count: 497
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  biotoolsCURIE: biotools:hictk
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  confidence_flag: null
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  credit: []
  description: Blazing fast toolkit to work with .hic and .cool files
  documentation:
  - note: null
    type:
    - User manual
    url: https://hictk.readthedocs.io/en/latest/index.html
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  - note: null
    type: Downloads page
    url: https://github.com/paulsengroup/hictk/releases
    version: null
  - note: null
    type: Binaries
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  license: MIT
  link:
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    type:
    - Repository
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  - note: null
    type:
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  - term: Sequence analysis
    uri: http://edamontology.org/topic_0080
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  version:
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  credit: []
  description: 'Python bindings for hictk: read and write .cool and .hic files directly
    from Python'
  documentation:
  - note: null
    type:
    - General
    url: https://hictkpy.readthedocs.io/en/latest/
  - note: null
    type:
    - Installation instructions
    url: https://hictkpy.readthedocs.io/en/latest/installation.html
  - note: null
    type:
    - Quick start guide
    url: https://hictkpy.readthedocs.io/en/latest/quickstart.html
  - note: null
    type:
    - API documentation
    url: https://hictkpy.readthedocs.io/en/latest/api/index.html
  download:
  - note: null
    type: Downloads page
    url: https://github.com/paulsengroup/hictkpy/releases
    version: null
  - note: null
    type: Binaries
    url: https://pypi.org/project/hictkpy/
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  license: MIT
  link:
  - note: null
    type:
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    type:
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    type: uses
  toolType:
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    uri: http://edamontology.org/topic_0091
  - term: Sequence analysis
    uri: http://edamontology.org/topic_0080
  validated: 0
  version:
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  - 0.0.2
  - 0.0.3
  - 0.0.4
  - 0.0.5
- accessibility: Open access
  additionDate: '2016-01-22T15:07:25Z'
  biotoolsCURIE: biotools:betaware
  biotoolsID: betaware
  collectionID:
  - Bologna Biocomputing Group
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  confidence_flag: tool
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    gridid: null
    name: ELIXIR-ITA-BOLOGNA
    note: null
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    typeEntity: Institute
    typeRole:
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    url: null
  - email: castrense.savojardo2@unibo.it
    fundrefid: null
    gridid: null
    name: Castrense Savojardo
    note: null
    orcidid: https://orcid.org/0000-0002-7359-0633
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    - Developer
    - Maintainer
    url: http://biocomp.unibo.it/savojard/
  description: A software package for the analysis of TransMembrane Î²-barrel proteins.
  documentation:
  - note: null
    type:
    - Citation instructions
    url: http://bioinformatics.oxfordjournals.org/content/29/4/504.abstract
  - note: null
    type:
    - Command-line options
    url: http://betaware.biocomp.unibo.it/BetAware/default/software
  download:
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    type: Source code
    url: http://betaware.biocomp.unibo.it/BetAware/default/software
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    type: Binaries
    url: http://betaware.biocomp.unibo.it/BetAware/default/software
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  function:
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    input:
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    - data:
        term: Structural profile
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    note: Prediction
    operation:
    - term: Protein secondary structure prediction
      uri: http://edamontology.org/operation_0267
    - term: Transmembrane protein prediction
      uri: http://edamontology.org/operation_0269
    output:
    - data:
        term: Report
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      - term: Textual format
        uri: http://edamontology.org/format_2330
  homepage: http://betaware.biocomp.unibo.it/BetAware/default/index
  homepage_status: 0
  language:
  - Python
  lastUpdate: '2024-03-07T17:59:38.621240Z'
  license: GPL-3.0
  link: []
  maturity: Mature
  name: BetAware
  operatingSystem:
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  - Windows
  - Mac
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  owner: ELIXIR-ITA-BOLOGNA
  publication:
  - doi: 10.1093/bioinformatics/bts728
    metadata:
      abstract: 'The annotation of membrane proteins in proteomes is an important
        problem of Computational Biology, especially after the development of high-throughput
        techniques that allow fast and efficient genome sequencing. Among membrane
        proteins, transmembrane β-barrels (TMBBs) are poorly represented in the database
        of protein structures (PDB) and difficult to identify with experimental approaches.
        They are, however, extremely important, playing key roles in several cell
        functions and bacterial pathogenicity. TMBBs are included in the lipid bilayer
        with a β-barrel structure and are presently found in the outer membranes of
        Gram-negative bacteria, mitochondria and chloroplasts. Recently, we developed
        two top-performing methods based on machine-learning approaches to tackle
        both the detection of TMBBs in sets of proteins and the prediction of their
        topology. Here, we present our BETAWARE program that includes both approaches
        and can run as a standalone program on a linux-based computer to easily address
        in-home massive protein annotation or filtering.Availability and implementation:
        http://www.biocomp.unibo.it/ ∼savojard/betawarecl. © 2013 The Author.'
      authors:
      - name: Savojardo C.
      - name: Fariselli P.
