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    metadata:
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  - term: Molecular interactions, pathways and networks
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  toolType:
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    typeEntity: Person
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  description: A suite of protein identification tools.
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    metadata:
      abstract: A thorough analysis of the protein interaction partners of the yeast
        GTPase Gsp1p was carried out by a multidimensional chromatography strategy
        of strong cation exchange fractionation of peptides followed by reverse phase
        LC-ESI-MSMS using a QSTAR instrument. This dataset was then analyzed using
        the latest developmental version of Protein Prospector. The Prospector search
        results were also compared with results from the search engine "Mascot" using
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        The results from this study demonstrate that the high quality data produced
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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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        spectrometry dataset acquired on a quadrupole selecting, quadrupole collision
        cells, time-of-flight mass spectrometer: II New developments in protein prospector
        allow for reliable and comprehensive automatic analysis of large datasets'
    note: null
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    version: null
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    uri: http://edamontology.org/topic_0121
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  - term: Database management
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  description: Make2D-DB II is an environment to create, convert, publish, interconnect
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    update data related to numerous external data resources. It is also possible to
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    metadata:
      abstract: The Make 2D-DB tool has been previously developed to help build federated
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        The purpose of our work is to extend the strength of the first package and
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        to fulfill the different needs and requirements arising from both the growing
        use of 2-DE techniques and the increasing amount of distributed experimental
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      authors:
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      - name: Hoogland C.
      - name: Binz P.-A.
      - name: Appel R.D.
      citationCount: 27
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    note: null
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  additionDate: '2017-12-06T18:14:54Z'
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  description: Calculator of peptide and glycopeptide masses. It is purposefully kept
    as simple as a basic calculator executing arithmetic operations.
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    type:
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  toolType:
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  topic:
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  - term: Structural genomics
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  - term: Protein modifications
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  biotoolsCURIE: biotools:glydin
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  description: Glydin' compiles and maps information relative to glycoepitopes (glycan
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  additionDate: '2023-07-25T12:35:27.605861Z'
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    name: Julian Uszkoreit
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    url: null
  - email: dirk.winkelhardt@rub.de
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  description: A Database to Quickly Access All Tryptic Peptides of the UniProtKB
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  homepage: https://macpepdb.cubimed.rub.de/
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  language:
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  - JavaScript
  - Other
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  link:
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  - note: Frontend implementation written in Rust / Dioxus
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  - doi: 10.1021/acs.jproteome.0c00967
    metadata:
      abstract: Protein sequence databases play a crucial role in the majority of
        the currently applied mass-spectrometry-based proteomics workflows. Here UniProtKB
        serves as one of the major sources, as it combines the information of several
        smaller databases and enriches the entries with additional biological information.
        For the identification of peptides in a sample by tandem mass spectra, as
        generated by data-dependent acquisition, protein sequence databases provide
        the basis for most spectrum identification search engines. In addition, for
        targeted proteomics approaches like selected reaction monitoring (SRM) and
        parallel reaction monitoring (PRM), knowledge of the peptide sequences, their
        masses, and whether they are unique for a protein is essential. Because most
        bottom-up proteomics approaches use trypsin to cleave the proteins in a sample,
        the tryptic peptides contained in a protein database are of great interest.
        We present a database, called MaCPepDB (mass-centric peptide database), that
        consists of the complete tryptic digest of the Swiss-Prot and TrEMBL parts
        of UniProtKB. This database is especially designed to not only allow queries
        of peptide sequences and return the respective information about connected
        proteins and thus whether a peptide is unique but also allow queries of specific
        masses of peptides or precursors of MS/MS spectra. Furthermore, posttranslational
        modifications can be considered in a query as well as different mass deviations
        for posttranslational modifications. Hence the database can be used by a sequence
        query not only to, for example, check in which proteins of the UniProt database
        a tryptic peptide can be found but also to find possibly interfering peptides
        in PRM/SRM experiments using the mass query. The complete database contains
        currently 5 939 244 990 peptides from 185 561 610 proteins (UniProt version
        2020_03), for which a single query usually takes less than 1 s. For easy exploration
        of the data, a web interface was developed. A REST application programming
        interface (API) for programmatic and workflow access is also available at
        https://macpepdb.mpc.rub.de.
      authors:
      - name: Uszkoreit J.
      - name: Winkelhardt D.
      - name: Barkovits K.
      - name: Wulf M.
      - name: Roocke S.
      - name: Marcus K.
      - name: Eisenacher M.
      citationCount: 9
      date: '2021-04-02T00:00:00Z'
      journal: Journal of Proteome Research
      title: 'MaCPepDB: A Database to Quickly Access All Tryptic Peptides of the UniProtKB'
    note: null
    pmcid: null
    pmid: '33724838'
    type:
    - Primary
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    uri: http://edamontology.org/topic_0121
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  version:
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- accessibility: null
  additionDate: '2019-11-27T10:47:08Z'
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    type:
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    input:
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    - data:
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    note: null
    operation:
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    - term: Query and retrieval
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      format: []
    - data:
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        uri: http://edamontology.org/data_3786
      format: []
    - data:
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  homepage_status: 0
  language:
  - R
  - Ruby
  - Java
  - Python
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  - term: Protein interactions
    uri: http://edamontology.org/topic_0128
  - term: Machine learning
    uri: http://edamontology.org/topic_3474
  - term: Protein interaction experiment
    uri: http://edamontology.org/topic_3957
  - term: Proteomics
    uri: http://edamontology.org/topic_0121
  - term: Small molecules
    uri: http://edamontology.org/topic_0154
  validated: 1
  version: []
- accessibility: Open access
  additionDate: '2025-06-12T11:47:48.641345Z'
  biotoolsCURIE: biotools:mzspeclib
  biotoolsID: mzspeclib
  collectionID: []
  confidence_flag: tool
  cost: Free of charge
  credit: []
  description: A python reference implementation of the mzSpecLib spectral library
    format.
  documentation:
  - note: null
    type:
    - API documentation
    url: https://hupo-psi.github.io/mzSpecLib/
  download:
  - note: null
    type: Source code
    url: https://github.com/HUPO-PSI/mzspeclib-py
    version: null
  - note: null
    type: Software package
    url: https://pypi.org/project/mzspeclib/
    version: null
  editPermission:
    authors: []
    type: public
  elixirCommunity:
  - Proteomics
  - Metabolomics
  elixirNode: []
  elixirPlatform:
  - Interoperability
  elixir_badge: 0
  function:
  - cmd: mzspeclib convert
    input:
    - data:
        term: Mass spectrum
        uri: http://edamontology.org/data_0943
      format:
      - term: MSP
        uri: http://edamontology.org/format_4039
      - term: MGF
        uri: http://edamontology.org/format_3651
    note: null
    operation:
    - term: Conversion
      uri: http://edamontology.org/operation_3434
    output:
    - data:
        term: Mass spectrum
        uri: http://edamontology.org/data_0943
      format: []
  - cmd: null
    input:
    - data:
        term: Mass spectrum
        uri: http://edamontology.org/data_0943
      format: []
    note: null
    operation:
    - term: Format validation
      uri: http://edamontology.org/operation_0336
    output:
    - data:
        term: Mass spectrum
        uri: http://edamontology.org/data_0943
      format: []
  homepage: https://github.com/HUPO-PSI/mzspeclib-py
  homepage_status: 0
  language:
  - Python
  lastUpdate: '2025-06-12T11:57:26.484553Z'
  license: APSL-2.0
  link:
  - note: null
    type:
    - Discussion forum
    url: https://www.psidev.info/
  - note: null
    type:
    - Repository
    url: https://github.com/HUPO-PSI/mzspeclib-py
  maturity: Mature
  name: mzspeclib
  operatingSystem: []
  otherID: []
  owner: recetox-specdatri
  publication:
  - doi: 10.1021/acs.analchem.4c04091
    metadata:
      abstract: Mass spectral libraries are collections of reference spectra, usually
        associated with specific analytes from which the spectra were generated, that
        are used for further downstream analysis of new spectra. There are many different
        formats used for encoding spectral libraries, but none have undergone a standardization
        process to ensure broad applicability to many applications. As part of the
        Human Proteome Organization Proteomics Standards Initiative (PSI), we have
        developed a standardized format for encoding spectral libraries, called mzSpecLib
        (https://psidev.info/mzSpecLib). It is primarily a data model that flexibly
        encodes metadata about the library entries using the extensible PSI-MS controlled
        vocabulary and can be encoded in and converted between different serialization
        formats. We have also developed a standardized data model and serialization
        for fragment ion peak annotations, called mzPAF (https://psidev.info/mzPAF).
        It is defined as a separate standard, since it may be used for other applications
        besides spectral libraries. The mzSpecLib and mzPAF standards are compatible
        with existing PSI standards such as ProForma 2.0 and the Universal Spectrum
        Identifier. The mzSpecLib and mzPAF standards have been primarily defined
        for peptides in proteomics applications with basic small molecule support.
        They could be extended in the future to other fields that need to encode spectral
        libraries for nonpeptidic analytes.
      authors:
      - name: Klein J.
      - name: Lam H.
      - name: Mak T.D.
      - name: Bittremieux W.
      - name: Perez-Riverol Y.
      - name: Gabriels R.
      - name: Shofstahl J.
      - name: Hecht H.
      - name: Binz P.-A.
      - name: Kawano S.
      - name: Van Den Bossche T.
      - name: Carver J.
      - name: Neely B.A.
      - name: Mendoza L.
      - name: Suomi T.
      - name: Claeys T.
      - name: Payne T.
      - name: Schulte D.
      - name: Sun Z.
      - name: Hoffmann N.
      - name: Zhu Y.
      - name: Neumann S.
      - name: Jones A.R.
      - name: Bandeira N.
      - name: Vizcaino J.A.
      - name: Deutsch E.W.
      citationCount: 1
      date: '2024-11-19T00:00:00Z'
      journal: Analytical Chemistry
      title: 'The Proteomics Standards Initiative Standardized Formats for Spectral
        Libraries and Fragment Ion Peak Annotations: mzSpecLib and mzPAF'
    note: null
    pmcid: null
    pmid: null
    type:
    - Primary
    version: null
  relation: []
  toolType:
  - Command-line tool
  - Library
  topic:
  - term: Proteomics
    uri: http://edamontology.org/topic_0121
  - term: Metabolomics
    uri: http://edamontology.org/topic_3172
  validated: 0
  version:
  - 1.0.5
- accessibility: null
  additionDate: '2017-01-17T14:51:29Z'
  biotoolsCURIE: biotools:peptideprophet
  biotoolsID: peptideprophet
  collectionID:
  - ms-utils
  - Proteomics
  confidence_flag: null
  cost: null
  credit:
  - email: nesvi@umich.edu
    fundrefid: null
    gridid: null
    name: nesvi@umich.edu
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Maintainer
    url: null
  - email: akeller@systemsbiology.org
    fundrefid: null
    gridid: null
    name: akeller@systemsbiology.org
    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: Validation of peptide identifications by MS/MS and database searches.
  documentation:
  - note: null
    type:
    - General
    url: http://tools.proteomecenter.org/wiki/index.php?title=Software:PeptideProphet
  download:
  - note: null
    type: Source code
    url: https://sourceforge.net/projects/peptideprophet/
    version: null
  editPermission:
    authors:
    - proteomics.bio.tools
    - n.m.palmblad@lumc.nl
    type: group
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Peptide identification
        uri: http://edamontology.org/data_0945
      format:
      - term: pepXML
        uri: http://edamontology.org/format_3655
      - term: HTML
        uri: http://edamontology.org/format_2331
    note: null
    operation:
    - term: Statistical modelling
      uri: http://edamontology.org/operation_3664
    - term: Variant filtering
      uri: http://edamontology.org/operation_3675
    - term: Peptide identification
      uri: http://edamontology.org/operation_3631
    - term: Target-Decoy
      uri: http://edamontology.org/operation_3649
    output:
    - data:
        term: Peptide identification
        uri: http://edamontology.org/data_0945
      format:
      - term: pepXML
        uri: http://edamontology.org/format_3655
      - term: HTML
        uri: http://edamontology.org/format_2331
  homepage: http://peptideprophet.sourceforge.net/index.html
  homepage_status: 0
  language:
  - C++
  - Perl
  lastUpdate: '2025-06-11T07:30:21.805189Z'
  license: null
  link:
  - note: null
    type:
    - Software catalogue
    url: http://ms-utils.org
  - note: null
    type:
    - Other
    url: http://tools.proteomecenter.org/PeptideProphet.php
  maturity: null
  name: PeptideProphet
  operatingSystem:
  - Linux
  - Mac
  - Windows
  otherID: []
  owner: msutils_import
  publication:
  - doi: 10.1021/ac025747h
    metadata:
      abstract: We present a statistical model to estimate the accuracy of peptide
        assignments to tandem mass (MS/MS) spectra made by database search applications
        such as SEQUEST. Employing the expectation maximization algorithm, the analysis
        learns to distinguish correct from incorrect database search results, computing
        probabilities that peptide assignments to spectra are correct based upon database
        search scores and the number of tryptic termini of peptides. Using SEQUEST
        search results for spectra generated from a sample of known protein components,
        we demonstrate that the computed probabilities are accurate and have high
        power to discriminate between correctly and incorrectly assigned peptides.
