z'
      journal: Nature Biotechnology
      title: Absolute protein expression profiling estimates the relative contributions
        of transcriptional and translational regulation
    note: null
    pmcid: null
    pmid: '17187058'
    type:
    - Primary
    version: null
  relation: []
  toolType:
  - Desktop application
  topic:
  - term: Proteins
    uri: http://edamontology.org/topic_0078
  - term: Machine learning
    uri: http://edamontology.org/topic_3474
  - term: Proteomics
    uri: http://edamontology.org/topic_0121
  - term: Protein expression
    uri: http://edamontology.org/topic_0108
  validated: 1
  version:
  - 1.1.0
- accessibility: null
  additionDate: '2017-08-03T18:36:26Z'
  biotoolsCURIE: biotools:archcandy
  biotoolsID: archcandy
  collectionID:
  - Proteomics
  confidence_flag: null
  cost: null
  credit:
  - email: Andrey.Kajava@crbm.cnrs.fr
    fundrefid: null
    gridid: null
    name: Andrey V. Kajava
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: http://bioinfo.montp.cnrs.fr/index.php
  description: Tool able to decode protein sequence motifs that have a potential to
    form amyloids.
  documentation:
  - note: null
    type:
    - General
    url: http://bioinfo.montp.cnrs.fr/?r=ArchCandy&p=home
  download: []
  editPermission:
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    type: group
  elixirCommunity: []
  elixirNode: []
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  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Protein sequence analysis
      uri: http://edamontology.org/operation_2479
    - term: Protein feature detection
      uri: http://edamontology.org/operation_3092
    output: []
  homepage: http://bioinfo.montp.cnrs.fr/?r=ArchCandy
  homepage_status: 0
  language: []
  lastUpdate: '2024-11-25T14:17:06.094012Z'
  license: null
  link:
  - note: null
    type:
    - Software catalogue
    url: http://www.mybiosoftware.com/archcandy-detect-regions-in-protein-sequences-that-have-a-potential-to-form-amyloids.html
  maturity: null
  name: ArchCandy
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: mbs_import
  publication:
  - doi: 10.1016/j.jalz.2014.06.007
    metadata:
      abstract: 'Background: Neurodegenerative diseases and other amyloidoses are
        linked to the formation of amyloid fibrils. It has been shown that the ability
        to form these fibrils is coded by the amino acid sequence. Existing methods
        for the prediction of amyloidogenicity generate an unsatisfactory high number
        of false positives when tested against sequences of the disease-related proteins.
        Methods: Recently, it has been shown that the three-dimensional structure
        of a majority of disease-related amyloid fibrils contains a β-strand-loop-β-strand
        motif called β-arch. Using this information, we have developed a novel bioinformatics
        approach for the prediction of amyloidogenicity. Results: The benchmark results
        show the superior performance of our method over the existing programs. Conclusions:
        As genome sequencing becomes more affordable, our method provides an opportunity
        to create individual risk profiles for the neurodegenerative, age-related,
        and other diseases ushering in an era of personalized medicine. It will also
        be used in the large-scale analysis of proteomes to find new amyloidogenic
        proteins.'
      authors:
      - name: Ahmed A.B.
      - name: Znassi N.
      - name: Chateau M.-T.
      - name: Kajava A.V.
      citationCount: 77
      date: '2015-06-01T00:00:00Z'
      journal: Alzheimer's and Dementia
      title: A structure-based approach to predict predisposition to amyloidosis
    note: null
    pmcid: null
    pmid: '25150734'
    type: []
    version: null
  relation: []
  toolType:
  - Desktop application
  topic:
  - term: Protein sites, features and motifs
    uri: http://edamontology.org/topic_3510
  - term: Proteomics
    uri: http://edamontology.org/topic_0121
  validated: 1
  version: []
- accessibility: null
  additionDate: '2017-08-03T18:36:28Z'
  biotoolsCURIE: biotools:archip
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    fundrefid: null
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    name: Evgeniy Aksianov
    note: null
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    typeEntity: Person
    typeRole:
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    url: null
  description: This tool detects architectures of all-β and α/β-classes
  documentation:
  - note: null
    type:
    - General
    url: http://mouse.belozersky.msu.ru/~evgeniy/cgi-bin/proton/proton.php?subproj=archip&page=help&data=alldocs
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  homepage: http://mouse.belozersky.msu.ru/~evgeniy/cgi-bin/proton/proton.php?subproj=archip
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  lastUpdate: '2024-11-25T14:17:04.676391Z'
  license: null
  link:
  - note: null
    type:
    - Software catalogue
    url: http://www.mybiosoftware.com/archip-2-1-detecting-architectures-of-all-β-and-αβ-classes.html
  maturity: null
  name: ArchiP
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  publication:
  - doi: 10.1142/s021972001241003x
    metadata:
      abstract: The description of a protein fold is a hard problem due to significant
        variability of main structural units, β-sheets and α-helixes, and their mutual
        arrangements. An adequate description of the structural units is an important
        step in objective protein structure classification, which to date is based
        on expert judgment in a number of cases. Explicit determination and description
        of structural units is more complicated for β-sheets than for α-helixes due
        to β-sheets variability both in composition and geometry. We have developed
        an algorithm that can significantly modify β-sheets detected by commonly used
        DSSP and Stride algorithms and represent the result as a "β-sheet map," a
        table describing certain β-sheet features. In our approach, β-sheets (rather
        than β-strands) are considered as holistic objects. Both hydrogen bonds and
        geometrical restrains are explored for the determination of β-sheets. The
        algorithm is implemented in SheeP program. It was tested for prediction architectures
        of domains from 93 well-defined all-β and α/β SCOP protein domain families,
        and showed 93% of correct results. The Web-service allows to detect β-sheets
        in a given protein structure, visualize β-sheet maps, as well as input three-dimensional
        structures with highlighted β-sheets and their structural features. © 2012
        Imperial College Press.
      authors:
      - name: Aksianov E.