      - name: Casadio R.
      citationCount: 38
      date: '2013-02-15T00:00:00Z'
      journal: Bioinformatics
      title: 'BETAWARE: A machine-learning tool to detect and predict transmembrane
        beta-barrel proteins in prokaryotes'
    note: null
    pmcid: null
    pmid: '23297037'
    type:
    - Primary
    version: null
  - doi: 10.1093/bioinformatics/btr549
    metadata:
      abstract: 'Motivation: Transmembrane β-barrels (TMBBs) are extremely important
        proteins that play key roles in several cell functions. They cross the lipid
        bilayer with β-barrel structures. TMBBs are presently found in the outer membranes
        of Gram-negative bacteria and of mitochondria and chloroplasts. Loop exposure
        outside the bacterial cell membranes makes TMBBs important targets for vaccine
        or drug therapies. In genomes, they are not highly represented and are difficult
        to identify with experimental approaches. Several computational methods have
        been developed to discriminate TMBBs from other types of proteins. However,
        the best performing approaches have a high fraction of false positive predictions.Results:
        In this article, we introduce a new machine learning approach for TMBB detection
        based on N-to-1 Extreme Learning Machines that significantly outperforms previous
        methods achieving a Matthews correlation coefficient of 0.82, a probability
        of correct prediction of 0.92 and a sensitivity of 0.73. © The Author 2011.
        Published by Oxford University Press. All rights reserved.'
      authors:
      - name: Savojardo C.
      - name: Fariselli P.
      - name: Casadio R.
      citationCount: 19
      date: '2011-11-01T00:00:00Z'
      journal: Bioinformatics
      title: Improving the detection of transmembrane β-barrel chains with N-to-1
        extreme learning machines
    note: null
    pmcid: null
    pmid: null
    type:
    - Other
    version: null
  - doi: 10.1186/1748-7188-4-13
    metadata:
      abstract: 'Background: Discriminative models are designed to naturally address
        classification tasks. However, some applications require the inclusion of
        grammar rules, and in these cases generative models, such as Hidden Markov
        Models (HMMs) and Stochastic Grammars, are routinely applied. Results: We
        introduce Grammatical-Restrained Hidden Conditional Random Fields (GRHCRFs)
        as an extension of Hidden Conditional Random Fields (HCRFs). GRHCRFs while
        preserving the discriminative character of HCRFs, can assign labels in agreement
        with the production rules of a defined grammar. The main GRHCRF novelty is
        the possibility of including in HCRFs prior knowledge of the problem by means
        of a defined grammar. Our current implementation allows regular grammar rules.
        We test our GRHCRF on a typical biosequence labeling problem: the prediction
        of the topology of Prokaryotic outer-membrane proteins. Conclusion: We show
        that in a typical biosequence labeling problem the GRHCRF performs better
        than CRF models of the same complexity, indicating that GRHCRFs can be useful
        tools for biosequence analysis applications. Availability: GRHCRF software
        is available under GPLv3 licence at the website. http://www.biocomp.unibo.it/~savojard/biocrf-0.9.tar.gz.
        © 2009 Fariselli et al; licensee BioMed Central Ltd.'
      authors:
      - name: Fariselli P.
      - name: Savojardo C.
      - name: Martelli P.L.
      - name: Casadio R.
      citationCount: 18
      date: '2009-10-22T00:00:00Z'
      journal: Algorithms for Molecular Biology
      title: Grammatical-restrained hidden conditional random fields for bioinformatics
        applications
    note: null
    pmcid: null
    pmid: null
    type:
    - Other
    version: null
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    type: hasNewVersion
  toolType:
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  - Web application
  topic:
  - term: Structure prediction
    uri: http://edamontology.org/topic_0082
  - term: Protein secondary structure
    uri: http://edamontology.org/topic_3542
  validated: 1
  version:
  - '1.0'
- accessibility: Open access
  additionDate: '2024-02-25T14:21:46.268659Z'
  biotoolsCURIE: biotools:omicssuite
  biotoolsID: omicssuite
  collectionID: []
  community: null
  confidence_flag: tool
  cost: Free of charge
  credit: []
  description: OmicsSuite (https://omicssuite.github.io, https://github.com/OmicsSuite/),
    original name BioSciTools, a desktop program developed based on Java 11, aims
    to make new exploration and contribution to bioinformatics, and realize data analysis
    and visualization in the fields of sequence analysis, multi-omics (transcriptomics,
    genomics, protein omics, metabolomics, single cell), microbiology, clinical, etc.
  documentation: []
  download:
  - note: GitHub download page
    type: Downloads page
    url: https://omicssuite.github.io
    version: 1.4.0
  - note: SourceForge download
    type: Binaries
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  editPermission:
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  function:
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    input:
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        term: Alignment
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    - data:
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      format: []
    - data:
        term: Mathematical model
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    - data:
        term: Matrix
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      format: []
    - data:
        term: Sequence
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    - data:
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    note: null
    operation:
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    - term: Visualisation
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    output:
    - data:
        term: Plot
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      format:
      - term: Binary format
        uri: http://edamontology.org/format_2333
      - term: RDF format
        uri: http://edamontology.org/format_2376
      - term: Textual format
        uri: http://edamontology.org/format_2330
  homepage: https://github.com/OmicsSuite/
  homepage_status: 0
  language:
  - Java
  - Python
  - R
  - JavaScript
  lastUpdate: '2024-02-25T14:22:11.738545Z'
  license: GPL-3.0
  link:
  - note: GitHub Organization
    type:
    - Repository
    url: https://github.com/OmicsSuite/
  - note: OmicsSuite Website
    type:
    - Helpdesk
    url: https://omicssuite.github.io
  - note: OmicsSuite Courses
    type:
    - Social media
    url: https://space.bilibili.com/34105515
  - note: OmicsSuite Paper
    type:
    - Helpdesk
    url: https://doi.org/10.1093/hr/uhad195
  maturity: Emerging
  name: OmicsSuite
  operatingSystem:
  - Windows
  otherID: []
  owner: benben.miao
  publication:
  - doi: 10.1093/hr/uhad195
    metadata:
      abstract: 'With the advancements in high-throughput sequencing technologies
        such as Illumina, PacBio, and 10X Genomics platforms, and gas/liquid chromatography-mass
        spectrometry, large volumes of biological data in multiple formats can now
        be obtained through multi-omics analysis. Bioinformatics is constantly evolving
        and seeking breakthroughs to solve multi-omics problems; however, it is challenging
        for most experimental biologists to analyse data using command-line interfaces,
        coding, and scripting. Based on experience with multi-omics, we have developed
        OmicsSuite, a desktop suite that comprehensively integrates statistics and
        multi-omics analysis and visualization. The suite has 175 sub-applications
        in 12 categories, including Sequence, Statistics, Algorithm, Genomics, Transcriptomics,
        Enrichment, Proteomics, Metabolomics, Clinical, Microorganism, Single Cell,
        and Table Operation. We created the user interface with Sequence View, Table
        View, and intelligent components based on JavaFX and the popular Shiny framework.