        This analysis makes it possible to filter large volumes of MS/MS database
        search results with predictable false identification error rates and can serve
        as a common standard by which the results of different research groups are
        compared.
      authors:
      - name: Keller A.
      - name: Nesvizhskii A.I.
      - name: Kolker E.
      - name: Aebersold R.
      citationCount: 4142
      date: '2002-10-15T00:00:00Z'
      journal: Analytical Chemistry
      title: Empirical statistical model to estimate the accuracy of peptide identifications
        made by MS/MS and database search
    note: null
    pmcid: null
    pmid: '12403597'
    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: Statistics and probability
    uri: http://edamontology.org/topic_2269
  validated: 1
  version: []
- accessibility: null
  additionDate: '2017-01-17T14:51:30Z'
  biotoolsCURIE: biotools:proteinprophet
  biotoolsID: proteinprophet
  collectionID:
  - ms-utils
  - Proteomics
  confidence_flag: tool
  cost: null
  credit:
  - email: nesvi@umich.edu
    fundrefid: null
    gridid: null
    name: nesvi@umich.edu
    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: Validation of protein identifications by MS/MS and database searches.
  documentation:
  - note: null
    type:
    - General
    url: http://tools.proteomecenter.org/wiki/index.php?title=Software:ProteinProphet
  download:
  - note: null
    type: Source code
    url: https://sourceforge.net/projects/proteinprophet/
    version: null
  editPermission:
    authors:
    - proteomics.bio.tools
    - n.m.palmblad@lumc.nl
    type: group
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Peptide identification
        uri: http://edamontology.org/data_0945
      format:
      - term: pepXML
        uri: http://edamontology.org/format_3655
      - term: HTML
        uri: http://edamontology.org/format_2331
    note: null
    operation:
    - term: Statistical modelling
      uri: http://edamontology.org/operation_3664
    - term: Protein identification
      uri: http://edamontology.org/operation_3767
    - term: Validation of peptide-spectrum matches
      uri: http://edamontology.org/operation_3648
    - term: de Novo sequencing
      uri: http://edamontology.org/operation_3644
    - term: Data filtering
      uri: http://edamontology.org/operation_3695
    output:
    - data:
        term: Peptide identification
        uri: http://edamontology.org/data_0945
      format:
      - term: XML
        uri: http://edamontology.org/format_2332
      - term: protXML
        uri: http://edamontology.org/format_3747
      - term: HTML
        uri: http://edamontology.org/format_2331
      - term: xls
        uri: http://edamontology.org/format_3468
  homepage: http://tools.proteomecenter.org/ProteinProphet.php
  homepage_status: 0
  language:
  - Perl
  - C
  lastUpdate: '2025-06-11T07:29:44.805939Z'
  license: null
  link:
  - note: null
    type:
    - Software catalogue
    url: http://ms-utils.org
  maturity: null
  name: ProteinProphet
  operatingSystem:
  - Linux
  - Mac
  - Windows
  otherID: []
  owner: msutils_import
  publication:
  - doi: null
    metadata:
      abstract: A statistical model is presented for computing probabilities that
        proteins are present in a sample on the basis of peptides assigned to tandem
        mass (MS/MS) spectra acquired from a proteolytic digest of the sample. Peptides
        that correspond to more than a single protein in the sequence database are
        apportioned among all corresponding proteins, and a minimal protein list sufficient
        to account for the observed peptide assignments is derived using the expectation-maximization
        algorithm. Using peptide assignments to spectra generated from a sample of
        18 purified proteins, as well as complex H. influenzae and Halobacterium samples,
        the model is shown to produce probabilities that are accurate and have high
        power to discriminate correct from incorrect protein identifications. This
        method allows filtering of large-scale proteomics data sets with predictable
        sensitivity and false positive identification error rates. Fast, consistent,
        and transparent, it provides a standard for publishing large-scale protein
        identification data sets in the literature and for comparing the results obtained
        from different experiments.
      authors:
      - name: Nesvizhskii A.I.
      - name: Keller A.
      - name: Kolker E.
      - name: Aebersold R.
      citationCount: 3996
      date: '2003-09-01T00:00:00Z'
      journal: Analytical Chemistry
      title: A statistical model for identifying proteins by tandem mass spectrometry
    note: null
    pmcid: null
    pmid: '14632076'
    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: Statistics and probability
    uri: http://edamontology.org/topic_2269
  validated: 1
  version: []
- accessibility: null
  additionDate: '2021-03-19T09:12:19Z'
  biotoolsCURIE: biotools:msi-r
  biotoolsID: msi-r
  collectionID: []
  confidence_flag: tool
  cost: null
  credit: []
  description: 'Adaptive Pixel Mass Recalibration for Mass Spectrometry Imaging Based
    on Locally Endogenous Biological Signals.


    Using Biological Signals for Mass Recalibration of Mass Spectrometry Imaging Data.


    This repository contains the python script performing the recalibration of mass
    spectrometry images (MSI) from the associated paper Using Biological Signals for
    Mass Recalibration of Mass Spectrometry Imaging Data.'
  documentation: []
  download: []
  editPermission:
    authors:
    - sizhengZhao
    type: group
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Mass spectrometry data
        uri: http://edamontology.org/data_2536
      format:
      - term: imzML metadata file
        uri: http://edamontology.org/format_3682
    - data:
        term: Mass spectrometry data
        uri: http://edamontology.org/data_2536
      format:
      - term: ibd
        uri: http://edamontology.org/format_3839
    - data:
        term: Data reference
        uri: http://edamontology.org/data_2093
      format:
      - term: Textual format
        uri: http://edamontology.org/format_2330
    note: null
    operation:
    - term: Mass spectra calibration
      uri: http://edamontology.org/operation_3627
    output:
    - data:
        term: Mass spectrometry data
        uri: http://edamontology.org/data_2536
      format:
      - term: imzML metadata file
        uri: http://edamontology.org/format_3682
    - data:
        term: Mass spectrometry data
        uri: http://edamontology.org/data_2536
      format:
      - term: ibd
        uri: http://edamontology.org/format_3839
  homepage: https://github.com/LaRoccaRaphael/MSI_recalibration
  homepage_status: 0
  language:
  - Python
  lastUpdate: '2025-06-05T11:49:34.683716Z'
  license: Apache-2.0
  link: []
  maturity: null
  name: MSI-R
  operatingSystem: []
  otherID: []
  owner: Niclaskn
  publication:
  - doi: 10.1021/acs.analchem.0c05071
    metadata:
      abstract: Mass spectrometry imaging (MSI) is a powerful and convenient method
        for revealing the spatial chemical composition of different biological samples.
        Molecular annotation of the detected signals is only possible if a high mass
        accuracy is maintained over the entire image and the m/z range. However, the
        change in the number of ions from pixel-to-pixel of the biological samples
        could lead to small fluctuations in the detected m/z-values, called mass shift.
        The use of internal calibration is known to offer the best solution to avoid,
        or at least to reduce, mass shifts. Their “a priori” selection for a global
        MSI acquisition is prone to false positive detection and therefore to poor
        recalibration. To fill this gap, this work describes an algorithm that recalibrates
        each spectrum individually by estimating its mass shift with the help of a
        list of pixel-specific internal calibrating ions, automatically generated
        in a data-adaptive manner (https://github.com/ LaRoccaRaphael/MSI_recalibration).
        Through a practical example, we applied the methodology to a zebrafish whole-body
        section acquired at a high mass resolution to demonstrate the impact of mass
        shift on data analysis and the capability of our algorithm to recalibrate
        MSI data. In addition, we illustrate the broad applicability of the method
        by recalibrating 31 different public MSI data sets from METASPACE from various
        samples and types of MSI and show that our recalibration significantly increases
        the numbers of METASPACE annotations (gaining from 20 up to 400 additional
        annotations), particularly the high-confidence annotations with a low false
        discovery rate.
      authors:
      - name: Rocca R.L.
      - name: Kune C.
      - name: Tiquet M.
      - name: Stuart L.
      - name: Eppe G.
      - name: Alexandrov T.
      - name: de Pauw E.
      - name: Quinton L.
      citationCount: 14
      date: '2021-03-02T00:00:00Z'
      journal: Analytical Chemistry
      title: Adaptive pixel mass recalibration for mass spectrometry imaging based
        on locally endogenous biological signals
    note: null
    pmcid: null
    pmid: '33583182'
    type: []
    version: null
  relation: []
  toolType:
  - Command-line tool
  topic:
  - term: Proteomics experiment
    uri: http://edamontology.org/topic_3520
  - term: Imaging
    uri: http://edamontology.org/topic_3382
  - term: Metabolomics
    uri: http://edamontology.org/topic_3172
  - term: Transcription factors and regulatory sites
    uri: http://edamontology.org/topic_0749
  validated: 0
  version: []
- accessibility: null
  additionDate: '2021-01-18T12:22:18Z'
  biotoolsCURIE: biotools:msiwarp
  biotoolsID: msiwarp
  collectionID: []
  confidence_flag: high
  cost: null
  credit:
  - email: p.l.horvatovich@rug.nl
    fundrefid: null
    gridid: null
    name: Peter Horvatovich
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  description: 'A General Approach to Mass Alignment in Mass Spectrometry Imaging.


    MSIWarp is a flexible tool to perform mass alignment of Mass Spectrometry Imaging
    (MSI) spectra. A key feature of MSIWarp is its compatibility with centroid spectra.'
  documentation: []
  download: []
  editPermission:
    authors:
    - sizhengZhao
    type: group
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Mass spectrometry data
        uri: http://edamontology.org/data_2536
      format:
      - term: imzML metadata file
        uri: http://edamontology.org/format_3682
    - data:
        term: Mass spectrometry data
        uri: http://edamontology.org/data_2536
      format:
      - term: ibd
        uri: http://edamontology.org/format_3839
    note: null
    operation:
    - term: Alignment
      uri: http://edamontology.org/operation_2928
    output:
    - data:
        term: Mass spectrometry data
        uri: http://edamontology.org/data_2536
      format:
      - term: imzML metadata file
        uri: http://edamontology.org/format_3682
    - data:
        term: Mass spectrometry data
        uri: http://edamontology.org/data_2536
      format:
      - term: ibd
        uri: http://edamontology.org/format_3839
  homepage: https://github.com/horvatovichlab/MSIWarp
  homepage_status: 0
  language:
  - C++
  - Python
  lastUpdate: '2025-06-05T11:41:35.873717Z'
  license: MIT
  link: []
  maturity: null
  name: MSIWarp
  operatingSystem: []
  otherID: []
  owner: Niclaskn
  publication:
  - doi: 10.1021/acs.analchem.0c03833
    metadata:
      abstract: Mass spectrometry imaging (MSI) is a technique that provides comprehensive
        molecular information with high spatial resolution from tissue. Today, there
        is a strong push toward sharing data sets through public repositories in many
        research fields where MSI is commonly applied; yet, there is no standardized
        protocol for analyzing these data sets in a reproducible manner. Shifts in
        the mass-to-charge ratio (m/z) of molecular peaks present a major obstacle
        that can make it impossible to distinguish one compound from another. Here,
        we present a label-free m/z alignment approach that is compatible with multiple
        instrument types and makes no assumptions on the sample's molecular composition.
