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    - data:
        term: Heat map
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    - data:
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    - data:
        term: Gene expression profile
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  name: PolySTest
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    note: null
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    type:
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    version: null
  relation: []
  toolType:
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  topic:
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  - term: Proteomics experiment
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  - term: Statistics and probability
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- accessibility: Open access
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    orcidid: null
    rorid: null
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  description: Feature-based variance-sensitive clustering of omics data. Optimizes
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    operation:
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    - term: Statistical modelling
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    - term: Principal component analysis
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    output:
    - data:
        term: Clustered expression profiles
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      format:
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    - data:
        term: Q-value
        uri: http://edamontology.org/data_3932
      format:
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        uri: http://edamontology.org/format_3752
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  language:
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  link:
  - note: null
    type:
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  maturity: null
  name: VSClust
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  owner: veits@bmb.sdu.dk
  publication:
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    metadata:
      abstract: ''
      authors: []
      citationCount: 27
      date: '2018-09-01T00:00:00Z'
      journal: Bioinformatics
      title: 'VSClust: Feature-based variance-sensitive clustering of omics data'
    note: null
    pmcid: null
    pmid: '29635359'
    type:
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    version: null
  relation: []
  toolType:
  - Command-line tool
  - Web service
  topic:
  - term: Genomics
    uri: http://edamontology.org/topic_0622
  - term: Proteomics
    uri: http://edamontology.org/topic_0121
  - term: Omics
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  - term: Metabolomics
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  - term: Statistics and probability
    uri: http://edamontology.org/topic_2269
  - term: Data mining
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  validated: 1
  version: []
- accessibility: Open access
  additionDate: '2025-11-05T14:50:14.996722Z'
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  description: The Spectra package defines an efficient infrastructure for storing
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  - note: null
    type:
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    url: https://rformassspectrometry.github.io/Spectra/
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  link:
  - note: null
    type:
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  toolType:
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- accessibility: Open access
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  description: A command-line tool for differential expression analysis in quantitative
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    note: null
    operation:
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    note: null
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  - cmd: null
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    note: null
    operation:
    - term: Expression data visualisation
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    output:
    - data:
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      format:
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      - term: PDF
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  homepage_status: 0
  language:
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  license: MIT
  link:
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    type:
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  - note: null
    type:
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  maturity: Emerging
  name: prolfquapp
  operatingSystem:
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  otherID: []
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  publication:
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    metadata:
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      authors: []
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    pmid: null
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  validated: 0
  version:
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- accessibility: Open access
  additionDate: '2024-01-02T16:37:22.478902Z'
  biotoolsCURIE: biotools:ipapy2
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  confidence_flag: tool
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  description: Bayesian-based method for the annotation of LC-MS/MS untargeted metabolomics
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    type:
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    version: null
  - note: null
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    note: null
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  owner: Pub2Tools
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      authors: []
      citationCount: 4
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    version: null
  relation: []
  toolType:
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  topic:
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  - term: Workflows
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  - term: Analytical chemistry
    uri: http://edamontology.org/topic_3370
  validated: 0
  version: []
- accessibility: Open access
  additionDate: '2021-11-06T22:47:59.994136Z'
  biotoolsCURIE: biotools:matrixqcvis
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  confidence_flag: tool
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    orcidid: null
    rorid: null
    typeEntity: null
    typeRole: []
    url: null
  - email: null
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    typeEntity: null
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    url: null
  description: shiny-based interactive data quality exploration for omics data.
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    - data:
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    - Repository
    url: https://github.com/tnaake/MsQuality/
  maturity: null
  name: MsQuality
  operatingSystem:
  - Windows
  - Mac
  - Linux
  otherID: []
  owner: Pub2Tools
  publication:
  - doi: 10.1093/bioinformatics/btad618
    metadata:
      abstract: ''
      authors: []
      citationCount: 4
      date: '2023-10-01T00:00:00Z'
      journal: Bioinformatics
      title: 'MsQuality: an interoperable open-source package for the calculation
        of standardized quality metrics of mass spectrometry data'
    note: null
    pmcid: PMC10580266
    pmid: '37812234'
    type:
    - Primary
    version: null
  relation: []
  toolType:
  - Library
  topic:
  - term: Proteomics experiment
    uri: http://edamontology.org/topic_3520
  - term: Metabolomics
    uri: http://edamontology.org/topic_3172
  - term: Proteomics
    uri: http://edamontology.org/topic_0121
  - term: Workflows
    uri: http://edamontology.org/topic_0769
  validated: 0
  version: []
- accessibility: Open access
  additionDate: '2021-01-18T09:01:58Z'
  biotoolsCURIE: biotools:retip
  biotoolsID: retip
  collectionID: []
  confidence_flag: tool
  cost: Free of charge
  credit: []
  description: 'Retention Time Prediction for Compound Annotation in Untargeted Metabolomics.