        The multi-omics analysis functions were developed based on BioJava and 300+
        packages provided by the R CRAN and Bioconductor communities, and it encompasses
        over 3000 adjustable parameter interfaces. OmicsSuite can directly read multi-omics
        raw data in FastA, FastQ, Mutation Annotation Format, mzML, Matrix, and HDF5
        formats, and the programs emphasize data transfer directions and pipeline
        analysis functions. OmicsSuite can produce pre-publication images and tables,
        allowing users to focus on biological aspects. OmicsSuite offers multi-omics
        step-by-step workflows that can be easily applied to horticultural plant breeding
        and molecular mechanism studies in plants. It enables researchers to freely
        explore the molecular information contained in multi-omics big data (Source:
        https://github.com/OmicsSuite/, Website: https://omicssuite.github.io, v1.3.9).'
      authors:
      - name: Miao B.-B.
      - name: Dong W.
      - name: Gu Y.-X.
      - name: Han Z.-F.
      - name: Luo X.
      - name: Ke C.-H.
      - name: You W.-W.
      citationCount: 0
      date: '2023-11-01T00:00:00Z'
      journal: Horticulture Research
      title: 'OmicsSuite: a customized and pipelined suite for analysis and visualization
        of multi-omics big data'
    note: 'Ben-ben Miao, Wei Dong, Yi-xin Gu, Zhao-fang Han, Xuan Luo, Cai-huan Ke,
      Wei-wei You, OmicsSuite: a customized and pipelined suite for analysis and visualization
      of multi-omics big data, Horticulture Research, 2023;, uhad195, https://doi.org/10.1093/hr/uhad195.'
    pmcid: null
    pmid: null
    type:
    - Method
    version: 1.4.0
  relation: []
  toolType:
  - Desktop application
  - Suite
  - Bioinformatics portal
  - Plug-in
  - Web application
  - Workbench
  - Workflow
  topic:
  - term: Biology
    uri: http://edamontology.org/topic_3070
  - term: Omics
    uri: http://edamontology.org/topic_3391
  - term: Mathematics
    uri: http://edamontology.org/topic_3315
  validated: 0
  version:
  - 1.4.0
- accessibility: Open access
  additionDate: '2023-03-05T10:26:21.069202Z'
  biotoolsCURIE: biotools:bioscitools
  biotoolsID: bioscitools
  collectionID: []
  community: null
  confidence_flag: tool
  cost: Free of charge
  credit: []
  description: OmicsSuite (https://omicssuite.github.io, https://github.com/OmicsSuite/),
    original name BioSciTools, a desktop program developed based on Java 11, aims
    to make new exploration and contribution to bioinformatics, and realize data analysis
    and visualization in the fields of sequence analysis, multi-omics (transcriptomics,
    genomics, protein omics, metabolomics, single cell), microbiology, clinical, etc.