        Our approach, MSIWarp (https://github.com/horvatovichlab/MSIWarp), finds an
        m/z recalibration function by maximizing a similarity score that considers
        both the intensity and m/z position of peaks matched between two spectra.
        MSIWarp requires only centroid spectra to find the recalibration function
        and is thereby readily applicable to almost any MSI data set. To deal with
        particularly misaligned or peak-sparse spectra, we provide an option to detect
        and exclude spurious peak matches with a tailored random sample consensus
        (RANSAC) procedure. We evaluate our approach with four publicly available
        data sets from both time-of-flight (TOF) and Orbitrap instruments and demonstrate
        up to 88% improvement in m/z alignment.
      authors:
      - name: Eriksson J.O.
      - name: Sanchez Brotons A.
      - name: Rezeli M.
      - name: Suits F.
      - name: Marko-Varga G.
      - name: Horvatovich P.
      citationCount: 15
      date: '2020-12-15T00:00:00Z'
      journal: Analytical Chemistry
      title: 'MSIWarp: A General Approach to Mass Alignment in Mass Spectrometry Imaging'
    note: null
    pmcid: PMC7745203
    pmid: '33317272'
    type: []
    version: null
  relation: []
  toolType:
  - Command-line tool
  topic:
  - term: Proteomics experiment
    uri: http://edamontology.org/topic_3520
  - term: Imaging
    uri: http://edamontology.org/topic_3382
  - term: Structure analysis
    uri: http://edamontology.org/topic_0081
  validated: 0
  version: []
- accessibility: Open access
  additionDate: '2021-05-26T20:42:18Z'
  biotoolsCURIE: biotools:maldi_quant
  biotoolsID: maldi_quant
  collectionID: []
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: mail@sebastiangibb.de
    fundrefid: null
    gridid: null
    name: Sebastian Gibb
    note: null
    orcidid: https://orcid.org/0000-0001-7406-4443
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    - Developer
    - Maintainer
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Korbinian Strimmer
    note: null
    orcidid: https://orcid.org/0000-0001-7917-2056
    rorid: null
    typeEntity: Person
    typeRole:
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    url: null
  description: MALDIquant is a complete analysis pipeline for matrix-assisted laser
    desorption/ionization-time-of-flight (MALDI-TOF) and other two-dimensional mass
    spectrometry data. In addition to commonly used plotting and processing methods
    it includes distinctive features, namely baseline subtraction methods such as
    morphological filters (TopHat) or the statistics-sensitive non-linear iterative
    peak-clipping algorithm (SNIP), peak alignment using warping functions, handling
    of replicated measurements as well as allowing spectra with different resolutions.
  documentation:
  - note: null
    type:
    - General
    url: https://cran.r-project.org/web/packages/MALDIquant/MALDIquant.pdf
  download: []
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  function:
  - cmd: null
    input:
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        term: Mass spectrometry data
        uri: http://edamontology.org/data_2536
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        uri: http://edamontology.org/format_3682
    - data:
        term: Mass spectrometry data
        uri: http://edamontology.org/data_2536
      format:
      - term: ibd
        uri: http://edamontology.org/format_3839
    note: null
    operation:
    - term: Quantification
      uri: http://edamontology.org/operation_3799
    - term: Spectrum calculation
      uri: http://edamontology.org/operation_3860
    - term: Peak detection
      uri: http://edamontology.org/operation_3215
    output:
    - data:
        term: Report
        uri: http://edamontology.org/data_2048
      format:
      - term: CSV
        uri: http://edamontology.org/format_3752
  - cmd: null
    input:
    - data:
        term: Mass spectrometry data
        uri: http://edamontology.org/data_2536
      format:
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    - data:
        term: Mass spectrometry data
        uri: http://edamontology.org/data_2536
      format:
      - term: ibd
        uri: http://edamontology.org/format_3839
    note: null
    operation:
    - term: Visualisation
      uri: http://edamontology.org/operation_0337
    output:
    - data:
        term: Plot
        uri: http://edamontology.org/data_2884
      format:
      - term: PNG
        uri: http://edamontology.org/format_3603
  - cmd: null
    input:
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        term: Mass spectrometry data
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    - data:
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      format:
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    note: null
    operation:
    - term: Mass spectra calibration
      uri: http://edamontology.org/operation_3627
    output:
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        term: Mass spectrometry data
        uri: http://edamontology.org/data_2536
      format:
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        uri: http://edamontology.org/format_3682
    - data:
        term: Mass spectrometry data
        uri: http://edamontology.org/data_2536
      format:
      - term: ibd
        uri: http://edamontology.org/format_3839
  homepage: https://cran.r-project.org/package=MALDIquant
  homepage_status: 0
  language:
  - R
  lastUpdate: '2025-06-05T11:28:57.497366Z'
  license: GPL-3.0
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/sgibb/MALDIquant/
  - note: null
    type:
    - Issue tracker
    url: https://github.com/sgibb/MALDIquant/issues
  - note: null
    type:
    - Other
    url: http://strimmerlab.org/software/maldiquant/
  maturity: null
  name: MALDIquant
  operatingSystem: []
  otherID: []
  owner: Kigaard
  publication:
  - doi: 10.1093/bioinformatics/bts447
    metadata:
      abstract: MALDIquant is an R package providing a complete and modular analysis
        pipeline for quantitative analysis of mass spectrometry data. MALDIquant is
        specifically designed with application in clinical diagnostics in mind and
        implements sophisticated routines for importing raw data, preprocessing, non-linear
        peak alignment and calibration. It also handles technical replicates as well
        as spectra with unequal resolution. © The Author 2012. Published by Oxford
        University Press. All rights reserved.
      authors:
      - name: Gibb S.
      - name: Strimmer K.
      citationCount: 499
      date: '2012-09-01T00:00:00Z'
      journal: Bioinformatics
      title: 'Maldiquant: A versatile R package for the analysis of mass spectrometry
        data'
    note: null
    pmcid: null
    pmid: '22796955'
    type:
    - Primary
    version: null
  relation: []
  toolType:
  - Library
  - Workflow
  topic:
  - term: Proteomics experiment
    uri: http://edamontology.org/topic_3520
  - term: Proteomics
    uri: http://edamontology.org/topic_0121
  validated: 0
  version: []
- accessibility: Open access
  additionDate: '2016-07-12T10:54:05Z'
  biotoolsCURIE: biotools:pia
  biotoolsID: pia
  collectionID:
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  - de.NBI
  - Proteomics
  - BioInfra.Prot
  - CUBiMed.RUB
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: julian.uszkoreit@rub.de
    fundrefid: null
    gridid: null
    name: Julian Uszkoreit
    note: null
    orcidid: http://orcid.org/0000-0001-7522-4007
    rorid: null
    typeEntity: Person
    typeRole:
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    - Developer
    - Maintainer
    url: null
  - email: cubimed@rub.de
    fundrefid: null
    gridid: null
    name: CUBiMed.RUB
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
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    url: null
  description: The main focus lays on the integrated inference algorithms, concluding
    the proteins from a set of identified spectra. But it also allows you to integrate
    results of various search engines, inspect your peptide spectrum matches, calculate
    FDR values across different results and visualize the correspondence between PSMs,
    peptides and proteins.
  documentation:
  - note: null
    type:
    - General
    url: https://github.com/medbioinf/pia/wiki
  download:
  - note: null
    type: Source code
    url: https://github.com/mpc-bioinformatics/pia
    version: null
  - note: null
    type: Software package
    url: http://bioconda.github.io/recipes/pia/README.html
    version: null
  - note: null
    type: Binaries
    url: https://github.com/mpc-bioinformatics/pia/releases
    version: null
  - note: null
    type: Container file
    url: https://hub.docker.com/r/julianusz/pia
    version: null
  editPermission:
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    type: private
  elixirCommunity:
  - Proteomics
  elixirNode:
  - Germany
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Mass spectrometry spectra
        uri: http://edamontology.org/data_0943
      format:
      - term: Mascot .dat file
        uri: http://edamontology.org/format_3713
      - term: mzIdentML
        uri: http://edamontology.org/format_3247
      - term: TSV
        uri: http://edamontology.org/format_3475
      - term: PRIDE XML
        uri: http://edamontology.org/format_3684
      - term: X!Tandem XML
        uri: http://edamontology.org/format_3711
      - term: MSF
        uri: http://edamontology.org/format_3702
      - term: mzTab
        uri: http://edamontology.org/format_3681
    note: PIA allows you to inspect the results of common proteomics spectrum identification
      search engines, combine them seamlessly and conduct statistical analyses. The
      main focus of PIA lays on the integrated inference algorithms, i.e. concluding
      the proteins from a set of identified spectra. But it also allows you to inspect
      your peptide spectrum matches, calculate FDR values across different search
      engine results and visualize the correspondence between PSMs, peptides and proteins.
      Search engine results in several formats peptide spectrum matches (PSMs) and
      peptides Inferred Proteins
    operation:
    - term: Protein identification
      uri: http://edamontology.org/operation_3767
    - term: Target-Decoy
      uri: http://edamontology.org/operation_3649
    output:
    - data:
        term: Peptide identification
        uri: http://edamontology.org/data_0945
      format:
      - term: Sequence feature table format (text)
        uri: http://edamontology.org/format_2206
      - term: KNIME datatable format
        uri: http://edamontology.org/format_3765
      - term: idXML
        uri: http://edamontology.org/format_3764
      - term: TSV
        uri: http://edamontology.org/format_3475
      - term: mzTab
        uri: http://edamontology.org/format_3681
      - term: mzIdentML
        uri: http://edamontology.org/format_3247
    - data:
        term: Protein identifier
        uri: http://edamontology.org/data_0989
      format:
      - term: Sequence feature table format (text)
        uri: http://edamontology.org/format_2206
      - term: KNIME datatable format
        uri: http://edamontology.org/format_3765
      - term: idXML
        uri: http://edamontology.org/format_3764
      - term: TSV
        uri: http://edamontology.org/format_3475
      - term: mzTab
        uri: http://edamontology.org/format_3681
      - term: mzIdentML
        uri: http://edamontology.org/format_3247
  homepage: https://github.com/medbioinf/pia
  homepage_status: 0
  language:
  - Java
  lastUpdate: '2025-05-02T13:15:26.717477Z'
  license: BSD-3-Clause
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/medbioinf/pia
  maturity: Mature
  name: PIA - Protein Inference Algorithms
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: julianu
  publication:
  - doi: 10.1021/acs.jproteome.5b00121
    metadata:
      abstract: Protein inference connects the peptide spectrum matches (PSMs) obtained
        from database search engines back to proteins, which are typically at the
        heart of most proteomics studies. Different search engines yield different
        PSMs and thus different protein lists. Analysis of results from one or multiple
        search engines is often hampered by different data exchange formats and lack
        of convenient and intuitive user interfaces. We present PIA, a flexible software
        suite for combining PSMs from different search engine runs and turning these
        into consistent results. PIA can be integrated into proteomics data analysis
        workflows in several ways. A user-friendly graphical user interface can be
        run either locally or (e.g., for larger core facilities) from a central server.