    Retip is an R package for predicting Retention Time (RT) for small molecules in
    a high pressure liquid chromatography (HPLC) Mass Spectrometry analysis.


    Retip - Retention Time prediction for Metabolomics.


    Retip: Retention Time Prediction for Compound Annotation in Untargeted Metabolomics
    Paolo Bonini, Tobias Kind, Hiroshi Tsugawa, Dinesh Kumar Barupal, and Oliver Fiehn
    Analytical Chemistry 2020 92 (11), 7515-7522 DOI: 10.1021/acs.analchem.9b05765.'
  documentation:
  - note: null
    type:
    - General
    url: https://www.retip.app/
  download: []
  editPermission:
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    type: group
  elixirCommunity:
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  function:
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    input:
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      format:
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        uri: http://edamontology.org/format_1196
    - data:
        term: Mathematical model
        uri: http://edamontology.org/data_0950
      format:
      - term: JSON
        uri: http://edamontology.org/format_3464
    note: null
    operation:
    - term: Retention time prediction
      uri: http://edamontology.org/operation_3633
    output:
    - data:
        term: Molecular property
        uri: http://edamontology.org/data_2087
      format:
      - term: DSV
        uri: http://edamontology.org/format_3751
  - cmd: null
    input:
    - data:
        term: Experimental measurement
        uri: http://edamontology.org/data_3108
      format:
      - term: DSV
        uri: http://edamontology.org/format_3751
    - data:
        term: Molecule identifier
        uri: http://edamontology.org/data_0982
      format:
      - term: SMILES
        uri: http://edamontology.org/format_1196
    note: null
    operation:
    - term: Modelling and simulation
      uri: http://edamontology.org/operation_2426
    output:
    - data:
        term: Mathematical model
        uri: http://edamontology.org/data_0950
      format:
      - term: JSON
        uri: http://edamontology.org/format_3464
  homepage: https://www.retip.app
  homepage_status: 0
  language:
  - R
  lastUpdate: '2025-11-04T10:46:26.117809Z'
  license: CC-BY-4.0
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/oloBion/Retip
  - note: null
    type:
    - Repository
    url: https://github.com/oloBion/pyRetip/tree/master
  maturity: null
  name: Retip
  operatingSystem: []
  otherID: []
  owner: zsmag19
  publication:
  - doi: 10.1021/ACS.ANALCHEM.9B05765
    metadata:
      abstract: ''
      authors: []
      citationCount: 177
      date: '2020-06-02T00:00:00Z'
      journal: Analytical Chemistry
      title: 'Retip: Retention Time Prediction for Compound Annotation in Untargeted
        Metabolomics'
    note: null
    pmcid: null
    pmid: '32390414'
    type: []
    version: null
  relation: []
  toolType:
  - Library
  topic:
  - term: Metabolomics
    uri: http://edamontology.org/topic_3172
  - term: Proteomics experiment
    uri: http://edamontology.org/topic_3520
  - term: Machine learning
    uri: http://edamontology.org/topic_3474
  - term: Cheminformatics
    uri: http://edamontology.org/topic_2258
  - term: Chemistry
    uri: http://edamontology.org/topic_3314
  validated: 0
  version: []
- accessibility: Open access
  additionDate: '2021-01-18T11:04:22Z'
  biotoolsCURIE: biotools:mfassignr
  biotoolsID: mfassignr
  collectionID: []
  confidence_flag: tool
  cost: Free of charge
  credit: []
  description: 'Molecular formula assignment software for ultrahigh resolution mass
    spectrometry analysis of environmental complex mixtures.