  documentation: []
  download:
  - note: GitHub download page
    type: Downloads page
    url: https://omicssuite.github.io
    version: 1.4.0
  - note: SourceForge download
    type: Binaries
    url: https://sourceforge.net/projects/omicssuite-github-io/files/latest/download
    version: 1.4.0
  - note: ALiYun Drive
    type: Binaries
    url: https://www.aliyundrive.com/s/Defuhf7FVGw
    version: 1.4.0
  editPermission:
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  function:
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    input:
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        term: Alignment
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      format: []
    - data:
        term: Mathematical model
        uri: http://edamontology.org/data_0950
      format: []
    - data:
        term: Matrix
        uri: http://edamontology.org/data_2082
      format: []
    - data:
        term: Sequence
        uri: http://edamontology.org/data_2044
      format: []
    - data:
        term: Text data
        uri: http://edamontology.org/data_2526
      format: []
    note: null
    operation:
    - term: Analysis
      uri: http://edamontology.org/operation_2945
    - term: Alignment
      uri: http://edamontology.org/operation_2928
    - term: Visualisation
      uri: http://edamontology.org/operation_0337
    output:
    - data:
        term: Plot
        uri: http://edamontology.org/data_2884
      format:
      - term: Binary format
        uri: http://edamontology.org/format_2333
      - term: RDF format
        uri: http://edamontology.org/format_2376
      - term: Textual format
        uri: http://edamontology.org/format_2330
  homepage: https://github.com/OmicsSuite/
  homepage_status: 0
  language:
  - Java
  - Python
  - R
  - JavaScript
  lastUpdate: '2024-02-25T14:20:44.230314Z'
  license: GPL-3.0
  link:
  - note: GitHub Organization
    type:
    - Repository
    url: https://github.com/OmicsSuite/
  - note: OmicsSuite Website
    type:
    - Helpdesk
    url: https://omicssuite.github.io
  - note: OmicsSuite Courses
    type:
    - Social media
    url: https://space.bilibili.com/34105515
  - note: OmicsSuite Paper
    type:
    - Helpdesk
    url: https://doi.org/10.1093/hr/uhad195
  maturity: Emerging
  name: OmicsSuite
  operatingSystem:
  - Windows
  otherID: []
  owner: benben.miao
  publication:
  - doi: 10.1093/hr/uhad195
    metadata:
      abstract: 'With the advancements in high-throughput sequencing technologies
        such as Illumina, PacBio, and 10X Genomics platforms, and gas/liquid chromatography-mass
        spectrometry, large volumes of biological data in multiple formats can now
        be obtained through multi-omics analysis. Bioinformatics is constantly evolving
        and seeking breakthroughs to solve multi-omics problems; however, it is challenging
        for most experimental biologists to analyse data using command-line interfaces,
        coding, and scripting. Based on experience with multi-omics, we have developed
        OmicsSuite, a desktop suite that comprehensively integrates statistics and
        multi-omics analysis and visualization. The suite has 175 sub-applications
        in 12 categories, including Sequence, Statistics, Algorithm, Genomics, Transcriptomics,
        Enrichment, Proteomics, Metabolomics, Clinical, Microorganism, Single Cell,
        and Table Operation. We created the user interface with Sequence View, Table
        View, and intelligent components based on JavaFX and the popular Shiny framework.
        The multi-omics analysis functions were developed based on BioJava and 300+
        packages provided by the R CRAN and Bioconductor communities, and it encompasses
        over 3000 adjustable parameter interfaces. OmicsSuite can directly read multi-omics
        raw data in FastA, FastQ, Mutation Annotation Format, mzML, Matrix, and HDF5
        formats, and the programs emphasize data transfer directions and pipeline
        analysis functions. OmicsSuite can produce pre-publication images and tables,
        allowing users to focus on biological aspects. OmicsSuite offers multi-omics
        step-by-step workflows that can be easily applied to horticultural plant breeding
        and molecular mechanism studies in plants. It enables researchers to freely
        explore the molecular information contained in multi-omics big data (Source:
        https://github.com/OmicsSuite/, Website: https://omicssuite.github.io, v1.3.9).'
      authors:
      - name: Miao B.-B.
      - name: Dong W.
      - name: Gu Y.-X.
      - name: Han Z.-F.
      - name: Luo X.
      - name: Ke C.-H.
      - name: You W.-W.
      citationCount: 0
      date: '2023-11-01T00:00:00Z'
      journal: Horticulture Research
      title: 'OmicsSuite: a customized and pipelined suite for analysis and visualization
        of multi-omics big data'
    note: 'Ben-ben Miao, Wei Dong, Yi-xin Gu, Zhao-fang Han, Xuan Luo, Cai-huan Ke,
      Wei-wei You, OmicsSuite: a customized and pipelined suite for analysis and visualization
      of multi-omics big data, Horticulture Research, 2023;, uhad195, https://doi.org/10.1093/hr/uhad195.'
    pmcid: null
    pmid: null
    type:
    - Method
    version: 1.4.0
  relation: []
  toolType:
  - Desktop application
  - Suite
  - Bioinformatics portal
  - Plug-in
  - Web application
  - Workbench
  - Workflow
  topic:
  - term: Biology
    uri: http://edamontology.org/topic_3070
  - term: Omics
    uri: http://edamontology.org/topic_3391
  - term: Mathematics
    uri: http://edamontology.org/topic_3315
  validated: 0
  version:
  - 1.4.0
- accessibility: null
  additionDate: '2016-10-19T14:56:00Z'
  biotoolsCURIE: biotools:kaiju
  biotoolsID: kaiju
  collectionID: []
  community: null
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: null
    fundrefid: null
    gridid: null
    name: Peter Menzel
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Anders Krogh
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Kim Lee Ng
    note: null
    orcidid: null
    rorid: null
    typeEntity: null
    typeRole:
    - Contributor
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Section for Bioinformatics, Department of Biology, University of Copenhagen
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
    - Provider
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Elixir
    note: null
    orcidid: null
    rorid: null
    typeEntity: Consortium
    typeRole: []
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: binf.ku.dk
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
    - Provider
    url: null
  - email: pmenzel@gmail.com
    fundrefid: null
    gridid: null
    name: Peter Menzel
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  - email: krogh@binf.ku.dk
    fundrefid: null
    gridid: null
    name: Anders Krogh
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  description: Program for the taxonomic assignment of high-throughput sequencing
    reads, e.g., Illumina or Roche/454, from whole-genome sequencing of metagenomic
    DNA. Reads are directly assigned to taxa using the NCBI taxonomy and a reference
    database of protein sequences from Bacteria, Archaea, Fungi, microbial eukaryotes
    and viruses.