      - name: Alexeevski A.
      citationCount: 3
      date: '2012-04-01T00:00:00Z'
      journal: Journal of Bioinformatics and Computational Biology
      title: 'Sheep: A tool for description of β-sheets in protein 3D structures'
    note: null
    pmcid: null
    pmid: '22809339'
    type: []
    version: null
  relation: []
  toolType:
  - Web application
  topic:
  - term: Molecular modelling
    uri: http://edamontology.org/topic_2275
  - term: Proteomics
    uri: http://edamontology.org/topic_0121
  - term: Structure prediction
    uri: http://edamontology.org/topic_0082
  validated: 1
  version: []
- accessibility: null
  additionDate: '2017-08-03T18:36:27Z'
  biotoolsCURIE: biotools:archki
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  confidence_flag: null
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    typeEntity: Person
    typeRole:
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    url: http://sbi.imim.es/cgi-bin/archdb/loops.pl?con=1
  description: This tool performs a structural classification of kinase loops with
    information of functional residues to find relationships between structure and
    function of classified kinase-loops.
  documentation:
  - note: null
    type:
    - General
    url: http://bioinf.uab.es/cgi-bin/archki/loops.pl?class=all
  download: []
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  function:
  - cmd: null
    input: []
    note: null
    operation:
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    output: []
  homepage: http://bioinf.uab.es/cgi-bin/archki/loops.pl?class=all&set=ArchKI
  homepage_status: 0
  language: []
  lastUpdate: '2024-11-25T14:17:03.282188Z'
  license: null
  link:
  - note: null
    type:
    - Software catalogue
    url: http://www.mybiosoftware.com/archki-classification-common-functional-loops-kinase-super-families.html
  maturity: null
  name: ArchKI
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  - Linux
  - Windows
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  publication:
  - doi: 10.1002/prot.20136
    metadata:
      abstract: A structural classification of loops has been obtained from a set
        of 141 protein structures classified as kinases. A total of 1813 loops was
        classified into 133 subclasses (9 ββlinks, 15 ββ hairpins, 31 α-α, 46 α-β
        and 32 β-α). Functional information and specific features relating subclasses
        and function were included in the classification. Functional loops such as
        the P-loop (shared by different folds) or the Gly-rich-loop, among others,
        were classified into structural motifs. As a result, a common mechanism of
        catalysis and substrate binding was proved for most kinases. Additionally,
        the multiple-alignment of loop sequences made within each subclass was shown
        to be useful for comparative modeling of kinase loops. © 2004 Wiley-Liss,
        Inc.
      authors:
      - name: Fernandez-Fuentes N.
      - name: Hermoso A.
      - name: Espadaler J.
      - name: Querol E.
      - name: Aviles F.X.
      - name: Oliva B.
      citationCount: 21
      date: '2004-08-15T00:00:00Z'
      journal: 'Proteins: Structure, Function and Genetics'
      title: Classification of common functional loops of kinase super-families
    note: null
    pmcid: null
    pmid: '15229886'
    type: []
    version: null
  relation: []
  toolType:
  - Web service
  topic:
  - term: Proteomics
    uri: http://edamontology.org/topic_0121
  - term: Gene and protein families
    uri: http://edamontology.org/topic_0623
  - term: Protein structural motifs and surfaces
    uri: http://edamontology.org/topic_0166
  validated: 1
  version: []
- accessibility: null
  additionDate: '2017-08-03T18:36:25Z'
  biotoolsCURIE: biotools:arshift
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  confidence_flag: null
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  - email: null
    fundrefid: null
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    name: null
    note: null
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    typeEntity: Person
    typeRole:
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    url: http://www-vendruscolo.ch.cam.ac.uk/index.html
  description: Method of calculating side-chain aromatic chemical shifts from protein
    structures.
  documentation:
  - note: Downloadable PDF within homepage.
    type:
    - General
    url: http://www-sidechain.ch.cam.ac.uk/ArShift/
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  function:
  - cmd: null
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    note: null
    operation:
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      uri: http://edamontology.org/operation_2479
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    output: []
  homepage: http://www-sidechain.ch.cam.ac.uk/ArShift/
  homepage_status: 0
  language:
  - R
  lastUpdate: '2024-11-25T14:17:02.124102Z'
  license: null
  link:
  - note: null
    type:
    - Software catalogue
    url: http://www.mybiosoftware.com/arshift-structure-based-predictor-of-protein-aromatic-side-chain-proton-chemical-shifts.html
  maturity: null
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  operatingSystem:
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  otherID: []
  owner: mbs_import
  publication:
  - doi: 10.1002/anie.201101641
    metadata:
      abstract: 'Predicting chemical shifts: A method for the structure-based prediction
        of side-chain aromatic 1H chemical shifts of proteins is presented (see picture;
        blue structures: aromatic side chains, red spheres: aromatic hydrogen atoms).
        Its ability to differentiate correct structural models from incorrect ones
        is also demonstrated, together with its use to detect differences caused by
        cofactor or ligand binding, or by sequence alterations between structures.
        Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.'
      authors:
      - name: Sahakyan A.B.
      - name: Vranken W.F.
      - name: Cavalli A.
      - name: Vendruscolo M.
      citationCount: 21
      date: '2011-10-04T00:00:00Z'
      journal: Angewandte Chemie - International Edition
      title: Using side-chain aromatic proton chemical shifts for a quantitative analysis
        of protein structures
    note: null
    pmcid: null
    pmid: '21887824'
    type: []
    version: null
  relation: []
  toolType:
  - Web application
  topic:
  - term: Molecular modelling
    uri: http://edamontology.org/topic_2275
  - term: Proteomics
    uri: http://edamontology.org/topic_0121
  - term: Protein secondary structure
    uri: http://edamontology.org/topic_3542
  validated: 1
  version: []
- accessibility: null
  additionDate: '2017-01-17T14:51:31Z'
  biotoolsCURIE: biotools:asapratio
  biotoolsID: asapratio
  collectionID:
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  - Proteomics
  confidence_flag: null
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  credit:
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    fundrefid: null
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    name: null
    note: null
    orcidid: null
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    typeEntity: Person
    typeRole:
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    url: http://ms-utils.org
  description: Statistical analysis of protein ratios from ICAT, cICAT or SILAC experiments.
  documentation:
  - note: null
    type:
    - General
    url: http://tools.proteomecenter.org/wiki/index.php?title=Software:ASAPRatio
  download: []
  editPermission:
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    type: group
  elixirCommunity: []
  elixirNode: []
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  elixir_badge: 0
  function:
  - cmd: null
    input:
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        term: Peptide identification
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      format:
      - term: pepXML
        uri: http://edamontology.org/format_3655
    note: null
    operation:
    - term: SILAC
      uri: http://edamontology.org/operation_3638
    - term: Protein quantification
      uri: http://edamontology.org/operation_3630
    - term: Differential protein expression analysis
      uri: http://edamontology.org/operation_3741
    - term: Gene expression profiling
      uri: http://edamontology.org/operation_0314
    - term: Isotope-coded protein label
      uri: http://edamontology.org/operation_3705
    - term: Statistical inference
      uri: http://edamontology.org/operation_3658
    - term: Isotopic distributions calculation
      uri: http://edamontology.org/operation_3632
    - term: Labeled quantification
      uri: http://edamontology.org/operation_3635
    output:
    - data:
        term: P-value
        uri: http://edamontology.org/data_1669
      format:
      - term: protXML
        uri: http://edamontology.org/format_3747
      - term: pepXML
        uri: http://edamontology.org/format_3655
    - data:
        term: Expression data
        uri: http://edamontology.org/data_2603
      format:
      - term: protXML
        uri: http://edamontology.org/format_3747
      - term: pepXML
        uri: http://edamontology.org/format_3655
  homepage: http://tools.proteomecenter.org/ASAPRatio.php
  homepage_status: 0
  language:
  - C++
  lastUpdate: '2024-11-25T14:17:00.893759Z'
  license: null
  link:
  - note: null
    type:
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    url: http://ms-utils.org
  maturity: null
  name: ASAPRatio
  operatingSystem:
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  otherID: []
  owner: msutils_import
  publication:
  - doi: 10.1021/ac034633i
    metadata:
      abstract: We describe an algorithm for the automated statistical analysis of
        protein abundance ratios (ASAPRatio) of proteins contained in two samples.