    Ultrahigh resolution mass spectrometry is widely used for nontargeted analysis
    of complex environmental and biological mixtures, such as dissolved organic matter,
    due to its unparalleled ability to provide accurate mass measurements.'
  documentation:
  - note: null
    type:
    - Training material
    url: https://training.galaxyproject.org/training-material/topics/metabolomics/tutorials/mfassignr/tutorial.html
  download:
  - note: null
    type: Software package
    url: https://bioconda.github.io/recipes/r-mfassignr/README.html
    version: null
  - note: null
    type: Tool wrapper (Galaxy)
    url: https://github.com/RECETOX/galaxytools/tree/master/tools/mfassignr
    version: null
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  function:
  - cmd: null
    input:
    - data:
        term: Mass spectrum
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      format:
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        uri: http://edamontology.org/format_3751
    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:
    - data:
        term: Mass spectrum
        uri: http://edamontology.org/data_0943
      format:
      - term: DSV
        uri: http://edamontology.org/format_3751
    note: null
    operation:
    - term: Mass spectra calibration
      uri: http://edamontology.org/operation_3627
    output:
    - data:
        term: Mass spectrum
        uri: http://edamontology.org/data_0943
      format:
      - term: DSV
        uri: http://edamontology.org/format_3751
  - cmd: null
    input:
    - data:
        term: Mass spectrum
        uri: http://edamontology.org/data_0943
      format:
      - term: DSV
        uri: http://edamontology.org/format_3751
    note: null
    operation:
    - term: Deisotoping
      uri: http://edamontology.org/operation_3629
    - term: Annotation
      uri: http://edamontology.org/operation_0226
    output:
    - data:
        term: Mass spectrum
        uri: http://edamontology.org/data_0943
      format:
      - term: DSV
        uri: http://edamontology.org/format_3751
  homepage: https://github.com/skschum/MFAssignR
  homepage_status: 0
  language:
  - R
  lastUpdate: '2025-11-04T10:19:55.271318Z'
  license: GPL-2.0
  link:
  - note: null
    type:
    - Galaxy service
    url: https://toolshed.g2.bx.psu.edu/view/recetox/suite_mfassignr/114e55a434da
  - note: null
    type:
    - Repository
    url: https://github.com/skschum/MFAssignR
  - note: null
    type:
    - Mirror
    url: https://github.com/RECETOX/MFAssignR
  maturity: Emerging
  name: MFAssignR
  operatingSystem: []
  otherID: []
  owner: Niclaskn
  publication:
  - doi: 10.1016/J.ENVRES.2020.110114
    metadata:
      abstract: ''
      authors: []
      citationCount: 91
      date: '2020-12-01T00:00:00Z'
      journal: Environmental Research
      title: 'MFAssignR: Molecular formula assignment software for ultrahigh resolution
        mass spectrometry analysis of environmental complex mixtures'
    note: null
    pmcid: null
    pmid: '32866496'
    type: []
    version: null
  relation: []
  toolType:
  - Library
  topic:
  - term: Proteomics experiment
    uri: http://edamontology.org/topic_3520
  - term: Workflows
    uri: http://edamontology.org/topic_0769
  - term: Metabolomics
    uri: http://edamontology.org/topic_3172
  validated: 0
  version: []
- accessibility: null
  additionDate: '2021-01-18T10:23:10Z'
  biotoolsCURIE: biotools:spec2vec
  biotoolsID: spec2vec
  collectionID: []
  confidence_flag: tool
  cost: null
  credit:
  - email: f.huber@esciencecenter.nl
    fundrefid: null
    gridid: null
    name: Florian Huber
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  description: 'Improved mass spectral similarity scoring through learning of structural
    relationships.


    Spec2vec is a novel spectral similarity score inspired by a natural language processing
    algorithm -- Word2Vec. Where Word2Vec learns relationships between words in sentences,
    spec2vec does so for mass fragments and neutral losses in MS/MS spectra. The spectral
    similarity score is based on spectral embeddings learnt from the fragmental relationships
    within a large set of spectral data.