  documentation:
  - note: null
    type:
    - General
    url: http://kaiju.binf.ku.dk
  download:
  - note: null
    type: Source code
    url: https://github.com/bioinformatics-centre/kaiju
    version: null
  - note: null
    type: Binaries
    url: https://github.com/bioinformatics-centre/kaiju/releases/download/v1.4.4/kaiju-1.4.4-linux-x86_64.tar.gz
    version: null
  editPermission:
    authors:
    - wenzel@sund.ku.dk
    type: group
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Nucleic acid sequence (raw)
        uri: http://edamontology.org/data_2975
      format:
      - term: FASTQ
        uri: http://edamontology.org/format_1930
      - term: FASTA
        uri: http://edamontology.org/format_1929
    note: Raw high-throughput sequencing reads (e.g. Illumina, Roche 454)
    operation:
    - term: Taxonomic classification
      uri: http://edamontology.org/operation_3460
    output:
    - data:
        term: Taxonomy
        uri: http://edamontology.org/data_3028
      format:
      - term: TSV
        uri: http://edamontology.org/format_3475
  homepage: http://kaiju.binf.ku.dk
  homepage_status: 0
  language:
  - C++
  lastUpdate: '2024-02-21T13:53:35.628352Z'
  license: GPL-3.0
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/bioinformatics-centre/kaiju
  maturity: Mature
  name: Kaiju
  operatingSystem:
  - Linux
  - Mac
  otherID: []
  owner: ptr@binf.ku.dk
  publication:
  - doi: 10.1038/ncomms11257
    metadata:
      abstract: Metagenomics emerged as an important field of research not only in
        microbial ecology but also for human health and disease, and metagenomic studies
        are performed on increasingly larger scales. While recent taxonomic classification
        programs achieve high speed by comparing genomic k-mers, they often lack sensitivity
        for overcoming evolutionary divergence, so that large fractions of the metagenomic
        reads remain unclassified. Here we present the novel metagenome classifier
        Kaiju, which finds maximum (in-)exact matches on the protein-level using the
        Burrows-Wheeler transform. We show in a genome exclusion benchmark that Kaiju
        classifies reads with higher sensitivity and similar precision compared with
        current k-mer-based classifiers, especially in genera that are underrepresented
        in reference databases. We also demonstrate that Kaiju classifies up to 10
        times more reads in real metagenomes. Kaiju can process millions of reads
        per minute and can run on a standard PC. Source code and web server are available
        at http://kaiju.binf.ku.dk.
      authors:
      - name: Menzel P.
      - name: Ng K.L.
      - name: Krogh A.
      citationCount: 491
      date: '2016-04-13T00:00:00Z'
      journal: Nature Communications
      title: Fast and sensitive taxonomic classification for metagenomics with Kaiju
    note: null
    pmcid: null
    pmid: null
    type:
    - Primary
    version: null
  relation: []
  toolType:
  - Command-line tool
  - Web application
  topic:
  - term: Metagenomics
    uri: http://edamontology.org/topic_3174
  validated: 1
  version:
  - 1.4.4
- accessibility: null
  additionDate: '2016-04-12T11:22:47Z'
  biotoolsCURIE: biotools:comet
  biotoolsID: comet
  collectionID:
  - Proteomics
  community: null
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: null
    fundrefid: null
    gridid: null
    name: lumc.nl
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
    - Provider
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Comet's Google group
    note: null
    orcidid: null
    rorid: null
    typeEntity: null
    typeRole:
    - Support
    url: https://groups.google.com/forum/#!forum/comet-ms
  - email: null
    fundrefid: null
    gridid: null
    name: Comet's Google group
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: https://groups.google.com/forum/#!forum/comet-ms
  description: Comet is an open source tandem mass spectrometry (MS/MS) sequence database
    search tool.
  documentation:
  - note: null
    type:
    - Terms of use
    url: http://comet-ms.sourceforge.net/release/
  - note: null
    type:
    - Citation instructions
    - General
    url: http://comet-ms.sourceforge.net/
  download:
  - note: null
    type: Source code
    url: https://sourceforge.net/projects/comet-ms/files/
    version: null
  - note: null
    type: Binaries
    url: https://sourceforge.net/projects/comet-ms/files/
    version: null
  editPermission:
    authors:
    - n.m.palmblad@lumc.nl
    - proteomics.bio.tools
    type: group
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Mass spectrometry spectra
        uri: http://edamontology.org/data_0943
      format:
      - term: mzML
        uri: http://edamontology.org/format_3244
      - term: mzXML
        uri: http://edamontology.org/format_3654
      - term: MGF
        uri: http://edamontology.org/format_3651
    - data:
        term: Protein sequence
        uri: http://edamontology.org/data_2976
      format:
      - term: FASTA
        uri: http://edamontology.org/format_1929
    note: null
    operation:
    - term: Peptide database search
      uri: http://edamontology.org/operation_3646
    output:
    - data:
        term: Peptide identification
        uri: http://edamontology.org/data_0945
      format:
      - term: pepXML
        uri: http://edamontology.org/format_3655
      - term: mzIdentML
        uri: http://edamontology.org/format_3247
      - term: TSV
        uri: http://edamontology.org/format_3475
  homepage: http://comet-ms.sourceforge.net/
  homepage_status: 0
  language:
  - C++
  lastUpdate: '2024-02-16T12:32:41.278020Z'
  license: Apache-2.0
  link:
  - note: null
    type:
    - Repository
    url: https://sourceforge.net/projects/comet-ms/files/
  maturity: Mature
  name: Comet
  operatingSystem:
  - Linux
  - Mac
  - Windows
  otherID: []
  owner: admin
  publication:
  - doi: 10.1002/pmic.201200439
    metadata:
      abstract: Proteomics research routinely involves identifying peptides and proteins
        via MS/MS sequence database search. Thus the database search engine is an
        integral tool in many proteomics research groups. Here, we introduce the Comet
        search engine to the existing landscape of commercial and open-source database
        search tools. Comet is open source, freely available, and based on one of
        the original sequence database search tools that has been widely used for
        many years. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
      authors:
      - name: Eng J.K.