        Proteins are labeled with distinct stable-isotope tags and fragmented, and
        the tagged peptide fragments are separated by liquid chromatography (LC) and
        analyzed by electrospray ionization (ESI) tandem mass spectrometry (MS/MS).
        The algorithm utilizes the signals recorded for the different isotopic forms
        of peptides of identical sequence and numerical and statistical methods, such
        as Savitzky-Golay smoothing filters, statistics for weighted samples, and
        Dixon's test for outliers, to evaluate protein abundance ratios and their
        associated errors. The algorithm also provides a statistical assessment to
        distinguish proteins of significant abundance changes from a population of
        proteins of unchanged abundance. To evaluate its performance, two sets of
        LC-ESI-MS/MS data were analyzed by the ASAPRatio algorithm without human intervention,
        and the data were related to the expected and manually validated values. The
        utility of the ASAPRatio program was clearly demonstrated by its speed and
        the accuracy of the generated protein abundance ratios and by its capability
        to identify specific core components of the RNA polymerase II transcription
        complex within a high background of copurifying proteins.
      authors:
      - name: Li X.-J.
      - name: Zhang H.
      - name: Ranish J.A.
      - name: Aebersold R.
      citationCount: 323
      date: '2003-12-01T00:00:00Z'
      journal: Analytical Chemistry
      title: Automated Statistical Analysis of Protein Abundance Ratios from Data
        Generated by Stable-Isotope Dilution and Tandem Mass Spectrometry
    note: null
    pmcid: null
    pmid: '14640741'
    type:
    - Primary
    version: null
  relation: []
  toolType:
  - Command-line tool
  - Desktop application
  topic:
  - term: Proteomics
    uri: http://edamontology.org/topic_0121
  - term: Proteomics experiment
    uri: http://edamontology.org/topic_3520
  - term: Statistics and probability
    uri: http://edamontology.org/topic_2269
  validated: 1
  version: []
- accessibility: null
  additionDate: '2017-05-01T17:09:03Z'
  biotoolsCURIE: biotools:atsubp
  biotoolsID: atsubp
  collectionID:
  - Proteomics
  confidence_flag: null
  cost: null
  credit:
  - email: bioinfo@noble.org
    fundrefid: null
    gridid: null
    name: AtSubP team
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  description: A highly accurate subcellular localization prediction tool for annotating
    the Arabidopsis thaliana proteome.
  documentation:
  - note: null
    type:
    - General
    url: http://bioinfo3.noble.org/AtSubP/?dowhat=Help
  download: []
  editPermission:
    authors:
    - proteomics.bio.tools
    type: group
  elixirCommunity: []
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  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Protein subcellular localisation prediction
      uri: http://edamontology.org/operation_2489
    - term: Protein secondary structure prediction
      uri: http://edamontology.org/operation_0267
    - term: Protein feature detection
      uri: http://edamontology.org/operation_3092
    output: []
  homepage: http://bioinfo3.noble.org/AtSubP/
  homepage_status: 0
  language: []
  lastUpdate: '2024-11-25T14:16:58.795083Z'
  license: null
  link: []
  maturity: null
  name: AtSubP
  operatingSystem:
  - Linux
  - Windows
  - Mac
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  owner: ELIXIR-EE
  publication:
  - doi: 10.1104/pp.110.156851
    metadata:
      abstract: A complete map of the Arabidopsis (Arabidopsis thaliana) proteome
        is clearly a major goal for the plant research community in terms of determining
        the function and regulation of each encoded protein. Developing genome-wide
        prediction tools such as for localizing gene products at the subcellular level
        will substantially advance Arabidopsis gene annotation. To this end, we performed
        a comprehensive study in Arabidopsis and created an integrative support vector
        machine-based localization predictor called AtSubP (for Arabidopsis subcellular
        localization predictor) that is based on the combinatorial presence of diverse
        protein features, such as its amino acid composition, sequence-order effects,
        terminal information, Position-Specific Scoring Matrix, and similarity search-based
        Position-Specific Iterated-Basic Local Alignment Search Tool information.
        When used to predict seven subcellular compartments through a 5-fold cross-validation
        test, our hybrid-based best classifier achieved an overall sensitivity of
        91% with high-confidence precision and Matthews correlation coefficient values
        of 90.9% and 0.89, respectively. Benchmarking AtSubP on two independent data
        sets, one from Swiss-Prot and another containing green fluorescent protein-
        and mass spectrometry-determined proteins, showed a significant improvement
        in the prediction accuracy of species-specific AtSubP over some widely used
        "general" tools such as TargetP, LOCtree, PA-SUB, MultiLoc, WoLF PSORT, Plant-PLoc,
        and our newly created All-Plant method. Cross-comparison of AtSubP on six
        nontrained eukaryotic organisms (rice [Oryza sativa], soybean [Glycine max],
        human [Homo sapiens], yeast [Saccharomyces cerevisiae], fruit fly [Drosophila
        melanogaster], and worm [Caenorhabditis elegans]) revealed inferior predictions.
        AtSubP significantly outperformed all the prediction tools being currently
        used for Arabidopsis proteome annotation and, therefore, may serve as a better
        complement for the plant research community. A supplemental Web site that
        hosts all the training/testing data sets and whole proteome predictions is
        available at http://bioinfo3.noble.org/AtSubP/. © 2010 American Society of
        Plant Biologists.
      authors:
      - name: Kaundal R.
      - name: Saini R.