    Analysis and benchmarking of mass spectra similarity measures using gnps data
    set.'
  documentation: []
  download:
  - note: null
    type: Source code
    url: https://github.com/iomega/spec2vec
    version: null
  - note: null
    type: Software package
    url: https://pypi.org/project/spec2vec/
    version: null
  - note: null
    type: Tool wrapper (Galaxy)
    url: https://github.com/RECETOX/galaxytools/tree/master/tools/spec2vec
    version: null
  editPermission:
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  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Mass spectrum
        uri: http://edamontology.org/data_0943
      format:
      - term: MGF
        uri: http://edamontology.org/format_3651
      - term: MSP
        uri: http://edamontology.org/format_4039
      - term: JSON
        uri: http://edamontology.org/format_3464
    note: null
    operation:
    - term: Database search
      uri: http://edamontology.org/operation_2421
    - term: Comparison
      uri: http://edamontology.org/operation_2424
    - term: Spectral library search
      uri: http://edamontology.org/operation_3801
    - term: Natural product identification
      uri: http://edamontology.org/operation_3803
    output:
    - data:
        term: Score
        uri: http://edamontology.org/data_1772
      format:
      - term: DSV
        uri: http://edamontology.org/format_3751
      - term: JSON
        uri: http://edamontology.org/format_3464
  - cmd: null
    input:
    - data:
        term: Mass spectrum
        uri: http://edamontology.org/data_0943
      format: []
    note: null
    operation:
    - term: Modelling and simulation
      uri: http://edamontology.org/operation_2426
    output:
    - data:
        term: Mathematical model
        uri: http://edamontology.org/data_0950
      format: []
  homepage: https://github.com/iomega/spec2vec
  homepage_status: 0
  language:
  - Python
  lastUpdate: '2025-11-04T08:56:02.340299Z'
  license: Apache-2.0
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/iomega/spec2vec_gnps_data_analysis
  maturity: null
  name: Spec2Vec
  operatingSystem: []
  otherID: []
  owner: zsmag19
  publication:
  - doi: 10.1101/2020.08.11.245928
    metadata: null
    note: null
    pmcid: null
    pmid: null
    type: []
    version: null
  relation: []
  toolType: []
  topic:
  - term: Proteomics experiment
    uri: http://edamontology.org/topic_3520
  - term: Metabolomics
    uri: http://edamontology.org/topic_3172
  - term: Natural language processing
    uri: http://edamontology.org/topic_0218
  - term: Proteomics
    uri: http://edamontology.org/topic_0121
  validated: 0
  version: []
- accessibility: Open access
  additionDate: '2021-10-11T08:42:43.272159Z'
  biotoolsCURIE: biotools:ms2deepscore
  biotoolsID: ms2deepscore
  collectionID: []
  confidence_flag: tool
  cost: null
  credit:
  - email: f.huber@esciencecenter.nl
    fundrefid: null
    gridid: null
    name: Florian Huber
    note: null
    orcidid: https://orcid.org/0000-0002-3535-9406
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  description: MS2DeepScore is a deep learning similarity measure for mass fragmentation
    spectrum comparisons. MS2DeepScore provides a Siamese neural network that is trained
    to predict molecular structural similarities (Tanimoto scores) from pairs of mass
    spectrometry spectra.