      - name: Jahan T.A.
      - name: Hoopmann M.R.
      citationCount: 891
      date: '2013-01-01T00:00:00Z'
      journal: Proteomics
      title: 'Comet: An open-source MS/MS sequence database search tool'
    note: null
    pmcid: null
    pmid: null
    type:
    - Primary
    version: null
  - doi: 10.1007/s13361-015-1179-x
    metadata:
      abstract: The Comet database search software was initially released as an open
        source project in late 2012. Prior to that, Comet existed as the University
        of Washington's academic version of the SEQUEST database search tool. Despite
        its availability and widespread use over the years, some details about its
        implementation have not been previously disseminated or are not well understood.
        We address a few of these details in depth and highlight new features available
        in the latest release. Comet is freely available for download at http://comet-ms.sourceforge.net
        or it can be accessed as a component of a number of larger software projects
        into which it has been incorporated. (Figure Presented).
      authors:
      - name: Eng J.K.
      - name: Hoopmann M.R.
      - name: Jahan T.A.
      - name: Egertson J.D.
      - name: Noble W.S.
      - name: MacCoss M.J.
      citationCount: 131
      date: '2015-11-01T00:00:00Z'
      journal: Journal of the American Society for Mass Spectrometry
      title: A Deeper Look into Comet - Implementation and Features
    note: null
    pmcid: null
    pmid: null
    type:
    - Other
    version: null
  relation: []
  toolType:
  - Command-line tool
  - Desktop application
  topic:
  - term: Proteomics
    uri: http://edamontology.org/topic_0121
  - term: Protein modifications
    uri: http://edamontology.org/topic_0601
  validated: 1
  version:
  - 2016.01.2
  - 2023.01.2
- accessibility: null
  additionDate: '2016-04-15T11:52:42Z'
  biotoolsCURIE: biotools:comparems2
  biotoolsID: comparems2
  collectionID:
  - ms-utils
  - Proteomics
  community: null
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: null
    fundrefid: null
    gridid: null
    name: lumc.nl
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
    - Support
    url: https://www.lumc.nl
  - email: magnus.palmblad@gmail.com
    fundrefid: null
    gridid: null
    name: Magnus Palmblad
    note: null
    orcidid: http://orcid.org/0000-0002-5865-8994
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    - Primary contact
    - Documentor
    url: https://github.com/magnuspalmblad
  - email: null
    fundrefid: null
    gridid: null
    name: Rob Marissen
    note: null
    orcidid: https://orcid.org/0000-0002-1220-9173
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: https://github.com/524D
  description: compareMS2 is a tool for comparing sets of (tandem) mass spectra for
    clustering samples, molecular phylogenetics, identification of biological species
    or tissues, and quality control. compareMS2 currently consumes Mascot Generic
    Format, or MGF, and produces output in a variety of common image and distance
    matrix formats.
  documentation:
  - note: null
    type:
    - General
    - Command-line options
    url: http://www.ms-utils.org/compareMS2.html
  - note: null
    type:
    - General
    - User manual
    - Command-line options
    - Installation instructions
    url: https://github.com/524D/compareMS2
  download:
  - note: null
    type: Source code
    url: http://www.ms-utils.org/compareMS2.c
    version: '1.0'
  - note: null
    type: Binaries
    url: http://www.ms-utils.org/compareMS2.html
    version: '1.0'
  - note: null
    type: Source code
    url: http://www.ms-utils.org/compareMS2.c
    version: '1.0'
  - note: null
    type: Source code
    url: https://github.com/524D/compareMS2/tree/main/src
    version: '2.0'
  - note: null
    type: Binaries
    url: https://github.com/524D/compareMS2/tree/main
    version: '2.0'
  editPermission:
    authors:
    - proteomics.bio.tools
    type: group
  elixirCommunity:
  - Proteomics
  elixirNode:
  - Netherlands
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Mass spectrometry data
        uri: http://edamontology.org/data_2536
      format:
      - term: MGF
        uri: http://edamontology.org/format_3651
    note: null
    operation:
    - term: Comparison
      uri: http://edamontology.org/operation_2424
    - term: Phylogenetic tree visualisation
      uri: http://edamontology.org/operation_0567
    output:
    - data:
        term: Species tree
        uri: http://edamontology.org/data_3272
      format:
      - term: PNG
        uri: http://edamontology.org/format_3603
      - term: SVG
        uri: http://edamontology.org/format_3604
    - data:
        term: Distance matrix
        uri: http://edamontology.org/data_2855
      format:
      - term: mega
        uri: http://edamontology.org/format_1991
      - term: Nexus format
        uri: http://edamontology.org/format_1912
      - term: newick
        uri: http://edamontology.org/format_1910
  homepage: https://github.com/524D/compareMS2
  homepage_status: 0
  language:
  - C
  - JavaScript
  lastUpdate: '2024-02-13T15:35:10.776331Z'
  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
  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: 28
      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: 2
      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:
    - Other
    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: Open access
  additionDate: '2019-02-13T17:01:40Z'
  biotoolsCURIE: biotools:Jalview
  biotoolsID: Jalview
  collectionID:
  - ELIXIR-UK
  community: null
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: null
    fundrefid: null
    gridid: null
    name: Jim Procter
    note: null
    orcidid: https://orcid.org/0000-0002-7865-7382
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: http://www.lifesci.dundee.ac.uk/people/jim-procter
  - email: null
    fundrefid: null
    gridid: null
    name: Geoff Barton
    note: null
    orcidid: https://orcid.org/0000-0002-9014-5355
    rorid: null
    typeEntity: null
    typeRole: []
    url: https://www.lifesci.dundee.ac.uk/people/geoff-barton
  description: Jalview is a free program for multiple sequence alignment editing,
    visualisation and analysis. Use it to view and edit sequence alignments, analyse
    them with phylogenetic trees and principal components analysis (PCA) plots and
    explore molecular structures and annotation.