      - name: Zhao P.X.
      citationCount: 73
      date: '2010-01-01T00:00:00Z'
      journal: Plant Physiology
      title: Combining machine learning and homology-based approaches to accurately
        predict subcellular localization in Arabidopsis
    note: null
    pmcid: null
    pmid: '20647376'
    type: []
    version: null
  relation: []
  toolType:
  - Web application
  topic:
  - term: Proteomics
    uri: http://edamontology.org/topic_0121
  - term: Machine learning
    uri: http://edamontology.org/topic_3474
  - term: Plant biology
    uri: http://edamontology.org/topic_0780
  - term: Model organisms
    uri: http://edamontology.org/topic_0621
  - term: Small molecules
    uri: http://edamontology.org/topic_0154
  validated: 1
  version: []
- accessibility: null
  additionDate: '2017-01-17T14:51:45Z'
  biotoolsCURIE: biotools:autohd
  biotoolsID: autohd
  collectionID:
  - ms-utils
  - Proteomics
  confidence_flag: null
  cost: null
  credit:
  - email: magnus.palmblad@gmail.com
    fundrefid: null
    gridid: null
    name: Magnus Palmblad
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
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    url: null
  - email: webmaster@ms-utils.org
    fundrefid: null
    gridid: null
    name: null
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
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    url: http://ms-utils.org
  description: Analysis of H/D-exchange data using isotopic distributions.
  documentation:
  - note: null
    type:
    - General
    url: http://www.ms-utils.org/autohd.html
  download:
  - note: null
    type: Source code
    url: http://www.ms-utils.org/autohd_download.html
    version: null
  - note: null
    type: Source code
    url: http://www.ms-utils.org/autohd_download.html
    version: null
  editPermission:
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  function:
  - cmd: null
    input:
    - data:
        term: Protein sequence
        uri: http://edamontology.org/data_2976
      format:
      - term: FASTA-like (text)
        uri: http://edamontology.org/format_2200
    note: null
    operation:
    - term: Protein hydrogen exchange rate calculation
      uri: http://edamontology.org/operation_0404
    output:
    - data:
        term: Protein structure report
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      format:
      - term: Textual format
        uri: http://edamontology.org/format_2330
  homepage: http://www.ms-utils.org/autohd.html
  homepage_status: 0
  language:
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  lastUpdate: '2024-11-25T14:16:56.803274Z'
  license: GPL-3.0
  link:
  - note: null
    type:
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    url: http://ms-utils.org
  maturity: null
  name: AUTOHD
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: msutils_import
  publication:
  - doi: 10.1016/s1044-0305(01)00301-4
    metadata:
      abstract: High mass-resolving power has been shown to be useful for studying
        the conformational dynamics of proteins by hydrogen/deuterium (H/D) exchange.
        A computer algorithm was developed that automatically identifies peptides
        and their extent of deuterium incorporation from H/D exchange mass spectra
        of enzymatic digests or fragment ions produced by collisionally induced dissociation
        (CID) or electron capture dissociation (ECD). The computer algorithm compares
        measured and calculated isotopic distributions and uses a fast calculation
        of isotopic distributions using the fast Fourier transform (FFT). The algorithm
        facilitates rapid and automated analysis of H/D exchange mass spectra suitable
        for high-throughput approaches to the study of peptide and protein structures.
        The algorithm also makes the identification independent on comparisons with
        undeuterated control samples. The applicability of the algorithm was demonstrated
        on simulated isotopic distributions as well as on experimental data, such
        as Fourier transform ion cyclotron resonance (FTICR) mass spectra of myoglobin
        peptic digests, and CID and ECD spectra of substance P. Copyright © 2001 American
        Society for Mass Spectrometry.
      authors:
      - name: Palmblad M.
      - name: Buijs J.
      - name: Hakansson P.
      citationCount: 62
      date: '2001-12-01T00:00:00Z'
      journal: Journal of the American Society for Mass Spectrometry
      title: Automatic analysis of hydrogen/deuterium exchange mass spectra of peptides
        and proteins using calculations of isotopic distributions
    note: null
    pmcid: null
    pmid: '11720389'
    type: []
    version: null
  relation: []
  toolType:
  - Command-line tool
  topic:
  - term: Proteomics
    uri: http://edamontology.org/topic_0121
  - term: Proteomics experiment
    uri: http://edamontology.org/topic_3520
  validated: 1
  version: []
- accessibility: null
  additionDate: '2016-07-21T13:28:23Z'
  biotoolsCURIE: biotools:babelomics
  biotoolsID: babelomics
  collectionID:
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  - Proteomics
  confidence_flag: null
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  credit:
  - email: null
    fundrefid: null
    gridid: null
    name: Computational Genomics Department. Prince Felipe Research Center (CIPF)
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
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    url: null
  - email: null
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    name: http://bioinfo.cipf.es
    note: null
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    rorid: null
    typeEntity: Institute
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    url: null
  - email: null
    fundrefid: null
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    name: cipf.es
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
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    url: null
  - email: babelomics@cipf.es
    fundrefid: null
    gridid: null
    name: babelomics@cipf.es  (Francisco García)
    note: null
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    typeEntity: Person
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    url: null
  description: Integrative platform for the analysis of Transcriptomics, Proteomics
    and Genomics data with advanced functional profiling. It integrates primary (normalization,
    calls, etc.) and secondary (signatures, predictors, associations, TDTs, clustering,
    etc.) analysis tools within an environment that allows relating genomic data and/or
    interpreting them by means of different functional enrichment or gene set methods.
  documentation:
  - note: null
    type:
    - Citation instructions
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  - note: null
    type:
    - General
    url: https://github.com/babelomics/babelomics/wiki
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  function:
  - cmd: null
    input:
    - data:
        term: Gene expression matrix
        uri: http://edamontology.org/data_3112
      format:
      - term: TSV
        uri: http://edamontology.org/format_3475
    - data:
        term: Raw microarray data
        uri: http://edamontology.org/data_3110
      format: []
    - data:
        term: ID list
        uri: http://edamontology.org/data_2872
      format: []
    - data:
        term: Matrix
        uri: http://edamontology.org/data_2082
      format: []
    note: null
    operation:
    - term: Pathway or network comparison
      uri: http://edamontology.org/operation_0277
    - term: Ontology visualisation
      uri: http://edamontology.org/operation_3559
    - term: Enrichment analysis
      uri: http://edamontology.org/operation_3501
    - term: Gene expression correlation
      uri: http://edamontology.org/operation_3463
    - term: Gene expression clustering
      uri: http://edamontology.org/operation_0313
    - term: Gene expression analysis
      uri: http://edamontology.org/operation_2495
    output:
    - data:
        term: Ontology
        uri: http://edamontology.org/data_0582
      format: []
    - data:
        term: Heat map
        uri: http://edamontology.org/data_1636
      format: []
    - data:
        term: Plot
        uri: http://edamontology.org/data_2884
      format: []
  homepage: http://babelomics.bioinfo.cipf.es/
  homepage_status: 0
  language: []
  lastUpdate: '2024-11-25T14:16:55.273772Z'
  license: null
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/babelomics/babelomics
  maturity: null
  name: Babelomics
  operatingSystem:
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  - Windows
  - Mac
  otherID: []
  owner: fgarcia@cipf.es
  publication:
  - doi: 10.1093/nar/gkv384
    metadata:
      abstract: 'Babelomics has been running for more than one decade offering a user-friendly
        interface for the functional analysis of gene expression and genomic data.
        Here we present its fifth release, which includes support for Next Generation
        Sequencing data including gene expression (RNA-seq), exome or genome resequencing.