        For automated data processing, stand-alone tools are available. PIA implements
        several established protein inference algorithms and can combine results from
        different search engines seamlessly. On several benchmark data sets, we show
        that PIA can identify a larger number of proteins at the same protein FDR
        when compared to that using inference based on a single search engine. PIA
        supports the majority of established search engines and data in the mzIdentML
        standard format. It is implemented in Java and freely available at https://github.com/mpc-bioinformatics/pia.
      authors:
      - name: Uszkoreit J.
      - name: Maerkens A.
      - name: Perez-Riverol Y.
      - name: Meyer H.E.
      - name: Marcus K.
      - name: Stephan C.
      - name: Kohlbacher O.
      - name: Eisenacher M.
      citationCount: 57
      date: '2015-07-02T00:00:00Z'
      journal: Journal of Proteome Research
      title: 'PIA: An Intuitive Protein Inference Engine with a Web-Based User Interface'
    note: null
    pmcid: null
    pmid: '25938255'
    type:
    - Primary
    version: null
  - doi: 10.1021/acs.jproteome.8b00723
    metadata:
      abstract: Proteomics using LC-MS/MS has become one of the main methods to analyze
        the proteins in biological samples in high-throughput. But the existing mass-spectrometry
        instruments are still limited with respect to resolution and measurable mass
        ranges, which is one of the main reasons why shotgun proteomics is the major
        approach. Here proteins are digested, which leads to the identification and
        quantification of peptides instead. While often neglected, the important step
        of protein inference needs to be conducted to infer from the identified peptides
        to the actual proteins in the original sample. In this work, we highlight
        some of the previously published and newly added features of the tool PIA
        - Protein Inference Algorithms, which helps the user with the protein inference
        of measured samples. We also highlight the importance of the usage of PSI
        standard file formats, as PIA is the only current software supporting all
        available standards used for spectrum identification and protein inference.
        Additionally, we briefly describe the benefits of working with workflow environments
        for proteomics analyses and show the new features of the PIA nodes for the
        KNIME Analytics Platform. Finally, we benchmark PIA against a recently published
        data set for isoform detection. PIA is open source and available for download
        on GitHub (https://github.com/mpc-bioinformatics/pia) or directly via the
        community extensions inside the KNIME analytics platform.
      authors:
      - name: Uszkoreit J.
      - name: Perez-Riverol Y.
      - name: Eggers B.
      - name: Marcus K.
      - name: Eisenacher M.
      citationCount: 30
      date: '2019-02-01T00:00:00Z'
      journal: Journal of Proteome Research
      title: Protein Inference Using PIA Workflows and PSI Standard File Formats
    note: null
    pmcid: null
    pmid: '30474983'
    type: []
    version: null
  relation:
  - biotoolsID: knime
    type: uses
  toolType:
  - Command-line tool
  - Library
  - Desktop application
  - Workflow
  topic:
  - term: Proteomics
    uri: http://edamontology.org/topic_0121
  - term: Proteomics experiment
    uri: http://edamontology.org/topic_3520
  - term: Protein variants
    uri: http://edamontology.org/topic_3120
  validated: 1
  version:
  - '1.5'
- accessibility: null
  additionDate: '2016-01-19T16:39:56Z'
  biotoolsCURIE: biotools:openms
  biotoolsID: openms
  collectionID:
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  - de.NBI
  - Proteomics
  - OpenMS
  confidence_flag: null
  cost: Free of charge
  credit:
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    fundrefid: null
    gridid: null
    name: ETH Zürich
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
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    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Eberhard-Karls-Universität Tübingen
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
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    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Freie Universität Berlin
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
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    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
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    note: null
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    rorid: null
    typeEntity: Institute
    typeRole:
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    url: null
  - email: open-ms-general@lists.sourceforge.net
    fundrefid: null
    gridid: null
    name: General Mailinglist
    note: null
    orcidid: null
    rorid: null
    typeEntity: null
    typeRole:
    - Support
    url: null
  - email: open-ms-general@lists.sourceforge.net
    fundrefid: null
    gridid: null
    name: General Mailinglist
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
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    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Hannes Röst
    note: null
    orcidid: http://orcid.org/0000-0003-0990-7488
    rorid: null
    typeEntity: Person
    typeRole:
    - Contributor
    url: null
  description: Open source library and a collection of tools and interfaces for the
    analysis of mass spectrometry data. Includes over 200 standalone (TOPP) tools
    that can be combined to a workflow with the integrated workflow editor TOPPAS.
    Raw and intermediate mass spectrometry data can be visualised with the included
    viewer TOPPView.
  documentation:
  - note: null
    type:
    - General
    url: http://ftp.mi.fu-berlin.de/pub/OpenMS/release-documentation/html/index.html
  download:
  - note: null
    type: Source code
    url: https://github.com/OpenMS/OpenMS
    version: null
  - note: null
    type: Binaries
    url: http://sourceforge.net/projects/open-ms/files/OpenMS/OpenMS-2.0/
    version: null
  - note: null
    type: Source code
    url: https://github.com/OpenMS/OpenMS
    version: null
  editPermission:
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    type: group
  elixirCommunity: []
  elixirNode: []
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  elixir_badge: 0
  function:
  - cmd: null
    input:
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        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
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      - term: mzIdentML
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      - term: mzXML
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      - term: MGF
        uri: http://edamontology.org/format_3651
      - term: qcML
        uri: http://edamontology.org/format_3683
    - data:
        term: Sequence record
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      format:
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      - term: mzQuantML
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      - term: mzML
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      - term: mzXML
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      - term: MGF
        uri: http://edamontology.org/format_3651
      - term: qcML
        uri: http://edamontology.org/format_3683
    - data:
        term: Peptide identification
        uri: http://edamontology.org/data_0945
      format:
      - term: pepXML
        uri: http://edamontology.org/format_3655
      - term: mzQuantML
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      - 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: '2019-08-09T13:16:33Z'
  biotoolsCURIE: biotools:pyOpenMS
  biotoolsID: pyOpenMS
  collectionID: []
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: hannes.rost@utoronto.ca
    fundrefid: null
    gridid: null
    name: Hannes L. Rost
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  description: Python library for mass spectrometry, specifically for the analysis
    of proteomics and metabolomics data.
  documentation:
  - note: null
    type:
    - User manual
    url: https://pyopenms.readthedocs.io
  download: []
  editPermission:
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  homepage: https://github.com/OpenMS/pyopenms-extra/blob/master/docs/source/index.rst
  homepage_status: 0
  language:
  - Python
  lastUpdate: '2025-04-30T11:39:29.549782Z'
  license: BSD-3-Clause
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/OpenMS/pyopenms-extra
  - note: null
    type:
    - Issue tracker
    url: https://github.com/OpenMS/pyopenms-extra/issues
  maturity: Mature
  name: pyOpenMS
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: samwein
  publication:
  - doi: 10.7287/PEERJ.PREPRINTS.27736
    metadata: null
    note: null
    pmcid: null
    pmid: null
    type:
    - Primary
    version: null
  relation: []
  toolType:
  - Library
  topic:
  - term: Proteomics
    uri: http://edamontology.org/topic_0121
  - term: Proteomics experiment
    uri: http://edamontology.org/topic_3520
  - term: Protein modifications
    uri: http://edamontology.org/topic_0601
  validated: 1
  version: []
- 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
        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
    - data:
        term: Mass spectrometry spectra
        uri: http://edamontology.org/data_0943
      format:
      - term: TSV
        uri: http://edamontology.org/format_3475
      - term: TraML
        uri: http://edamontology.org/format_3246
    note: null
    operation:
    - term: Peak detection
      uri: http://edamontology.org/operation_3215
    - term: Chromatographic alignment
      uri: http://edamontology.org/operation_3628
    - term: Chromatogram visualisation
      uri: http://edamontology.org/operation_3203
    - term: Target-Decoy
      uri: http://edamontology.org/operation_3649
    output:
    - data:
        term: Peptide mass fingerprint
        uri: http://edamontology.org/data_0944
      format:
      - term: featureXML
        uri: http://edamontology.org/format_3833
      - term: TSV
        uri: http://edamontology.org/format_3475
      - term: SQLite format
        uri: http://edamontology.org/format_3621
  homepage: http://www.openswath.org
  homepage_status: 0
  language:
  - C++
  lastUpdate: '2025-04-30T11:39:29.102190Z'
  license: BSD-3-Clause
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/OpenSWATH/docker
  - note: null
    type:
    - Repository
    url: https://github.com/OpenMS/OpenMS
  - note: null
    type:
    - Mailing list
    url: https://sourceforge.net/projects/open-ms/lists/open-ms-general
  maturity: null
  name: OpenSWATH
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: samwein
  publication:
  - 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: '2021-01-18T11:10:26Z'
  biotoolsCURIE: biotools:openpepxl
  biotoolsID: openpepxl
  collectionID: []
  confidence_flag: tool
  cost: null
  credit:
  - email: eugen.netz@tuebingen.mpg.de
    fundrefid: null
    gridid: null
    name: Eugen Netz
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  - email: oliver.kohlbacher@uni-tuebingen.de
    fundrefid: null
    gridid: null
    name: Oliver Kohlbacher
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  description: 'An Open-Source Tool for Sensitive Identification of Cross-Linked Peptides
    in XL-MS.


    Protein-Protein Cross-Linking (OpenPepXL) – OpenMS.


    OpenPepXL is a protein-protein cross-link identification tool implemented in C++
    as part of OpenMS. It works with all uncleavable labeled and label-free cross-linkers
    but not (yet) with cleavable ones.'
  documentation: []
  download: []
  editPermission:
    authors: []
    type: private
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  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Peptide identification
      uri: http://edamontology.org/operation_3631
    - term: Deisotoping
      uri: http://edamontology.org/operation_3629
    - term: Protein identification
      uri: http://edamontology.org/operation_3767
    - term: Deposition
      uri: http://edamontology.org/operation_3431
    output: []
  homepage: https://openms.org/openpepxl
  homepage_status: 0
  language: []
  lastUpdate: '2025-04-30T11:39:28.349250Z'
  license: BSD-3-Clause
  link:
  - note: null
    type:
    - Other
    url: https://www.openms.de/openpepxl
  maturity: null
  name: OpenPepXL
  operatingSystem: []
  otherID: []
  owner: samwein
  publication:
  - doi: 10.1074/MCP.TIR120.002186
    metadata:
      abstract: © 2020 Netz et al. Published under exclusive license by The American
        Society for Biochemistry and Molecular Biology, Inc.Cross-linking MS (XL-MS)
        has been recognized as an effective source of information about protein structures
        and interactions. In contrast to regular peptide identification, XL-MS has
        to deal with a quadratic search space, where peptides from every protein could
        potentially be cross-linked to any other protein. To cope with this search
        space, most tools apply different heuristics for search space reduction. We
        introduce a new open-source XL-MS database search algorithm, OpenPepXL, which
        offers increased sensitivity compared with other tools. OpenPepXL searches
        the full search space of an XL-MS experiment without using heuristics to reduce
        it. Because of efficient data structures and built-in parallelization OpenPepXL
        achieves excellent runtimes and can also be deployed on large compute clusters
        and cloud services while maintaining a slim memory footprint. We compared
        OpenPepXL to several other commonly used tools for identification of noncleavable
        labeled and label-free cross-linkers on a diverse set of XL-MS experiments.
        In our first comparison, we used a data set from a fraction of a cell lysate
        with a protein database of 128 targets and 128 decoys. At 5% FDR, OpenPepXL
        finds from 7% to over 50% more unique residue pairs (URPs) than other tools.