  documentation:
  - note: null
    type:
    - Citation instructions
    url: https://www.jalview.org/about/citation
  - note: Hands-on exercises, Training courses and Training videos
    type:
    - Training material
    url: https://www.jalview.org/training/
  - note: null
    type:
    - FAQ
    url: https://www.jalview.org/help/faq
  - note: null
    type:
    - User manual
    url: https://www.jalview.org/help/documentation/
  download:
  - note: null
    type: Downloads page
    url: https://www.jalview.org/download
    version: null
  - note: null
    type: Source code
    url: https://www.jalview.org/download/source/
    version: null
  - note: Binaries for all platforms
    type: Binaries
    url: https://www.jalview.org/download/?os=all
    version: null
  - note: null
    type: Icon
    url: https://www.jalview.org/favicon.svg
    version: null
  - note: Executable JAR file
    type: Binaries
    url: https://www.jalview.org/download/other/jar/
    version: null
  editPermission:
    authors:
    - ben_s
    - jimprocter
    type: group
  elixirCommunity: []
  elixirNode:
  - UK
  elixirPlatform:
  - Tools
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Sequence alignment
        uri: http://edamontology.org/data_0863
      format:
      - term: GFF3-seq
        uri: http://edamontology.org/format_1939
      - term: ClustalW format
        uri: http://edamontology.org/format_1982
      - term: Stockholm format
        uri: http://edamontology.org/format_1961
      - term: FASTA-aln
        uri: http://edamontology.org/format_1984
      - term: GFF2-seq
        uri: http://edamontology.org/format_1938
      - term: FASTA
        uri: http://edamontology.org/format_1929
      - term: nbrf/pir
        uri: http://edamontology.org/format_1948
      - term: BioJSON (Jalview)
        uri: http://edamontology.org/format_3774
      - term: PHYLIP format
        uri: http://edamontology.org/format_1997
      - term: BLC
        uri: http://edamontology.org/format_3313
      - term: RNAML
        uri: http://edamontology.org/format_3311
      - term: GCG MSF
        uri: http://edamontology.org/format_1947
      - term: Pileup
        uri: http://edamontology.org/format_3015
      - term: mmCIF
        uri: http://edamontology.org/format_1477
      - term: VCF
        uri: http://edamontology.org/format_3016
      - term: Format
        uri: http://edamontology.org/format_1915
    - data:
        term: Structure alignment
        uri: http://edamontology.org/data_0886
      format:
      - term: PDB
        uri: http://edamontology.org/format_1476
    note: 'Other Input formats:

      AMSA (.amsa);

      JnetFile (.concise, .jnet);

      PFAM (.pfam);

      Substitution matrix (.matrix);

      Jalview Project File (.jvp);

      Jalview Feature File (.features, .jvfeatures);

      Jalview Annotations File (.annotations, .jvannotations);

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

      ...

      Other Output formats:

      PFAM (.pfam);

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

      Jalview Project File (.jvp);'
    operation:
    - term: Sequence visualisation
      uri: http://edamontology.org/operation_0564
    - term: Phylogenetic tree analysis
      uri: http://edamontology.org/operation_0324
    - term: Sequence alignment editing
      uri: http://edamontology.org/operation_3081
    output:
    - data:
        term: Sequence alignment
        uri: http://edamontology.org/data_0863
      format:
      - term: nbrf/pir
        uri: http://edamontology.org/format_1948
      - term: JSON
        uri: http://edamontology.org/format_3464
      - term: Stockholm format
        uri: http://edamontology.org/format_1961
      - term: FASTA
        uri: http://edamontology.org/format_1929
      - term: PHYLIP format
        uri: http://edamontology.org/format_1997
      - term: BLC
        uri: http://edamontology.org/format_3313
      - term: BioJSON (Jalview)
        uri: http://edamontology.org/format_3774
      - term: GCG MSF
        uri: http://edamontology.org/format_1947
      - term: Pileup
        uri: http://edamontology.org/format_3015
      - term: ClustalW format
        uri: http://edamontology.org/format_1982
    - data:
        term: Plot
        uri: http://edamontology.org/data_2884
      format:
      - term: PNG
        uri: http://edamontology.org/format_3603
      - term: HTML
        uri: http://edamontology.org/format_2331
      - term: EPS
        uri: http://edamontology.org/format_3466
      - term: SVG
        uri: http://edamontology.org/format_3604
      - term: Format
        uri: http://edamontology.org/format_1915
  homepage: https://www.jalview.org/
  homepage_status: 0
  language: []
  lastUpdate: '2023-12-01T12:00:21.286261Z'
  license: GPL-3.0
  link:
  - note: null
    type:
    - Discussion forum
    url: https://discourse.jalview.org/
  - note: null
    type:
    - Issue tracker
    url: https://issues.jalview.org/
  - note: Latest development version
    type:
    - Other
    url: https://www.jalview.org/development/jalview_develop/
  - note: null
    type:
    - Repository
    url: https://source.jalview.org/crucible/browse/jalview
  - note: Twitter feed
    type:
    - Social media
    url: https://twitter.com/Jalview
  - note: YouTube training videos
    type:
    - Social media
    url: https://www.youtube.com/channel/UCIjpnvZB770yz7ftbrJ0tfw
  maturity: Mature
  name: Jalview
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: ben_s
  publication:
  - doi: 10.1093/bioinformatics/btp033
    metadata:
      abstract: 'Summary: Jalview Version 2 is a system for interactive WYSIWYG editing,
        analysis and annotation of multiple sequence alignments. Core features include
        keyboard and mouse-based editing, multiple views and alignment overviews,
        and linked structure display with Jmol. Jalview 2 is available in two forms:
        a lightweight Java applet for use in web applications, and a powerful desktop
        application that employs web services for sequence alignment, secondary structure
        prediction and the retrieval of alignments, sequences, annotation and structures
        from public databases and any DAS 1.53 compliant sequence or annotation server.