        Babelomics has simplified its interface, being now more intuitive. Improved
        visualization options, such as a genome viewer as well as an interactive network
        viewer, have been implemented. New technical enhancements at both, client
        and server sides, makes the user experience faster and more dynamic. Babelomics
        offers user-friendly access to a full range of methods that cover: (i) primary
        data analysis, (ii) a variety of tests for different experimental designs
        and (iii) different enrichment and network analysis algorithms for the interpretation
        of the results of such tests in the proper functional context. In addition
        to the public server, local copies of Babelomics can be downloaded and installed.
        Babelomics is freely available at: http://www.babelomics.org.'
      authors:
      - name: Alonso R.
      - name: Salavert F.
      - name: Garcia-Garcia F.
      - name: Carbonell-Caballero J.
      - name: Bleda M.
      - name: Garcia-Alonso L.
      - name: Sanchis-Juan A.
      - name: Perez-Gil D.
      - name: Marin-Garcia P.
      - name: Sanchez R.
      - name: Cubuk C.
      - name: Hidalgo M.R.
      - name: Amadoz A.
      - name: Hernansaiz-Ballesteros R.D.
      - name: Aleman A.
      - name: Tarraga J.
      - name: Montaner D.
      - name: Medina I.
      - name: Dopazo J.
      citationCount: 100
      date: '2015-01-01T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'Babelomics 5.0: Functional interpretation for new generations of genomic
        data'
    note: null
    pmcid: PMC4489263
    pmid: '25897133'
    type:
    - Primary
    version: null
  relation: []
  toolType:
  - Web application
  topic:
  - term: Transcriptomics
    uri: http://edamontology.org/topic_3308
  - term: Proteomics
    uri: http://edamontology.org/topic_0121
  - term: GWAS study
    uri: http://edamontology.org/topic_3517
  - term: Genomics
    uri: http://edamontology.org/topic_0622
  - term: Data management
    uri: http://edamontology.org/topic_3071
  - term: Systems biology
    uri: http://edamontology.org/topic_2259
  - term: Metabolomics
    uri: http://edamontology.org/topic_3172
  validated: 1
  version:
  - '5'
- accessibility: null
  additionDate: '2017-03-25T17:08:07Z'
  biotoolsCURIE: biotools:bagel3
  biotoolsID: bagel3
  collectionID:
  - Proteomics
  confidence_flag: null
  cost: null
  credit:
  - email: a.j.van.heel@rug.nl
    fundrefid: null
    gridid: null
    name: A.J. van Heel
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  description: Automated identification of genes encoding bacteriocins and (non)-bacteriocidal
    post-translationally modified peptides using updated bacteriocin and context protein
    databases. Input is single or multiple FASTA formatted files.
  documentation: []
  download: []
  editPermission:
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  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Peptide identification
      uri: http://edamontology.org/operation_3631
    - term: Format detection
      uri: http://edamontology.org/operation_3357
    - term: Tag-based peptide identification
      uri: http://edamontology.org/operation_3643
    - term: Coding region prediction
      uri: http://edamontology.org/operation_0436
    - term: Protein identification
      uri: http://edamontology.org/operation_3767
    output: []
  homepage: http://bagel.molgenrug.nl
  homepage_status: 0
  language: []
  lastUpdate: '2024-11-25T14:16:53.063051Z'
  license: null
  link: []
  maturity: null
  name: BAGEL3
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: ELIXIR-EE
  publication:
  - doi: 10.1093/nar/gkt391
    metadata:
      abstract: Identifying genes encoding bacteriocins and ribosomally synthesized
        and posttranslationally modified peptides (RiPPs) can be a challenging task.
        Especially those peptides that do not have strong homology to previously identified
        peptides can easily be overlooked. Extensive use of BAGEL2 and user feedback
        has led us to develop BAGEL3. BAGEL3 features genome mining of prokaryotes,
        which is largely independent of open reading frame (ORF) predictions and has
        been extended to cover more (novel) classes of posttranslationally modified
        peptides. BAGEL3 uses an identification approach that combines direct mining
        for the gene and indirect mining via context genes. Especially for heavily
        modified peptides like lanthipeptides, sactipeptides, glycocins and others,
        this genetic context harbors valuable information that is used for mining
        purposes. The bacteriocin and context protein databases have been updated
        and it is now easy for users to submit novel bacteriocins or RiPPs. The output
        has been simplified to allow user-friendly analysis of the results, in particular
        for large (meta-genomic) datasets. The genetic context of identified candidate
        genes is fully annotated. As input, BAGEL3 uses FASTA DNA sequences or folders
        containing multiple FASTA formatted files. BAGEL3 is freely accessible at
        http://bagel.molgenrug.nl.
      authors:
      - name: van Heel A.J.
      - name: de Jong A.
      - name: Montalban-Lopez M.
      - name: Kok J.
      - name: Kuipers O.P.
      citationCount: 396
      date: '2013-01-01T00:00:00Z'
      journal: Nucleic acids research
      title: 'BAGEL3: Automated identification of genes encoding bacteriocins and
        (non-)bactericidal posttranslationally modified peptides.'
    note: null
    pmcid: PMC3692055
    pmid: '23677608'
    type: []
    version: null
  relation: []
  toolType:
  - Web application
  topic:
  - term: Small molecules
    uri: http://edamontology.org/topic_0154
  - term: Proteomics
    uri: http://edamontology.org/topic_0121
  - term: Metagenomics
    uri: http://edamontology.org/topic_3174
  - term: Proteins
    uri: http://edamontology.org/topic_0078
  validated: 1
  version: []
- accessibility: null
  additionDate: '2017-08-03T18:37:22Z'
  biotoolsCURIE: biotools:betavoid
  biotoolsID: betavoid
  collectionID:
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  confidence_flag: null
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    note: null
    orcidid: null
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    typeEntity: Person
    typeRole:
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    url: http://voronoi.hanyang.ac.kr/
  description: This software recognizes molecular voids in the van der Waals surface
    or the Lee-Richards (solvent accessible) surface and computes their mass properties
    such the volume and the boundary area.
  documentation:
  - note: null
    type:
    - General
    url: http://voronoi.hanyang.ac.kr/software.htm#BetaVoidWin
  download: []
  editPermission:
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  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Protein structural motif recognition
      uri: http://edamontology.org/operation_0245
    output: []
  homepage: http://voronoi.hanyang.ac.kr/software.htm#BetaVoidWin
  homepage_status: 0
  language: []
  lastUpdate: '2024-11-25T14:16:51.628122Z'
  license: null
  link:
  - note: null
    type:
    - Software catalogue
    url: http://www.mybiosoftware.com/betavoid-v1-molecular-voids-via-beta-complexes-and-voronoi-diagrams.html
  maturity: null
  name: BetaVoid
  operatingSystem:
  - Linux
  - Windows
  otherID: []
  owner: mbs_import
  publication:
  - doi: 10.1002/prot.24537
    metadata:
      abstract: 'Molecular external structure is important for molecular function,
        with voids on the surface and interior being one of the most important features.