        On data sets with available high-resolution structures for cross-link validation
        OpenPepXL reports from 7% to over 40% more structurally validated URPs than
        other tools. Additionally, we used a synthetic peptide data set that allows
        objective validation of cross-links without relying on structural information
        and found that OpenPepXL reports at least 12% more validated URPs than other
        tools. It has been built as part of the OpenMS suite of tools and supports
        Windows, macOS, and Linux operating systems. OpenPepXL also supports the MzIdentML
        1.2 format for XL-MS identification results. It is freely available under
        a three-clause BSD license at https://openms.org/openpepxl.
      authors:
      - name: Netz E.
      - name: Dijkstra T.M.H.
      - name: Sachsenberg T.
      - name: Zimmermann L.
      - name: Walzer M.
      - name: Monecke T.
      - name: Ficner R.
      - name: Dybkov O.
      - name: Urlaub H.
      - name: Kohlbacher O.
      citationCount: 0
      date: '2020-12-01T00:00:00Z'
      journal: Molecular and Cellular Proteomics
      title: 'OpenPepXL: An Open-Source Tool for Sensitive Identification of Cross-Linked
        Peptides in XL-MS'
    note: null
    pmcid: PMC7710140
    pmid: '33067342'
    type: []
    version: null
  relation: []
  toolType:
  - Command-line tool
  topic:
  - term: Proteomics experiment
    uri: http://edamontology.org/topic_3520
  - term: Small molecules
    uri: http://edamontology.org/topic_0154
  - term: Proteomics
    uri: http://edamontology.org/topic_0121
  validated: 0
  version: []
- accessibility: null
  additionDate: '2016-04-15T11:52:42Z'
  biotoolsCURIE: biotools:comparems2
  biotoolsID: comparems2
  collectionID:
  - ms-utils
  - Proteomics
  confidence_flag: tool
  cost: Free of charge
  credit:
  - email: null
    fundrefid: null
    gridid: null
    name: lumc.nl
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
    - Support
    url: https://www.lumc.nl
  - email: magnus.palmblad@gmail.com
    fundrefid: null
    gridid: null
    name: Magnus Palmblad
    note: null
    orcidid: http://orcid.org/0000-0002-5865-8994
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    - Primary contact
    - Documentor
    url: https://github.com/magnuspalmblad
  - email: null
    fundrefid: null
    gridid: null
    name: Rob Marissen
    note: null
    orcidid: https://orcid.org/0000-0002-1220-9173
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: https://github.com/524D
  description: compareMS2 is a tool for comparing sets of (tandem) mass spectra for
    clustering samples, molecular phylogenetics, identification of biological species
    or tissues, and quality control. compareMS2 currently consumes Mascot Generic
    Format, or MGF, and produces output in a variety of common image and distance
    matrix formats.
  documentation:
  - note: null
    type:
    - General
    - Command-line options
    url: http://www.ms-utils.org/compareMS2.html
  - note: null
    type:
    - General
    - User manual
    - Command-line options
    - Installation instructions
    url: https://github.com/524D/compareMS2
  download:
  - note: null
    type: Source code
    url: http://www.ms-utils.org/compareMS2.c
    version: '1.0'
  - note: null
    type: Binaries
    url: http://www.ms-utils.org/compareMS2.html
    version: '1.0'
  - note: null
    type: Source code
    url: http://www.ms-utils.org/compareMS2.c
    version: '1.0'
  - note: null
    type: Source code
    url: https://github.com/524D/compareMS2/tree/main/src
    version: '2.0'
  - note: null
    type: Binaries
    url: https://github.com/524D/compareMS2/tree/main
    version: '2.0'
  editPermission:
    authors:
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    type: group
  elixirCommunity:
  - Proteomics
  elixirNode:
  - Netherlands
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Mass spectrometry data
        uri: http://edamontology.org/data_2536
      format:
      - term: MGF
        uri: http://edamontology.org/format_3651
    note: null
    operation:
    - term: Comparison
      uri: http://edamontology.org/operation_2424
    - term: Phylogenetic tree visualisation
      uri: http://edamontology.org/operation_0567
    output:
    - data:
        term: Species tree
        uri: http://edamontology.org/data_3272
      format:
      - term: PNG
        uri: http://edamontology.org/format_3603
      - term: SVG
        uri: http://edamontology.org/format_3604
    - data:
        term: Distance matrix
        uri: http://edamontology.org/data_2855
      format:
      - term: mega
        uri: http://edamontology.org/format_1991
      - term: Nexus format
        uri: http://edamontology.org/format_1912
      - term: newick
        uri: http://edamontology.org/format_1910
  homepage: https://github.com/524D/compareMS2
  homepage_status: 0
  language:
  - C
  - JavaScript
  lastUpdate: '2025-04-16T14:22:04.957317Z'
  license: MIT
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/524D/compareMS2
  - note: null
    type:
    - Software catalogue
    url: https://www.ms-utils.org/compareMS2.html
  - note: null
    type:
    - Software catalogue
    url: https://research-software-directory.org/software/comparems2
  maturity: Mature
  name: compareMS2
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: n.m.palmblad@lumc.nl
  publication:
  - doi: 10.1002/rcm.6162
    metadata:
      abstract: 'Rationale: Molecular phylogenetics is the study of evolution and
        relatedness of organisms or genes. Mass spectrometry is used routinely for
        bacterial identification and has also been used for phylogenetic analysis,
        for instance from bone material. Unfortunately, only a small fraction of the
        acquired tandem mass spectra allow direct interpretation. Methods: We describe
        a new algorithm and software for molecular phylogenetics using pairwise comparisons
        of tandem mass spectra from enzymatically digested proteins. The spectra need
        not be annotated and all acquired data is used in the analysis. To demonstrate
        the method, we analyzed tryptic digests of sera from four great apes and two
        other primates. Results: The distribution of spectra dot products for thousands
        of tandem mass spectra collected from two samples provides a measure on the
        fraction of shared peptides between the two samples. When inverted, this becomes
        a distance metric. By pairwise comparison between species and averaging over
        four individuals per species, it was possible to reconstruct the unique correct
        phylogenetic tree for the great apes and other primates. Conclusions: The
        new method described here has several attractive features compared with existing
        methods, among them simplicity, the unbiased use of all acquired data rather
        than a small subset of spectra, and the potential use of heavily degraded
        proteins or proteins with a priori unknown modifications. © 2012 John Wiley
        & Sons, Ltd.'
      authors:
      - name: Palmblad M.
      - name: Deelder A.M.
      citationCount: 30
      date: '2012-04-15T00:00:00Z'
      journal: Rapid Communications in Mass Spectrometry
      title: Molecular phylogenetics by direct comparison of tandem mass spectra
    note: null
    pmcid: null
    pmid: '22368051'
    type:
    - Primary
    version: '1.0'
  - doi: 10.1021/acs.jproteome.2c00457
    metadata:
      abstract: It has long been known that biological species can be identified from
        mass spectrometry data alone. Ten years ago, we described a method and software
        tool, compareMS2, for calculating a distance between sets of tandem mass spectra,
        as routinely collected in proteomics. This method has seen use in species
        identification and mixture characterization in food and feed products, as
        well as other applications. Here, we present the first major update of this
        software, including a new metric, a graphical user interface and additional
        functionality. The data have been deposited to ProteomeXchange with dataset
        identifier PXD034932.
      authors:
      - name: Marissen R.
      - name: Varunjikar M.S.
      - name: Laros J.F.J.
      - name: Rasinger J.D.
      - name: Neely B.A.
      - name: Palmblad M.
      citationCount: 7
      date: '2023-02-03T00:00:00Z'
      journal: Journal of Proteome Research
      title: 'compareMS2 2.0: An Improved Software for Comparing Tandem Mass Spectrometry
        Datasets'
    note: null
    pmcid: PMC9903320
    pmid: '36173614'
    type:
    - Primary
    version: '2.0'
  - doi: 10.1021/acs.jproteome.1c00528
    metadata:
      abstract: Science is full of overlooked and undervalued research waiting to
        be rediscovered. Proteomics is no exception. In this perspective, we follow
        the ripples from a 1960 study of Zuckerkandl, Jones, and Pauling comparing
        tryptic peptides across animal species. This pioneering work directly led
        to the molecular clock hypothesis and the ensuing explosion in molecular phylogenetics.
        In the decades following, proteins continued to provide essential clues on
        evolutionary history. While technology has continued to improve, contemporary
        proteomics has strayed from this larger biological context, rarely comparing
        species or asking how protein structure, function, and interactions have evolved.
        Here we recombine proteomics with molecular phylogenetics, highlighting the
        value of framing proteomic results in a larger biological context and how
        almost forgotten research, though technologically surpassed, can still generate
        new ideas and illuminate our work from a different perspective. Though it
        is infeasible to read all research published on a large topic, looking up
        older papers can be surprisingly rewarding when rediscovering a "gem"at the
        end of a long citation chain, aided by digital collections and perpetually
        helpful librarians. Proper literature study reduces unnecessary repetition
        and allows research to be more insightful and impactful by truly standing
        on the shoulders of giants. All data was uploaded to MassIVE (https://massive.ucsd.edu/)
        as dataset MSV000087993.
      authors:
      - name: Neely B.A.
      - name: Palmblad M.
      citationCount: 1
      date: '2021-10-01T00:00:00Z'
      journal: Journal of Proteome Research
      title: 'Rewinding the Molecular Clock: Looking at Pioneering Molecular Phylogenetics
        Experiments in the Light of Proteomics'
    note: null
    pmcid: PMC8491155
    pmid: '34523928'
    type:
    - Review
    version: '2.0'
  relation: []
  toolType:
  - Command-line tool
  - Desktop application
  topic:
  - term: Phylogeny
    uri: http://edamontology.org/topic_0084
  - term: Proteomics
    uri: http://edamontology.org/topic_0121
  - term: Metabolomics
    uri: http://edamontology.org/topic_3172
  - term: Proteomics experiment
    uri: http://edamontology.org/topic_3520
  validated: 1
  version:
  - '1.0'
  - '2.0'
- accessibility: null
  additionDate: '2015-01-21T13:30:06Z'
  biotoolsCURIE: biotools:nextprot
  biotoolsID: nextprot
  collectionID:
  - Rare Disease
  - Proteomics
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: null
    fundrefid: null
    gridid: null
    name: SIB Swiss Institute of Bioinformatics
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
    - Provider
    url: null
  - email: support@nextprot.org
    fundrefid: null
    gridid: null
    name: Support
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Pascale Gaudet
    note: null
    orcidid: http://orcid.org/0000-0003-1813-6857
    rorid: null
    typeEntity: Person
    typeRole:
    - Contributor
    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:
    authors:
    - proteomics.bio.tools
    - mzahn
    - LanfearJ
    type: group
  elixirCommunity: []
  elixirNode:
  - Switzerland
  elixirPlatform:
  - Data
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Visualisation
      uri: http://edamontology.org/operation_0337
    - 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:
  - Database portal
  topic:
  - term: Model organisms
    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: Open access
  additionDate: '2025-03-28T11:13:12.813456Z'
  biotoolsCURIE: biotools:we_sa
  biotoolsID: we_sa
  collectionID: []
  confidence_flag: tool
  cost: Free of charge
  credit: []
  description: 'WeSA, (weighted socioaffinity), is a statistical score which can rank
    results from protein experiments of the bait-prey type, e.g. affinity purification,
    immunoprecipitation or proximity labelling.


    You can enter lists of interacting proteins according to the results of your experiment.
    Input your raw data before any filtering is done.