        © 2009 The Author(s).'
      authors:
      - name: Waterhouse A.M.
      - name: Procter J.B.
      - name: Martin D.M.A.
      - name: Clamp M.
      - name: Barton G.J.
      citationCount: 6231
      date: '2009-05-07T00:00:00Z'
      journal: Bioinformatics
      title: Jalview Version 2-A multiple sequence alignment editor and analysis workbench
    note: null
    pmcid: null
    pmid: null
    type: []
    version: null
  relation:
  - biotoolsID: jabaws
    type: uses
  - biotoolsID: chimera
    type: uses
  - biotoolsID: chimerax
    type: uses
  - biotoolsID: pymol
    type: uses
  - biotoolsID: bioconda
    type: includedIn
  - biotoolsID: 3d-beacons
    type: uses
  - biotoolsID: uniprot
    type: uses
  - biotoolsID: pfam
    type: uses
  - biotoolsID: ensembl
    type: uses
  - biotoolsID: pdb
    type: uses
  - biotoolsID: rfam
    type: uses
  toolType:
  - Desktop application
  - Command-line tool
  topic:
  - term: Sequence analysis
    uri: http://edamontology.org/topic_0080
  - term: Data visualisation
    uri: http://edamontology.org/topic_0092
  validated: 1
  version:
  - 2.11.3.2
- accessibility: Open access
  additionDate: '2016-07-12T10:54:05Z'
  biotoolsCURIE: biotools:pia
  biotoolsID: pia
  collectionID:
  - KNIME
  - de.NBI
  - Proteomics
  - BioInfra.Prot
  - CUBiMed.RUB
  community: null
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: julian.uszkoreit@rub.de
    fundrefid: null
    gridid: null
    name: Julian Uszkoreit
    note: null
    orcidid: http://orcid.org/0000-0001-7522-4007
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    - Developer
    - Maintainer
    url: null
  - email: cubimed@rub.de
    fundrefid: null
    gridid: null
    name: CUBiMed.RUB
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
    - Provider
    url: null
  description: The main focus lays on the integrated inference algorithms, concluding
    the proteins from a set of identified spectra. But it also allows you to integrate
    results of various search engines, inspect your peptide spectrum matches, calculate
    FDR values across different results and visualize the correspondence between PSMs,
    peptides and proteins.
  documentation:
  - note: null
    type:
    - General
    url: https://github.com/mpc-bioinformatics/pia/wiki
  download:
  - note: null
    type: Source code
    url: https://github.com/mpc-bioinformatics/pia
    version: null
  - note: null
    type: Software package
    url: http://bioconda.github.io/recipes/pia/README.html
    version: null
  - note: null
    type: Binaries
    url: https://github.com/mpc-bioinformatics/pia/releases
    version: null
  - note: null
    type: Container file
    url: https://hub.docker.com/r/julianusz/pia
    version: null
  editPermission:
    authors: []
    type: private
  elixirCommunity:
  - Proteomics
  elixirNode:
  - Germany
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Mass spectrometry spectra
        uri: http://edamontology.org/data_0943
      format:
      - term: Mascot .dat file
        uri: http://edamontology.org/format_3713
      - term: mzIdentML
        uri: http://edamontology.org/format_3247
      - term: TSV
        uri: http://edamontology.org/format_3475
      - term: PRIDE XML
        uri: http://edamontology.org/format_3684
      - term: X!Tandem XML
        uri: http://edamontology.org/format_3711
      - term: MSF
        uri: http://edamontology.org/format_3702
      - term: mzTab
        uri: http://edamontology.org/format_3681
    note: PIA allows you to inspect the results of common proteomics spectrum identification
      search engines, combine them seamlessly and conduct statistical analyses. The
      main focus of PIA lays on the integrated inference algorithms, i.e. concluding
      the proteins from a set of identified spectra. But it also allows you to inspect
      your peptide spectrum matches, calculate FDR values across different search
      engine results and visualize the correspondence between PSMs, peptides and proteins.
      Search engine results in several formats peptide spectrum matches (PSMs) and
      peptides Inferred Proteins
    operation:
    - term: Analysis
      uri: http://edamontology.org/operation_2945
    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: '2023-11-29T13:17:14.978741Z'
  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: 53
      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: 25
      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:
  - '1.4'
next: ?page=2
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