        Hence, recognition of molecular voids and accurate computation of their geometrical
        properties, such as volume, area and topology, are crucial, yet most popular
        algorithms are based on the crude use of sampling points and thus are approximations
        even with a significant amount of computation. In this article, we propose
        an analytic approach to the problem using the Voronoi diagram of atoms and
        the beta-complex. The correctness and efficiency of the proposed algorithm
        is mathematically proved and experimentally verified. The benchmark test clearly
        shows the superiority of BetaVoid to two popular programs: VOIDOO and CASTp.
        The proposed algorithm is implemented in the BetaVoid program which is freely
        available at the Voronoi Diagram Research Center (http://voronoi.hanyang.ac.kr).
        © 2014 Wiley Periodicals, Inc.'
      authors:
      - name: Kim J.-K.
      - name: Cho Y.
      - name: Laskowski R.A.
      - name: Ryu S.E.
      - name: Sugihara K.
      - name: Kim D.-S.
      citationCount: 13
      date: '2014-01-01T00:00:00Z'
      journal: 'Proteins: Structure, Function and Bioinformatics'
      title: 'BetaVoid: Molecular voids via beta-complexes and Voronoi diagrams'
    note: null
    pmcid: null
    pmid: '24677176'
    type: []
    version: null
  relation: []
  toolType:
  - Desktop application
  topic:
  - term: Molecular modelling
    uri: http://edamontology.org/topic_2275
  - term: Protein structural motifs and surfaces
    uri: http://edamontology.org/topic_0166
  - term: Proteomics
    uri: http://edamontology.org/topic_0121
  validated: 1
  version: []
- accessibility: null
  additionDate: '2017-03-27T07:56:17Z'
  biotoolsCURIE: biotools:biodrugscreen
  biotoolsID: biodrugscreen
  collectionID:
  - Proteomics
  confidence_flag: null
  cost: null
  credit:
  - email: smeroueh@iupui.edu
    fundrefid: null
    gridid: null
    name: Samy O. Meroueh
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  description: Resource for ranking molecules docked against a large number of targets
    in the human proteome. Nearly 1600 molecules from the freely available NCI diversity
    set were docked onto 1926 cavities identified on 1589 human targets resulting
    in >3 million receptor-ligand complexes. The targets are originated from Human
    Cancer Protein Interaction Network, which we have updated, as well as the Human
    Druggable Proteome, created for this. This makes the resource highly valuable
    in drug discovery.
  documentation: []
  download: []
  editPermission:
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    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: Over-representation analysis
      uri: http://edamontology.org/operation_3501
    - term: Molecular docking
      uri: http://edamontology.org/operation_0478
    - term: Protein-ligand docking
      uri: http://edamontology.org/operation_0482
    output: []
  homepage: http://www.biodrugscore.org
  homepage_status: 0
  language: []
  lastUpdate: '2024-11-25T14:16:50.029041Z'
  license: null
  link: []
  maturity: null
  name: BioDrugScreen
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: ELIXIR-EE
  publication:
  - doi: 10.1093/nar/gkp852
    metadata:
      abstract: BioDrugScreen is a resource for ranking molecules docked against a
        large number of targets in the human proteome. Nearly 1600 molecules from
        the freely available NCI diversity set were docked onto 1926 cavities identified
        on 1589 human targets resulting in >3 million receptor-ligand complexes requiring
        >200 000 cpu-hours on the TeraGrid. The targets in BioDrugScreen originated
        from Human Cancer Protein Interaction Network, which we have updated, as well
        as the Human Druggable Proteome, which we have created for the purpose of
        this effort. This makes the BioDrugScreen resource highly valuable in drug
        discovery. The receptor-ligand complexes within the database can be ranked
        using standard and well-established scoring functions like AutoDock, DockScore,
        ChemScore, X-Score, GoldScore, DFIRE and PMF. In addition, we have scored
        the complexes with more intensive GBSA and PBSA approaches requiring an additional
        120 000 cpu-hours on the TeraGrid. We constructed a simple interface to enable
        users to view top-ranking molecules and access purchasing and other information
        for further experimental exploration. © The Author(s) 2009. Published by Oxford
        University Press.
      authors:
      - name: Li L.
      - name: Bum-Erdene K.
      - name: Baenziger P.H.
      - name: Rosen J.J.
      - name: Hemmert J.R.
      - name: Nellis J.A.
      - name: Pierce M.E.
      - name: Meroueh S.O.
      citationCount: 32
      date: '2009-11-18T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'BioDrugScreen: A computational drug design resource for ranking molecules
        docked to the human proteome'
    note: null
    pmcid: PMC2808957
    pmid: '19923229'
    type: []
    version: null
  relation: []
  toolType:
  - Database portal
  topic:
  - term: Drug discovery
    uri: http://edamontology.org/topic_3336
  - term: Small molecules
    uri: http://edamontology.org/topic_0154
  - term: Medicinal chemistry
    uri: http://edamontology.org/topic_0209
  - term: Humans
    uri: http://edamontology.org/topic_2815
  - term: Proteomics
    uri: http://edamontology.org/topic_0121
  validated: 1
  version: []
- accessibility: null
  additionDate: '2017-01-17T14:51:06Z'
  biotoolsCURIE: biotools:biolccc
  biotoolsID: biolccc
  collectionID:
  - ms-utils
  - Proteomics
  confidence_flag: null
  cost: null
  credit:
  - 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: An analytic model of peptide retention.
  documentation:
  - note: null
    type:
    - General
    url: http://theorchromo.ru/
  download:
  - note: null
    type: Source code
    url: http://packages.python.org/pyteomics.biolccc/API/mespaceBioLCCC.html
    version: null
  editPermission:
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    type: group
  elixirCommunity: []
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  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Protein sequence
        uri: http://edamontology.org/data_2976
      format:
      - term: Textual format
        uri: http://edamontology.org/format_2330
    note: null
    operation:
    - term: Retention time prediction
      uri: http://edamontology.org/operation_3633
    output:
    - data:
        term: Peptide property
        uri: http://edamontology.org/data_2979
      format:
      - term: HTML
        uri: http://edamontology.org/format_2331
  homepage: http://theorchromo.ru/
  homepage_status: 0
  language: []
  lastUpdate: '2024-11-25T14:16:48.686997Z'
  license: null
  link:
  - note: null
    type:
    - Software catalogue
    url: http://ms-utils.org
  maturity: null
  name: BioLCCC
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: msutils_import
  publication:
  - doi: 10.1021/ac060913x
    metadata:
      abstract: 'An approach to sequence-dependent retention time prediction of peptides
        based on the concept of liquid chromatography at critical conditions (LCCC)
        is presented. Within the LCCC approach applied to biopolymers (BioLCCC), the
        specific retention time corresponds to a particular sequence. In combination
        with mass spectrometry, this approach provides an efficient tool to solve
        problems wherein the protein sequencing is essential. In this work, we present
        a theoretical background of the BioLCCC concept and demonstrate experimentally
        its feasibility for sequence-dependent LC retention time prediction for peptides.