    As a result you will get a re-ordered list of scores which allows one to understand
    which interactions are more likely than others based on what previous experiments
    can add to your data.'
  documentation:
  - note: null
    type:
    - User manual
    url: https://wesa.russelllab.org/help
  download: []
  editPermission:
    authors: []
    type: private
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function: []
  homepage: https://wesa.russelllab.org/
  homepage_status: 0
  language:
  - Python
  lastUpdate: '2025-03-28T12:14:32.901305Z'
  license: null
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/russelllab/wesa
  maturity: null
  name: WeSA
  operatingSystem:
  - Mac
  - Linux
  - Windows
  otherID: []
  owner: Pub2Tools
  publication:
  - doi: 10.1093/nar/gkae423
    metadata:
      abstract: 'Protein-protein interaction experiments still yield many false positive
        interactions. The socioaffinity metric can distinguish true protein-protein
        interactions from noise based on available data. Here, we present WeSA (Weighted
        SocioAffinity), which considers large datasets of interaction proteomics data
        (IntAct, BioGRID, the BioPlex) to score human protein interactions and, in
        a statistically robust way, flag those (even from a single experiment) that
        are likely to be false positives. ROC analysis (using CORUM-PDB positives
        and Negatome negatives) shows that WeSA improves over other measures of interaction
        confidence. WeSA shows consistently good results over all datasets (up to:
        AUC = 0.93 and at best threshold: TPR = 0.84, FPR = 0.11, Precision = 0.98).
        WeSA is freely available without login (wesa.russelllab.org). Users can submit
        their own data or look for organized information on human protein interactions
        using the web server. Users can either retrieve available information for
        a list of proteins of interest or calculate scores for new experiments. The
        server outputs either pre-computed or updated WeSA scores for the input enriched
        with information from databases. The summary is presented as a table and a
        network-based visualization allowing the user to remove those nodes/edges
        that the method considers spurious.'
      authors:
      - name: Shtetinska M.M.
      - name: Gonzalez-Sanchez J.-C.
      - name: Beyer T.
      - name: Boldt K.
      - name: Ueffing M.
      - name: Russell R.B.
      citationCount: 1
      date: '2024-07-05T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'WeSA: A web server for improving analysis of affinity proteomics data'
    note: null
    pmcid: PMC11223876
    pmid: '38795065'
    type: []
    version: null
  relation: []
  toolType:
  - Web application
  topic:
  - term: Proteomics
    uri: http://edamontology.org/topic_0121
  - term: Protein interaction experiment
    uri: http://edamontology.org/topic_3957
  validated: 0
  version: []
- accessibility: Open access
  additionDate: '2025-02-28T15:04:33.594183Z'
  biotoolsCURIE: biotools:prolfquapp
  biotoolsID: prolfquapp
  collectionID: []
  confidence_flag: null
  cost: Free of charge
  credit: []
  description: A command-line tool for differential expression analysis in quantitative
    proteomics
  documentation:
  - note: null
    type:
    - General
    url: https://github.com/prolfqua/prolfquapp/blob/master/README.md
  download:
  - note: null
    type: Downloads page
    url: https://github.com/prolfqua/prolfquapp/releases/tag/0.1.6
    version: 0.1.6
  editPermission:
    authors:
    - thatmariia
    type: group
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: './prolfqua_dea.sh -i data_dir/ -d annotation.xlsx -y config.yaml -w NameOfAnalysis
      -s DIANN

      # and again you run the version within the docker container with

      # ./prolfquapp_docker.sh prolfqua_dea.sh -i data_dir/ -d annotation.xlsx -y
      config.yaml -w NameOfAnalysis -s DIANN'
    input:
    - data:
        term: Expression data
        uri: http://edamontology.org/data_2603
      format:
      - term: CSV
        uri: http://edamontology.org/format_3752
      - term: TSV
        uri: http://edamontology.org/format_3475
    - data:
        term: Sequence
        uri: http://edamontology.org/data_2044
      format:
      - term: FASTA
        uri: http://edamontology.org/format_1929
    note: null
    operation:
    - term: Differential protein expression profiling
      uri: http://edamontology.org/operation_3741
    output:
    - data:
        term: Expression data
        uri: http://edamontology.org/data_2603
      format:
      - term: xlsx
        uri: http://edamontology.org/format_3620
      - term: HTML
        uri: http://edamontology.org/format_2331
  - cmd: null
    input:
    - data:
        term: Expression data
        uri: http://edamontology.org/data_2603
      format:
      - term: xlsx
        uri: http://edamontology.org/format_3620
    note: null
    operation:
    - term: Validation
      uri: http://edamontology.org/operation_2428
    output:
    - data:
        term: Quality control report
        uri: http://edamontology.org/data_3914
      format:
      - term: HTML
        uri: http://edamontology.org/format_2331
  - cmd: null
    input:
    - data:
        term: Expression data
        uri: http://edamontology.org/data_2603
      format:
      - term: CSV
        uri: http://edamontology.org/format_3752
      - term: TSV
        uri: http://edamontology.org/format_3475
    - data:
        term: Protein sequence
        uri: http://edamontology.org/data_2976
      format:
      - term: FASTA
        uri: http://edamontology.org/format_1929
    note: null
    operation:
    - term: Expression data visualisation
      uri: http://edamontology.org/operation_0571
    output:
    - data:
        term: Expression data
        uri: http://edamontology.org/data_2603
      format:
      - term: PDF
        uri: http://edamontology.org/format_3508
      - term: HTML
        uri: http://edamontology.org/format_2331
  homepage: https://github.com/prolfqua/prolfquapp
  homepage_status: 0
  language:
  - R
  lastUpdate: '2025-03-28T10:18:25.715685Z'
  license: MIT
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/prolfqua/prolfquapp
  - note: null
    type:
    - Issue tracker
    url: https://github.com/prolfqua/prolfquapp/issues
  maturity: Emerging
  name: prolfquapp
  operatingSystem:
  - Mac
  - Linux
  otherID: []
  owner: n.m.palmblad@lumc.nl
  publication:
  - doi: 10.1021/acs.jproteome.4c00911
    metadata:
      abstract: Mass spectrometry is a cornerstone of quantitative proteomics, enabling
        relative protein quantification and differential expression analysis (DEA)
        of proteins. As experiments grow in complexity, involving more samples, groups,
        and identified proteins, interactive differential expression analysis tools
        become impractical. The prolfquapp addresses this challenge by providing a
        command-line interface that simplifies DEA, making it accessible to nonprogrammers
        and seamlessly integrating it into workflow management systems. Prolfquapp
        streamlines data processing and result visualization by generating dynamic
        HTML reports that facilitate the exploration of differential expression results.
        These reports allow for investigating complex experiments, such as those involving
        repeated measurements or multiple explanatory variables. Additionally, prolfquapp
        supports various output formats, including XLSX files, SummarizedExperiment
        objects and rank files, for further interactive analysis using spreadsheet
        software, the exploreDE Shiny application, or gene set enrichment analysis
        software, respectively. By leveraging advanced statistical models from the
        prolfqua R package, prolfquapp offers a user-friendly, integrated solution
        for large-scale quantitative proteomics studies, combining efficient data
        processing with insightful, publication-ready outputs.
      authors:
      - name: Wolski W.E.
      - name: Grossmann J.
      - name: Schwarz L.
      - name: Leary P.
      - name: Turker C.
      - name: Nanni P.
      - name: Schlapbach R.
      - name: Panse C.
      citationCount: 0
      date: '2025-02-07T00:00:00Z'
      journal: Journal of Proteome Research
      title: prolfquapp ─ A User-Friendly Command-Line Tool Simplifying Differential
        Expression Analysis in Quantitative Proteomics
    note: null
    pmcid: null
    pmid: null
    type: []
    version: 0.0.6
  relation: []
  toolType:
  - Command-line tool
  topic:
  - term: Proteomics
    uri: http://edamontology.org/topic_0121
  validated: 0
  version:
  - 0.1.6
- accessibility: Open access
  additionDate: '2021-01-18T09:08:27Z'
  biotoolsCURIE: biotools:metidfyr
  biotoolsID: metidfyr
  collectionID: []
  confidence_flag: tool
  cost: null
  credit: []
  description: 'Open-Source R Package to Decipher Small-Molecule Drugs Metabolism
    Through High Resolution Mass Spectrometry.


    MetIDfyR is an open-source, cross-platform and versatile R script to predict and
    detect metabolites in mass spectrometry data (mzML) based on the raw formula of
    the drug of interest.'
  documentation:
  - note: null
    type:
    - Quick start guide
    - Installation instructions
    - Citation instructions
    url: https://github.com/agnesbrnb/MetIDfyR
  download: []
  editPermission:
    authors: []
    type: private
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Mass spectrometry data
        uri: http://edamontology.org/data_2536
      format:
      - term: mzML
        uri: http://edamontology.org/format_3244
    - data:
        term: Chemical formula
        uri: http://edamontology.org/data_0846
      format: []
    note: null
    operation:
    - term: Natural product identification
      uri: http://edamontology.org/operation_3803
    - term: Phasing
      uri: http://edamontology.org/operation_3454
    output:
    - data:
        term: Report
        uri: http://edamontology.org/data_2048
      format:
      - term: TSV
        uri: http://edamontology.org/format_3475
    - data:
        term: Plot
        uri: http://edamontology.org/data_2884
      format:
      - term: SVG
        uri: http://edamontology.org/format_3604
  homepage: https://github.com/agnesbrnb/MetIDfyR
  homepage_status: 0
  language:
  - R
  lastUpdate: '2025-02-27T15:46:01.807140Z'
  license: GPL-3.0
  link: []
  maturity: null
  name: MetIDfyR
  operatingSystem: []
  otherID: []
  owner: agnesbarnabe
  publication:
  - doi: 10.1021/acs.analchem.0c02281
    metadata:
      abstract: With recent advances in analytical chemistry, liquid chromatography
        high-resolution tandem mass spectrometry (LC-HRMS/MS) has become an essential
        tool for metabolite discovery and detection. Even if most of the common drug
        transformations have already been extensively described, manual search of
        drug metabolites in LC-HRMS/MS datasets is still a common practice in toxicology
        laboratories, complicating metabolite discovery. Furthermore, the availability
        of free open-source software for metabolite discovery is still limited. In
        this article, we present MetIDfyR, an open-source and cross-platform R package
        for in silico drug phase I/II biotransformation prediction and mass-spectrometric
        data mining. MetIDfyR has proven its efficacy for advanced metabolite identification
        in semi-complex and complex mixtures in in vitro or in vivo drug studies and
        is freely available at github.com/agnesblch/MetIDfyR.
      authors:
      - name: Delcourt V.
      - name: Barnabe A.
      - name: Loup B.
      - name: Garcia P.
      - name: Andre F.
      - name: Chabot B.
      - name: Trevisiol S.
      - name: Moulard Y.
      - name: Popot M.-A.