  documentation: []
  download:
  - note: null
    type: Tool wrapper (Galaxy)
    url: https://github.com/RECETOX/galaxytools/tree/master/tools/ms2deepscore
    version: null
  - note: null
    type: Source code
    url: https://github.com/matchms/ms2deepscore
    version: null
  - note: null
    type: Software package
    url: https://pypi.org/project/ms2deepscore/
    version: null
  editPermission:
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  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Mass spectrum
        uri: http://edamontology.org/data_0943
      format:
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        uri: http://edamontology.org/format_3651
      - term: mzML
        uri: http://edamontology.org/format_3244
      - term: MSP
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        uri: http://edamontology.org/format_3464
    note: null
    operation:
    - term: Natural product identification
      uri: http://edamontology.org/operation_3803
    - term: Comparison
      uri: http://edamontology.org/operation_2424
    - term: Spectral library search
      uri: http://edamontology.org/operation_3801
    output:
    - data:
        term: Score
        uri: http://edamontology.org/data_1772
      format:
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      - term: JSON
        uri: http://edamontology.org/format_3464
  - cmd: null
    input:
    - data:
        term: Mass spectrometry data
        uri: http://edamontology.org/data_2536
      format:
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        uri: http://edamontology.org/format_3651
      - term: MSP
        uri: http://edamontology.org/format_4039
    note: null
    operation:
    - term: Modelling and simulation
      uri: http://edamontology.org/operation_2426
    output:
    - data:
        term: Mathematical model
        uri: http://edamontology.org/data_0950
      format:
      - term: JSON
        uri: http://edamontology.org/format_3464
  homepage: https://github.com/matchms/ms2deepscore
  homepage_status: 0
  language:
  - Python
  lastUpdate: '2025-11-04T08:54:50.531589Z'
  license: Apache-2.0
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/matchms/ms2deepscore
  - note: null
    type:
    - Galaxy service
    url: https://toolshed.g2.bx.psu.edu/view/recetox/suite_ms2deepscore/2b7360b26610
  maturity: null
  name: MS2DeepScore
  operatingSystem: []
  otherID: []
  owner: Kigaard
  publication:
  - doi: 10.1101/2021.04.18.440324
    metadata: null
    note: null
    pmcid: null
    pmid: null
    type:
    - Primary
    version: null
  relation: []
  toolType:
  - Library
  topic:
  - term: Proteomics experiment
    uri: http://edamontology.org/topic_3520
  - term: Machine learning
    uri: http://edamontology.org/topic_3474
  - term: Metabolomics
    uri: http://edamontology.org/topic_3172
  - term: Small molecules
    uri: http://edamontology.org/topic_0154
  - term: Compound libraries and screening
    uri: http://edamontology.org/topic_3343
  validated: 0
  version: []
- accessibility: Open access
  additionDate: '2023-08-24T10:15:08.106111Z'
  biotoolsCURIE: biotools:maw
  biotoolsID: maw
  collectionID: []
  confidence_flag: tool
  cost: Free of charge
  credit:
  - email: mahnoor.zulfiqar@uni-jena.de
    fundrefid: null
    gridid: null
    name: Mahnoor Zulfiqar
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  - email: christoph.steinbeck@uni-jena.de
    fundrefid: null
    gridid: null
    name: Christoph Steinbeck
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  - email: kristian.peters@ipb-halle.de
    fundrefid: null
    gridid: null
    name: Kristian Peters
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Luiz Gadelha
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Maria Sorokina
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  description: Metabolome Annotation Workflow for untargeted tandem mass spectrometry.
  documentation: []
  download: []
  editPermission:
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  elixirCommunity: []
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  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Protein identification
      uri: http://edamontology.org/operation_3767
    - term: Natural product identification
      uri: http://edamontology.org/operation_3803
    - term: Tag-based peptide identification
      uri: http://edamontology.org/operation_3643
    - term: Data retrieval
      uri: http://edamontology.org/operation_2422
    output: []
  homepage: https://github.com/zmahnoor14/MAW
  homepage_status: 0
  language:
  - Python
  - R
  lastUpdate: '2025-11-03T16:47:22.668278Z'
  license: null
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/zmahnoor14/MAW-Benchmark
  maturity: null
  name: MAW
  operatingSystem:
  - Mac
  - Linux
  - Windows
  otherID: []
  owner: Pub2Tools
  publication:
  - doi: 10.1186/s13321-023-00695-y
    metadata:
      abstract: Mapping the chemical space of compounds to chemical structures remains
        a challenge in metabolomics. Despite the advancements in untargeted liquid
        chromatography-mass spectrometry (LC–MS) to achieve a high-throughput profile
        of metabolites from complex biological resources, only a small fraction of
        these metabolites can be annotated with confidence. Many novel computational
        methods and tools have been developed to enable chemical structure annotation
        to known and unknown compounds such as in silico generated spectra and molecular
        networking. Here, we present an automated and reproducible Metabolome Annotation
        Workflow (MAW) for untargeted metabolomics data to further facilitate and
        automate the complex annotation by combining tandem mass spectrometry (MS2)
        input data pre-processing, spectral and compound database matching with computational
        classification, and in silico annotation. MAW takes the LC-MS2 spectra as
        input and generates a list of putative candidates from spectral and compound
        databases. The databases are integrated via the R package Spectra and the
        metabolite annotation tool SIRIUS as part of the R segment of the workflow
        (MAW-R). The final candidate selection is performed using the cheminformatics
        tool RDKit in the Python segment (MAW-Py). Furthermore, each feature is assigned
        a chemical structure and can be imported to a chemical structure similarity
        network. MAW is following the FAIR (Findable, Accessible, Interoperable, Reusable)
        principles and has been made available as the docker images, maw-r and maw-py.