        BioLCCC model is based on three notions: (a) a random walk model for a macromolecule
        chain; (b) an entropy and energy compensation for the macromolecules within
        the adsorbent pore; and (c) a set of phenomenological parameters for the effective
        interaction energies of interactions between the amino acid residues and the
        adsorbent surface. In this work, the phenomenological parameters have been
        obtained for C18 reversed-phase HPLC. Note, that contrary to alternative additive
        models for retention time prediction based on summation of the so-called "retention
        coefficients", the BioLCCC approach takes into account the location of amino
        acids within the primary structure of a peptide and, thus, allows the identification
        of the peptides having the same composition of amino acids but differing by
        their arrangement. As a result, this new approach allows prediction of retention
        time for any possible amino acid sequence in particular HPLC experiments.
        In addition, the BioLCCC model lacks of main drawbacks of additive approaches
        that predict retention time for sequences of limited chain lengths and provide
        information about amino acid composition only. The proposed BioLCCC approach
        was characterized experimentally using LTQ FT LC-MS and LC-MS/MS data obtained
        earlier for Escherichia coli. The HPLC system calibration was performed using
        peptide retention standards. The results received show a linear correlation
        between predicted and experimental retention times, with a correlation coefficient,
        R2, of 0.97 for a peptide standard mixture and 0.9 for E. coli data, respectively,
        with the standard error below 1 min. The work presents the first description
        of a BioLCCC approach for high-throughput peptide characterization and preliminary
        results of its feasibility tests. © 2006 American Chemical Society.'
      authors:
      - name: Gorshkov A.V.
      - name: Tarasova I.A.
      - name: Evreinov V.V.
      - name: Savitski M.M.
      - name: Nielsen M.L.
      - name: Zubarev R.A.
      - name: Gorshkov M.V.
      citationCount: 71
      date: '2006-11-15T00:00:00Z'
      journal: Analytical Chemistry
      title: 'Liquid chromatography at critical conditions: Comprehensive approach
        to sequence-dependent retention time prediction'
    note: null
    pmcid: null
    pmid: '17105170'
    type: []
    version: null
  relation: []
  toolType:
  - Web application
  topic:
  - term: Proteomics
    uri: http://edamontology.org/topic_0121
  - term: Proteomics experiment
    uri: http://edamontology.org/topic_3520
  validated: 1
  version: []
- accessibility: null
  additionDate: '2017-08-03T18:37:44Z'
  biotoolsCURIE: biotools:bioplib
  biotoolsID: bioplib
  collectionID:
  - Proteomics
  confidence_flag: null
  cost: null
  credit:
  - email: andrew@bioinf.org.uk
    fundrefid: null
    gridid: null
    name: Dr. Andrew C.R. Martin
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: http://www.bioinf.org.uk/
  description: Library of C routines for general programming and handling protein
    structure
  documentation:
  - note: null
    type:
    - General
    url: http://www.bioinf.org.uk/software/bioplib/bioplib/doc/html/pages.html
  download: []
  editPermission:
    authors:
    - proteomics.bio.tools
    type: group
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Protein sequence analysis
      uri: http://edamontology.org/operation_2479
    output: []
  homepage: http://www.bioinf.org.uk/software/bioplib/index.html
  homepage_status: 0
  language:
  - C
  lastUpdate: '2024-11-25T14:16:47.356007Z'
  license: null
  link:
  - note: null
    type:
    - Software catalogue
    url: http://www.mybiosoftware.com/bioptools-1-1-a-set-of-command-line-tools-for-manipulating-protein-structure.html
  maturity: null
  name: BiopLib
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: mbs_import
  publication:
  - doi: 10.1093/bioinformatics/btv482
    metadata:
      abstract: We describe BiopLib, a mature C programming library for manipulating
        protein structure, and BiopTools, a set of command-line tools which exploit
        BiopLib. The library also provides a small number of functions for handling
        protein sequence and general purpose programming and mathematics. BiopLib
        transparently handles PDBML (XML) format and standard PDB files. BiopTools
        provides facilities ranging from renumbering atoms and residues to calculation
        of solvent accessibility.
      authors:
      - name: Porter C.T.
      - name: Martin A.C.R.
      citationCount: 12
      date: '2015-07-03T00:00:00Z'
      journal: Bioinformatics
      title: BiopLib and BiopTools - A C programming library and toolset for manipulating
        protein structure
    note: null
    pmcid: PMC4673973
    pmid: '26323716'
    type: []
    version: null
  relation: []
  toolType:
  - Command-line tool
  topic:
  - term: Protein structure analysis
    uri: http://edamontology.org/topic_2814
  - term: Proteomics
    uri: http://edamontology.org/topic_0121
  - term: Protein structural motifs and surfaces
    uri: http://edamontology.org/topic_0166
  validated: 1
  version: []
- accessibility: null
  additionDate: '2018-03-06T08:13:57Z'
  biotoolsCURIE: biotools:biosunms
  biotoolsID: biosunms
  collectionID:
  - Proteomics
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: labs.net@gmail.com
    fundrefid: null
    gridid: null
    name: null
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  description: Management of patients information and the analysis of peptide profiles
    from mass spectrometry.
  documentation:
  - note: null
    type:
    - General
    url: https://sourceforge.net/p/biosunms/wiki/Home/
  download:
  - note: null
    type: Binaries
    url: https://sourceforge.net/projects/biosunms/files/latest/download
    version: null
  editPermission:
    authors:
    - proteomics.bio.tools
    type: group
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Spectral analysis
      uri: http://edamontology.org/operation_3214
    output: []
  homepage: http://biosunms.sourceforge.net/
  homepage_status: 0
  language: []
  lastUpdate: '2024-11-25T14:16:46.069559Z'
  license: GPL-1.0
  link: []
  maturity: null
  name: BioSunMS
  operatingSystem: []
  otherID: []
  owner: jison
  publication:
  - doi: 10.1186/1472-6947-9-13
    metadata:
      abstract: Background. With wide applications of matrix-assisted laser desorption/ionization
        time-of-flight mass spectrometry (MALDI-TOF MS) and surface-enhanced laser
        desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS), statistical
        comparison of serum peptide profiles and management of patients information
        play an important role in clinical studies, such as early diagnosis, personalized
        medicine and biomarker discovery. However, current available software tools
        mainly focused on data analysis rather than providing a flexible platform
        for both the management of patients information and mass spectrometry (MS)
        data analysis. Results. Here we presented a plug-in-based software, BioSunMS,
        for both the management of patients information and serum peptide profiles-based
        statistical analysis. By integrating all functions into a user-friendly desktop
        application, BioSunMS provided a comprehensive solution for clinical researchers
        without any knowledge in programming, as well as a plug-in architecture platform
        with the possibility for developers to add or modify functions without need
        to recompile the entire application. Conclusion. BioSunMS provides a plug-in-based
        solution for managing, analyzing, and sharing high volumes of MALDI-TOF or
        SELDI-TOF MS data. The software is freely distributed under GNU General Public
        License (GPL) and can be downloaded from http://sourceforge.net/projects/biosunms/.