      - name: Bailly-Chouriberry L.
      citationCount: 10
      date: '2020-10-06T00:00:00Z'
      journal: Analytical Chemistry
      title: 'MetIDfyR: An Open-Source R Package to Decipher Small-Molecule Drug Metabolism
        through High-Resolution Mass Spectrometry'
    note: null
    pmcid: null
    pmid: null
    type: []
    version: null
  relation: []
  toolType:
  - Command-line tool
  - Script
  topic:
  - term: Metabolomics
    uri: http://edamontology.org/topic_3172
  - term: Proteomics experiment
    uri: http://edamontology.org/topic_3520
  - term: Small molecules
    uri: http://edamontology.org/topic_0154
  - term: Drug metabolism
    uri: http://edamontology.org/topic_3375
  - term: Analytical chemistry
    uri: http://edamontology.org/topic_3370
  validated: 0
  version: []
- accessibility: Open access
  additionDate: '2025-01-31T17:19:47.094256Z'
  biotoolsCURIE: biotools:proteomaker
  biotoolsID: proteomaker
  collectionID:
  - Proteomics
  confidence_flag: null
  cost: Free of charge
  credit: []
  description: ProteoMaker is a platform for the generation of an in-silico bottom-up
    proteomics data set with a ground truth on the level of proteoforms.
  documentation: []
  download:
  - note: null
    type: Source code
    url: https://github.com/computproteomics/ProteoMaker
    version: null
  editPermission:
    authors: []
    type: private
  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
    note: null
    operation:
    - term: Simulated gene expression data generation
      uri: http://edamontology.org/operation_3566
    - term: Statistical calculation
      uri: http://edamontology.org/operation_2238
    output:
    - data:
        term: Gene expression matrix
        uri: http://edamontology.org/data_3112
      format:
      - term: CSV
        uri: http://edamontology.org/format_3752
    - data:
        term: Proteolytic digest
        uri: http://edamontology.org/data_1238
      format:
      - term: CSV
        uri: http://edamontology.org/format_3752
    - data:
        term: Quality control report
        uri: http://edamontology.org/data_3914
      format:
      - term: YAML
        uri: http://edamontology.org/format_3750
    - data:
        term: Statistical estimate score
        uri: http://edamontology.org/data_0951
      format:
      - term: CSV
        uri: http://edamontology.org/format_3752
  homepage: https://github.com/computproteomics/ProteoMaker
  homepage_status: 0
  language:
  - R
  lastUpdate: '2025-01-31T17:19:47.096981Z'
  license: MIT
  link:
  - note: Web application
    type:
    - Service
    url: https://computproteomics.bmb.sdu.dk/app_direct/ProteoMaker
  maturity: Mature
  name: ProteoMaker
  operatingSystem:
  - Mac
  - Linux
  - Windows
  otherID: []
  owner: veitveit11
  publication: []
  relation: []
  toolType:
  - Library
  - Web application
  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: 0
  version: []
- accessibility: null
  additionDate: '2021-01-18T10:23:20Z'
  biotoolsCURIE: biotools:metabomaps
  biotoolsID: metabomaps
  collectionID: []
  confidence_flag: tool
  cost: null
  credit:
  - email: meina.neumann-schaal@dsmz.de
    fundrefid: null
    gridid: null
    name: Meina Neumann-Schaal
    note: null
    orcidid: https://orcid.org/0000-0002-1641-019X
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  description: 'Pathway sharing and multi-omics data visualization in metabolic context.


    MetaboMAPS is a web project for manipulating metabolic pathways in SVG format.
    MetaboMAPS consists of two main parts: the visualization tool, where users can
    plot their own data set, and the plot box editor, where users can add or change
    the areas for visualization (plot boxes) and assign identifiers to them.'
  documentation: []
  download: []
  editPermission:
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  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Expression profile pathway mapping
      uri: http://edamontology.org/operation_0533
    - term: Metabolic pathway prediction
      uri: http://edamontology.org/operation_3929
    - term: Pathway visualisation
      uri: http://edamontology.org/operation_3926
    - term: Box-Whisker plot plotting
      uri: http://edamontology.org/operation_2943
    - term: Data retrieval
      uri: http://edamontology.org/operation_2422
    output: []
  homepage: https://metabomaps.brenda-enzymes.org
  homepage_status: 0
  language:
  - JavaScript
  lastUpdate: '2025-01-23T15:00:32.268669Z'
  license: GPL-3.0
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/JuliaHelmecke/MetaboMAPS
  maturity: null
  name: MetaboMAPS
  operatingSystem: []
  otherID: []
  owner: Niclaskn
  publication:
  - doi: 10.12688/F1000RESEARCH.23427.1
    metadata: null
    note: null
    pmcid: PMC7383707
    pmid: '32765840'
    type: []
    version: null
  relation: []
  toolType:
  - Library
  - Web application
  topic:
  - term: Endocrinology and metabolism
    uri: http://edamontology.org/topic_3407
  - term: Molecular interactions, pathways and networks
    uri: http://edamontology.org/topic_0602
  - term: Small molecules
    uri: http://edamontology.org/topic_0154
  - term: Metabolomics
    uri: http://edamontology.org/topic_3172
  - term: Proteomics
    uri: http://edamontology.org/topic_0121
  validated: 0
  version: []
- accessibility: Open access
  additionDate: '2025-01-14T09:14:56.273060Z'
  biotoolsCURIE: biotools:phistruct
  biotoolsID: phistruct
  collectionID: []
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: gonzales.markedward@gmail.com
    fundrefid: null
    gridid: null
    name: Mark Edward M. Gonzales
    note: Research Assistant, Bioinformatics Lab, Advanced Research Institute for
      Informatics, Computing and Networking, De La Salle University, Manila, Philippines
    orcidid: https://orcid.org/0000-0001-5050-3157
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: https://github.com/memgonzales
  - email: jennifer.ureta@gmail.com
    fundrefid: null
    gridid: null
    name: Jennifer C. Ureta
    note: Faculty, Bioinformatics Lab, Advanced Research Institute for Informatics,
      Computing and Networking, De La Salle University, Manila, Philippines
    orcidid: https://orcid.org/0000-0003-0427-5311
    rorid: null
    typeEntity: Person
    typeRole:
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    url: https://scholar.google.com/citations?user=v0Tf_u4AAAAJ&hl=en
  - email: anish.shrestha@dlsu.edu.ph
    fundrefid: null
    gridid: null
    name: Anish M.S. Shrestha
    note: Head, Bioinformatics Lab, Advanced Research Institute for Informatics, Computing
      and Networking, De La Salle University, Manila, Philippines
    orcidid: https://orcid.org/0000-0002-9192-9709
    rorid: null
    typeEntity: Person
    typeRole:
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    url: https://a-transposable-element.com/
  description: "PHIStruct is a phage-host interaction prediction tool that uses structure-aware\
    \ protein embeddings to represent the receptor-binding proteins (RBPs) of phages.\
    \ \n\nBy incorporating structure information, it presents improvements over using\
    \ sequence-only protein embeddings and feature-engineered sequence properties\
    \ — especially for phages with RBPs that have low sequence similarity to those\
    \ of known phages."
  documentation:
  - note: null
    type:
    - Installation instructions
    - Quick start guide
    - Citation instructions
    - Command-line options
    url: https://github.com/bioinfodlsu/PHIStruct
  download:
  - note: null
    type: Source code
    url: https://github.com/bioinfodlsu/PHIStruct
    version: null
  editPermission:
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  elixirNode: []
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  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Protein structure
        uri: http://edamontology.org/data_1460
      format:
      - term: PDB
        uri: http://edamontology.org/format_1476
    note: Predicts the host genus of a phage given its receptor-binding protein sequences
    operation:
    - term: Prediction and recognition
      uri: http://edamontology.org/operation_2423
    output:
    - data:
        term: Report
        uri: http://edamontology.org/data_2048
      format:
      - term: CSV
        uri: http://edamontology.org/format_3752
  homepage: https://github.com/bioinfodlsu/PHIStruct
  homepage_status: 0
  language:
  - Python
  lastUpdate: '2025-01-14T09:14:56.275331Z'
  license: MIT
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/bioinfodlsu/PHIStruct
  - note: null
    type:
    - Service
    url: http://phistruct.bioinfodlsu.com/
  maturity: Emerging
  name: PHIStruct
  operatingSystem:
  - Mac
  - Linux
  - Windows
  otherID: []
  owner: memgonzales
  publication:
  - doi: 10.1093/bioinformatics/btaf016
    metadata: null
    note: null
    pmcid: null
    pmid: '39804673'
    type:
    - Primary
    version: null
  relation: []
  toolType:
  - Command-line tool
  topic:
  - term: Machine learning
    uri: http://edamontology.org/topic_3474
  - term: Protein structure analysis
    uri: http://edamontology.org/topic_2814
  - term: Proteins
    uri: http://edamontology.org/topic_0078
  - term: Proteomics
    uri: http://edamontology.org/topic_0121
  - term: Computational biology
    uri: http://edamontology.org/topic_3307
  - term: Bioinformatics
    uri: http://edamontology.org/topic_0091
  - term: Virology
    uri: http://edamontology.org/topic_0781
  validated: 0
  version: []
- accessibility: Open access
  additionDate: '2024-05-05T10:53:14.688391Z'
  biotoolsCURIE: biotools:phiembed
  biotoolsID: phiembed
  collectionID: []
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: gonzales.markedward@gmail.com
    fundrefid: null
    gridid: null
    name: Mark Edward M. Gonzales
    note: Research Assistant, Bioinformatics Lab, Advanced Research Institute for
      Informatics, Computing and Networking, De La Salle University, Manila, Philippines
    orcidid: https://orcid.org/0000-0001-5050-3157
    rorid: null
    typeEntity: Person
    typeRole:
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    url: https://github.com/memgonzales
  - email: jennifer.ureta@gmail.com
    fundrefid: null
    gridid: null
    name: Jennifer C. Ureta
    note: Faculty, Bioinformatics Lab, Advanced Research Institute for Informatics,
      Computing and Networking, De La Salle University, Manila, Philippines
    orcidid: https://orcid.org/0000-0003-0427-5311
    rorid: null
    typeEntity: Person
    typeRole:
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    url: https://scholar.google.com/citations?user=v0Tf_u4AAAAJ&hl=en
  - email: anish.shrestha@dlsu.edu.ph
    fundrefid: null
    gridid: null
    name: Anish M.S. Shrestha
    note: Head, Bioinformatics Lab, Advanced Research Institute for Informatics, Computing
      and Networking, De La Salle University, Manila, Philippines
    orcidid: https://orcid.org/0000-0002-9192-9709
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: https://a-transposable-element.com/
  description: PHIEmbed is a phage-host interaction prediction tool that uses protein
    language models to represent the receptor-binding proteins of phages. It presents
    improvements over using handcrafted (manually feature-engineered) sequence properties
    and eliminates the need to manually extract and select features from phage sequences.
  documentation:
  - note: null
    type:
    - Installation instructions
    - Quick start guide
    - Citation instructions
    - Command-line options
    url: https://github.com/bioinfodlsu/phage-host-prediction
  download:
  - note: null
    type: Source code
    url: https://github.com/bioinfodlsu/phage-host-prediction
    version: null
  editPermission:
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    type: private
  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
    note: Predicts the host genus of a phage given its receptor-binding protein sequences
    operation:
    - term: Prediction and recognition
      uri: http://edamontology.org/operation_2423
    output:
    - data:
        term: Report
        uri: http://edamontology.org/data_2048
      format:
      - term: CSV
        uri: http://edamontology.org/format_3752
  homepage: https://github.com/bioinfodlsu/phage-host-prediction
  homepage_status: 0
  language:
  - Python
  lastUpdate: '2025-01-14T09:13:55.932761Z'
  license: MIT
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/bioinfodlsu/phage-host-prediction
  - note: null
    type:
    - Service
    url: http://phiembed.bioinfodlsu.com/
  maturity: Emerging
  name: PHIEmbed
  operatingSystem:
  - Mac
  - Linux
  - Windows
  otherID: []
  owner: memgonzales
  publication:
  - doi: 10.1371/journal.pone.0289030
    metadata:
      abstract: With the growing interest in using phages to combat antimicrobial
        resistance, computational methods for predicting phage-host interactions have
        been explored to help shortlist candidate phages. Most existing models consider
        entire proteomes and rely on manual feature engineering, which poses difficulty
        in selecting the most informative sequence properties to serve as input to
        the model. In this paper, we framed phage-host interaction prediction as a
        multiclass classification problem that takes as input the embeddings of a
        phage’s receptor-binding proteins, which are known to be the key machinery
        for host recognition, and predicts the host genus. We explored different protein
        language models to automatically encode these protein sequences into dense
        embeddings without the need for additional alignment or structural information.
        We show that the use of embeddings of receptor-binding proteins presents improvements
        over handcrafted genomic and protein sequence features. The highest performance
        was obtained using the transformer-based protein language model ProtT5, resulting
        in a 3% to 4% increase in weighted F1 and recall scores across different prediction
        confidence thresholds, compared to using selected handcrafted sequence features.
      authors:
      - name: Gonzales M.E.M.