        The source code and documentation are available on GitHub (https://github.com/zmahnoor14/MAW).
        The performance of MAW is evaluated on two case studies. MAW can improve candidate
        ranking by integrating spectral databases with annotation tools like SIRIUS
        which contributes to an efficient candidate selection procedure. The results
        from MAW are also reproducible and traceable, compliant with the FAIR guidelines.
        Taken together, MAW could greatly facilitate automated metabolite characterization
        in diverse fields such as clinical metabolomics and natural product discovery.
      authors:
      - name: Zulfiqar M.
      - name: Gadelha L.
      - name: Steinbeck C.
      - name: Sorokina M.
      - name: Peters K.
      citationCount: 10
      date: '2023-12-01T00:00:00Z'
      journal: Journal of Cheminformatics
      title: 'MAW: the reproducible Metabolome Annotation Workflow for untargeted
        tandem mass spectrometry'
    note: null
    pmcid: PMC9985203
    pmid: '36871033'
    type: []
    version: null
  relation: []
  toolType:
  - Workflow
  topic:
  - term: Metabolomics
    uri: http://edamontology.org/topic_3172
  - term: Proteomics experiment
    uri: http://edamontology.org/topic_3520
  - term: Workflows
    uri: http://edamontology.org/topic_0769
  - term: Small molecules
    uri: http://edamontology.org/topic_0154
  - term: Cheminformatics
    uri: http://edamontology.org/topic_2258
  validated: 0
  version: []
- accessibility: Open access
  additionDate: '2019-08-09T13:14:25Z'
  biotoolsCURIE: biotools:El-MAVEN
  biotoolsID: El-MAVEN
  collectionID: []
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: info@elucidata.io
    fundrefid: null
    gridid: null
    name: null
    note: null
    orcidid: null
    rorid: null
    typeEntity: null
    typeRole:
    - Support
    url: null
  - email: elmaven@elucidata.io
    fundrefid: null
    gridid: null
    name: null
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  description: Fast, Robust, and User-Friendly Mass Spectrometry Data Processing Engine
    for Metabolomics.
  documentation:
  - note: null
    type:
    - User manual
    url: https://elucidatainc.github.io/ElMaven/documentation/
  download:
  - note: null
    type: Binaries
    url: https://elucidatainc.github.io/ElMaven/Downloads/
    version: null
  - note: null
    type: Source code
    url: https://github.com/ElucidataInc/ElMaven/releases
    version: null
  editPermission:
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    type: group
  elixirCommunity: []
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  function: []
  homepage: https://github.com/ElucidataInc/ElMaven
  homepage_status: 0
  language: []
  lastUpdate: '2025-11-03T16:47:19.388844Z'
  license: GPL-2.0
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/ElucidataInc/ElMaven
  - note: null
    type:
    - Issue tracker
    url: https://github.com/ElucidataInc/ElMaven/issues
  maturity: Mature
  name: El-MAVEN
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: hans
  publication:
  - doi: 10.1007/978-1-4939-9236-2_19
    metadata:
      abstract: ''
      authors: []
      citationCount: 106
      date: '2019-01-01T00:00:00Z'
      journal: Methods in Molecular Biology
      title: 'EL-MAVEN: A fast, robust, and user-friendly mass spectrometry data processing
        engine for metabolomics'
    note: null
    pmcid: null
    pmid: '31119671'
    type:
    - Primary
    version: null
  relation: []
  toolType:
  - Desktop application
  topic:
  - term: Metabolomics
    uri: http://edamontology.org/topic_3172
  - term: Proteomics experiment
    uri: http://edamontology.org/topic_3520
  - term: Molecular interactions, pathways and networks
    uri: http://edamontology.org/topic_0602
  validated: 1
  version: []
- accessibility: Open access
  additionDate: '2022-09-05T21:19:03.847868Z'
  biotoolsCURIE: biotools:msnovelist
  biotoolsID: msnovelist
  collectionID: []
  confidence_flag: tool
  cost: Free of charge
  credit:
  - email: zamboni@imsb.biol.ethz.ch
    fundrefid: null
    gridid: null
    name: Nicola Zamboni
    note: null
    orcidid: https://orcid.org/0000-0003-1271-1021
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Sebastian Böcker
    note: null
    orcidid: https://orcid.org/0000-0002-9304-8091
    rorid: null
    typeEntity: null
    typeRole: []
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Kai Dührkop
    note: null
    orcidid: https://orcid.org/0000-0002-9056-0540
    rorid: null
    typeEntity: null
    typeRole: []
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Michael A. Stravs
    note: null
    orcidid: https://orcid.org/0000-0002-1426-8572
    rorid: null
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    typeRole: []
    url: null
  description: De novo structure generation from mass spectra.