        © 2009 Cao et al; licensee BioMed Central Ltd.
      authors:
      - name: Cao Y.
      - name: Wang N.
      - name: Ying X.
      - name: Li A.
      - name: Wang H.
      - name: Zhang X.
      - name: Li W.
      citationCount: 5
      date: '2009-01-01T00:00:00Z'
      journal: BMC Medical Informatics and Decision Making
      title: 'BioSunMS: A plug-in-based software for the management of patients information
        and the analysis of peptide profiles from mass spectrometry'
    note: null
    pmcid: PMC2654546
    pmid: '19220920'
    type:
    - Primary
    version: null
  relation: []
  toolType:
  - Plug-in
  topic:
  - term: Proteomics
    uri: http://edamontology.org/topic_0121
  validated: 1
  version: []
- accessibility: null
  additionDate: '2017-02-07T13:52:13Z'
  biotoolsCURIE: biotools:bioverse
  biotoolsID: bioverse
  collectionID:
  - Proteomics
  confidence_flag: null
  cost: null
  credit: []
  description: System that uses computational techniques to facilitate exploring the
    relationships between molecular, genomic, proteomic, systems and organismal information.
  documentation: []
  download: []
  editPermission:
    authors:
    - proteomics.bio.tools
    type: group
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Molecular replacement
      uri: http://edamontology.org/operation_3455
    - term: Relation inference
      uri: http://edamontology.org/operation_3625
    output: []
  homepage: http://bioverse.compbio.washington.edu/
  homepage_status: 0
  language: []
  lastUpdate: '2024-11-25T14:16:41.109381Z'
  license: null
  link: []
  maturity: null
  name: Bioverse
  operatingSystem: []
  otherID: []
  owner: ELIXIR-EE
  publication:
  - doi: 10.1093/nar/gkg550
    metadata:
      abstract: Functional annotation is routinely performed for large-scale genomics
        projects and databases. Researchers working on more specific problems, for
        instance on an individual pathway or complex, also need to be able to quickly,
        completely and accurately annotate sequences. The Bioverse sequence annotation
        server (http://bioverse.compbio.washington.edu) provides a web-based interface
        to allow users to submit protein sequences to the Bioverse framework. Sequences
        are functionally and structurally annotated and potential contextual annotations
        are provided. Researchers can also submit candidate genomes for annotation
        of all proteins encoded by the genome (proteome).
      authors:
      - name: McDermott J.
      - name: Samudrala R.
      citationCount: 19
      date: '2003-07-01T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'Bioverse: Functional, structural and contextual annotation of proteins
        and proteomes'
    note: null
    pmcid: PMC168957
    pmid: '12824406'
    type: []
    version: null
  - doi: 10.1093/bioinformatics/bti514
    metadata:
      abstract: 'Motivation: Progress in large-scale experimental determination of
        protein-protein interaction networks for several organisms has resulted in
        innovative methods of functional inference based on network connectivity.
        However, the amount of effort and resources required for the elucidation of
        experimental protein interaction networks is prohibitive. Previously we, and
        others, have developed techniques to predict protein interactions for novel
        genomes using computational methods and data generated from other genomes.
        Results: We evaluated the performance of a network-based functional annotation
        method that makes use of our predicted protein interaction networks. We show
        that this approach performs equally well on experimentally derived and predicted
        interaction networks, for both manually and computationally assigned annotations.
        We applied the method to predicted protein interaction networks for over 50
        organisms from all domains of life, providing annotations for many previously
        unannotated proteins and verifying existing low-confidence annotations. ©
        The Author 2005. Published by Oxford University Press. All rights reserved.'
      authors:
      - name: McDermott J.
      - name: Bumgarner R.
      - name: Samudrala R.
      citationCount: 46
      date: '2005-08-01T00:00:00Z'
      journal: Bioinformatics
      title: Functional annotation from predicted protein interaction networks
    note: null
    pmcid: null
    pmid: '15919725'
    type: []
    version: null
  - doi: 10.1093/nar/gki401
    metadata:
      abstract: 'We have made a number of enhancements to the previously described
        Bioverse web server and computational biology framework (http:// bioverse.compbio.washington.edu).
        In this update, we provide an overview of the new features available that
        include: (i) expansion of the number of organisms represented in the Bioverse
        and addition of new data sources and novel prediction techniques not available
        elsewhere, including network-based annotation; (ii) reengineering the database
        backend and supporting code resulting in significant speed, search and ease-of
        use improvements; and (iii) creation of a stateful and dynamic web application
        frontend to improve interface speed and usability. Integrated Java-based applications
        also allow dynamic visualization of real and predicted protein interaction
        networks. © 2005 Oxford University Press.'
      authors:
      - name: McDermott J.
      - name: Guerquin M.
      - name: Frazier Z.
      - name: Chang A.N.
      - name: Samudrala R.
      citationCount: 15
      date: '2005-07-01T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'BIOVERSE: Enhancements to the framework for structural, functional and
        contextual modeling of proteins and proteomes'
    note: null
    pmcid: PMC1160162
    pmid: '15980482'
    type: []
    version: null
  - doi: 10.1016/j.tibtech.2003.11.010
    metadata:
      abstract: Experimentally derived genome-wide protein interaction networks have
        been useful in the elucidation of functional information that is not evident
        from examining individual proteins but determination of these networks is
        complex and time consuming. To address this problem, several computational
        methods for predicting protein networks in novel genomes have been developed.
        A recent publication by Date and Marcotte describes the use of phylogenetic
        profiling for elucidating novel pathways in proteomes that have not been experimentally
        characterized. This method, in combination with other computational methods
        for generating protein-interaction networks, might help identify novel functional
        pathways and enhance functional annotation of individual proteins.
      authors:
      - name: McDermott J.
      - name: Samudrala R.
      - name: Date S.V.
      - name: Marcotte E.M.
      citationCount: 18
      date: '2004-01-01T00:00:00Z'
      journal: Trends in Biotechnology
      title: Enhanced functional information from predicted protein networks
    note: null
    pmcid: null
    pmid: '14757037'
    type: []
    version: null
  relation: []
  toolType:
  - Web application
  topic:
  - term: Proteomics
    uri: http://edamontology.org/topic_0121
  - term: Molecular interactions, pathways and networks
    uri: http://edamontology.org/topic_0602
  validated: 1
  version: []
next: ?page=2
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