      - name: Ureta J.C.
      - name: Shrestha A.M.S.
      citationCount: 2
      date: '2023-07-01T00:00:00Z'
      journal: PLoS ONE
      title: Protein embeddings improve phage-host interaction prediction
    note: null
    pmcid: null
    pmid: '37486915'
    type:
    - Primary
    version: null
  relation: []
  toolType:
  - Command-line tool
  topic:
  - term: Machine learning
    uri: http://edamontology.org/topic_3474
  - term: Sequence analysis
    uri: http://edamontology.org/topic_0080
  - term: Proteins
    uri: http://edamontology.org/topic_0078
  - term: Proteomics
    uri: http://edamontology.org/topic_0121
  - term: Computational biology
    uri: http://edamontology.org/topic_3307
  - term: Bioinformatics
    uri: http://edamontology.org/topic_0091
  - term: Virology
    uri: http://edamontology.org/topic_0781
  validated: 0
  version: []
- accessibility: Open access
  additionDate: '2025-01-09T15:45:12.825558Z'
  biotoolsCURIE: biotools:scp
  biotoolsID: scp
  collectionID: []
  confidence_flag: tool
  cost: Free of charge
  credit: []
  description: Utility functions for manipulating, processing, and analyzing mass
    spectrometry-based single-cell proteomics data. The package is an extension to
    the 'QFeatures' package and relies on 'SingleCellExpirement' to enable single-cell
    proteomics analyses. The package offers the user the functionality to process
    quantitative table (as generated by MaxQuant, Proteome Discoverer, and more) into
    data tables ready for downstream analysis and data visualization.
  documentation: []
  download: []
  editPermission:
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  elixirNode: []
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  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Visualisation
      uri: http://edamontology.org/operation_0337
    output: []
  - cmd: null
    input: []
    note: null
    operation:
    - term: Expression analysis
      uri: http://edamontology.org/operation_2495
    output: []
  homepage: https://uclouvain-cbio.github.io/scp/
  homepage_status: 0
  language:
  - R
  lastUpdate: '2025-01-11T12:06:29.826828Z'
  license: null
  link: []
  maturity: null
  name: scp
  operatingSystem:
  - Mac
  - Linux
  - Windows
  otherID: []
  owner: recetox-specdatri
  publication: []
  relation: []
  toolType:
  - Library
  topic:
  - term: Proteomics experiment
    uri: http://edamontology.org/topic_3520
  - term: Proteomics
    uri: http://edamontology.org/topic_0121
  validated: 0
  version:
  - 1.16.0
- accessibility: null
  additionDate: '2017-01-17T14:50:59Z'
  biotoolsCURIE: biotools:esiprot
  biotoolsID: esiprot
  collectionID:
  - ms-utils
  - Proteomics
  confidence_flag: null
  cost: null
  credit:
  - email: robert.winkler@ira.cinvestav.mx
    fundrefid: null
    gridid: null
    name: Robert Winkler
    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: Charge state determination and molecular weight calculation for low
    resolution electrospray ionization data.
  documentation:
  - note: null
    type:
    - General
    url: http://www.lababi.bioprocess.org/index.php/lababi-software/84-esiprot
  download:
  - note: null
    type: Source code
    url: http://www.bioprocess.org/esiprot/esiprot.zip
    version: null
  - note: null
    type: Source code
    url: http://www.bioprocess.org/esiprot/esiprot.zip
    version: null
  editPermission:
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    type: group
  elixirCommunity: []
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  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Peptide mass fingerprint
        uri: http://edamontology.org/data_0944
      format:
      - term: Mass spectrometry data format
        uri: http://edamontology.org/format_3245
    note: null
    operation:
    - term: Protein molecular weight calculation
      uri: http://edamontology.org/operation_0398
    - term: Protein fragment weight comparison
      uri: http://edamontology.org/operation_2929
    - term: Deisotoping
      uri: http://edamontology.org/operation_3629
    output:
    - data:
        term: Peptide mass fingerprint
        uri: http://edamontology.org/data_0944
      format:
      - term: Mass spectrometry data format
        uri: http://edamontology.org/format_3245
  homepage: https://nube-gran.de/esiprot
  homepage_status: 0
  language:
  - Python
  lastUpdate: '2024-12-13T13:53:01.317118Z'
  license: GPL-3.0
  link:
  - note: null
    type:
    - Mirror
    url: http://www.bioprocess.org/esiprot/esiprot_form.php
  - note: null
    type:
    - Software catalogue
    url: http://ms-utils.org
  maturity: null
  name: ESIprot
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: msutils_import
  publication:
  - doi: 10.1002/rcm.4384
    metadata:
      abstract: Electrospray ionization (ESI) ion trap mass spectrometers with relatively
        low resolution are frequently used for the analysis of natural products and
        peptides. Although ESI spectra of multiply charged protein molecules also
        can be measured on this type of devices, only average spectra are produced
        for the majority of naturally occurring proteins. Evaluating such ESI protein
        spectra would provide valuable information about the native state of investigated
        proteins. However, no suitable and freely available software could be found
        which allows the charge state determination and molecular weight calculation
        of single proteins from average ESI-MS data. Therefore, an algorithm based
        on standard deviation optimization (scatter minimization) was implemented
        for the analysis of protein ESI-MS data. The resulting software ESIprot was
        tested with ESI-MS data of six intact reference proteins between 12.4 and
        66.7kDa. In all cases, the correct charge states could be determined. The
        obtained absolute mass errors were in a range between -0.2 and 1.2Da, the
        relative errors below 30ppm. The possible mass accuracy allows for valid conclusions
        about the actual condition of proteins. Moreover, the ESIprot algorithm demonstrates
        an extraordinary robustness and allows spectral interpretation from as little
        as two peaks, given sufficient quality of the provided m/z data, without the
        necessity for peak intensity data. ESIprot is independent from the raw data
        format and the computer platform, making it a versatile tool for mass spectrometrists.
        The program code was released under the open-source GPLv3 license to support
        future developments of mass spectrometry software. © 2010 John Wiley & Sons,
        Ltd.
      authors:
      - name: Winkler R.
      citationCount: 75
      date: '2010-01-01T00:00:00Z'
      journal: Rapid Communications in Mass Spectrometry
      title: 'ESIprot: A universal tool for charge state determination and molecular
        weight calculation of proteins from electrospray ionization mass spectrometry
        data'
    note: null
    pmcid: null
    pmid: '20049890'
    type: []
    version: null
  relation: []
  toolType:
  - Web application
  - Desktop 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: '2019-11-14T19:27:27Z'
  biotoolsCURIE: biotools:PolySTest
  biotoolsID: PolySTest
  collectionID: []
  confidence_flag: tool
  cost: null
  credit: []
  description: Robust statistical testing of quantitative proteomics data. The tool
    comprises and combines different tests and includes a new method for combined
    statistics of quantitative and missing values.
  documentation: []
  download: []
  editPermission:
    authors: []
    type: public
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Expression data
        uri: http://edamontology.org/data_2603
      format:
      - term: DSV
        uri: http://edamontology.org/format_3751
      - term: CSV
        uri: http://edamontology.org/format_3752
    note: null
    operation:
    - term: Statistical modelling
      uri: http://edamontology.org/operation_3664
    - term: Differential protein expression profiling
      uri: http://edamontology.org/operation_3741
    output:
    - data:
        term: Q-value
        uri: http://edamontology.org/data_3932
      format:
      - term: CSV
        uri: http://edamontology.org/format_3752
    - data:
        term: P-value
        uri: http://edamontology.org/data_1669
      format:
      - term: CSV
        uri: http://edamontology.org/format_3752
    - data:
        term: Heat map
        uri: http://edamontology.org/data_1636
      format:
      - term: SVG
        uri: http://edamontology.org/format_3604
    - data:
        term: Histogram
        uri: http://edamontology.org/data_3905
      format:
      - term: SVG
        uri: http://edamontology.org/format_3604
    - data:
        term: Gene expression profile
        uri: http://edamontology.org/data_0928
      format:
      - term: CSV
        uri: http://edamontology.org/format_3752
  homepage: http://computproteomics.bmb.sdu.dk/Apps/PolySTest
  homepage_status: 0
  language: []
  lastUpdate: '2024-11-25T16:09:23.465736Z'
  license: GPL-2.0
  link:
  - note: null
    type:
    - Repository
    url: https://bitbucket.org/veitveit/polystest
  maturity: null
  name: PolySTest
  operatingSystem:
  - Linux
  - Mac
  otherID: []
  owner: veits@bmb.sdu.dk
  publication:
  - doi: 10.1074/mcp.RA119.001777
    metadata: null
    note: null
    pmcid: PMC8015005
    pmid: '32424025'
    type: []
    version: null
  relation: []
  toolType: []
  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: '2015-09-11T17:01:36Z'
  biotoolsCURIE: biotools:2d-page
  biotoolsID: 2d-page
  collectionID:
  - DRCAT
  - Proteomics
  confidence_flag: null
  cost: null
  credit:
  - email: null
    fundrefid: null
    gridid: null
    name: University of Siena, Italy
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
    - Provider
    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:
    authors:
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    type: group
  elixirCommunity: []
  elixirNode: []
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  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: UniProt accession
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      format: []
    - data:
        term: Spot ID
        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:
  - Linux
  - Windows
  - Mac
  otherID: []
  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:
    - Primary
    version: null
  relation: []
  toolType:
  - Database portal
  topic:
  - term: Proteomics
    uri: http://edamontology.org/topic_0121
  validated: 1
  version: []
- accessibility: null
  additionDate: '2017-02-14T09:34:42Z'
  biotoolsCURIE: biotools:3dlogo
  biotoolsID: 3dlogo
  collectionID:
  - Proteomics
  confidence_flag: null
  cost: null
  credit: []
  description: 3dLOGO is a server for the identification and analysis of conserved
    protein three-dimensional (3D) substructures.
  documentation: []
  download: []
  editPermission:
    authors:
    - proteomics.bio.tools
    type: group
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Sequence alignment analysis (conservation)
      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
  language: []
  lastUpdate: '2024-11-25T14:17:22.357136Z'
  license: null
  link: []
  maturity: null
  name: 3dLOGO
  operatingSystem: []
  otherID: []
  owner: ELIXIR-EE
  publication:
  - doi: 10.1093/nar/gkm228
    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
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    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
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  lastUpdate: '2024-11-25T14:17:15.343704Z'
  license: null
  link:
  - note: null
    type:
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    url: http://www.mybiosoftware.com/anarci-antigen-receptor-numbering-and-receptor-classification.html
  maturity: null
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  otherID: []
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  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: []
- accessibility: null
  additionDate: '2017-08-03T18:36:20Z'
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    fundrefid: null
    gridid: null
    name: Dominik Schaack & Steffen Schmidt
    note: null
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    rorid: null
    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:
  - note: null
    type:
    - General
    url: http://andom.bioapps.biozentrum.uni-wuerzburg.de/Usage_new.html
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  - cmd: null
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      uri: http://edamontology.org/operation_2996
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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'
  license: null
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    type:
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    url: http://www.mybiosoftware.com/andom-assign-structual-domains-protein-sequences.html
  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
  biotoolsID: anm
  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.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: []
  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 modelling
      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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  - Linux
  - Windows
  - Mac
  otherID: []
  owner: mbs_import
  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:
    - Primary contact
    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: []
  editPermission:
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    type: group
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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 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
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: mbs_import
  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:
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    type: Source code
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    version: null
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  function:
  - cmd: null
    input: []
    note: null
    operation:
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      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:
  - Linux
  - Windows
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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:
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- accessibility: null
  additionDate: '2017-08-03T18:35:51Z'
  biotoolsCURIE: biotools:apecs
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    note: null
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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:
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      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
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  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: []
next: ?page=2
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