  documentation: []
  download: []
  editPermission:
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    type: group
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  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Ab initio structure prediction
      uri: http://edamontology.org/operation_0476
    - term: Spectrum calculation
      uri: http://edamontology.org/operation_3860
    - term: Phasing
      uri: http://edamontology.org/operation_3454
    - term: Deposition
      uri: http://edamontology.org/operation_3431
    - term: Small molecule design
      uri: http://edamontology.org/operation_4009
    output: []
  homepage: https://github.com/meowcat/MSNovelist
  homepage_status: 0
  language:
  - Python
  - Java
  lastUpdate: '2025-11-03T16:47:18.329938Z'
  license: AGPL-3.0
  link: []
  maturity: null
  name: MSNovelist
  operatingSystem:
  - Mac
  - Linux
  - Windows
  otherID: []
  owner: Jennifer
  publication:
  - doi: 10.1038/S41592-022-01486-3
    metadata:
      abstract: © 2022, The Author(s).Current methods for structure elucidation of
        small molecules rely on finding similarity with spectra of known compounds,
        but do not predict structures de novo for unknown compound classes. We present
        MSNovelist, which combines fingerprint prediction with an encoder–decoder
        neural network to generate structures de novo solely from tandem mass spectrometry
        (MS2) spectra. In an evaluation with 3,863 MS2 spectra from the Global Natural
        Product Social Molecular Networking site, MSNovelist predicted 25% of structures
        correctly on first rank, retrieved 45% of structures overall and reproduced
        61% of correct database annotations, without having ever seen the structure
        in the training phase. Similarly, for the CASMI 2016 challenge, MSNovelist
        correctly predicted 26% and retrieved 57% of structures, recovering 64% of
        correct database annotations. Finally, we illustrate the application of MSNovelist
        in a bryophyte MS2 dataset, in which de novo structure prediction substantially
        outscored the best database candidate for seven spectra. MSNovelist is ideally
        suited to complement library-based annotation in the case of poorly represented
        analyte classes and novel compounds.
      authors:
      - name: Stravs M.A.
      - name: Duhrkop K.
      - name: Bocker S.
      - name: Zamboni N.
      citationCount: 1
      date: '2022-07-01T00:00:00Z'
      journal: Nature Methods
      title: 'MSNovelist: de novo structure generation from mass spectra'
    note: null
    pmcid: PMC9262714
    pmid: '35637304'
    type: []
    version: null
  relation: []
  toolType:
  - Command-line tool
  topic:
  - term: Proteomics experiment
    uri: http://edamontology.org/topic_3520
  - term: Metabolomics
    uri: http://edamontology.org/topic_3172
  - term: Small molecules
    uri: http://edamontology.org/topic_0154
  - term: Machine learning
    uri: http://edamontology.org/topic_3474
  - term: Lipids
    uri: http://edamontology.org/topic_0153
  validated: 1
  version: []
- accessibility: Open access
  additionDate: '2021-10-28T20:02:19.622064Z'
  biotoolsCURIE: biotools:peakpanther
  biotoolsID: peakpanther
  collectionID: []
  confidence_flag: tool
  cost: Free of charge
  credit:
  - email: phenomecentre@imperial.ac.uk
    fundrefid: null
    gridid: null
    name: Arnaud M Wolfer
    note: null
    orcidid: https://orcid.org/0000-0001-5856-3218
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Goncalo Correia
    note: null
    orcidid: https://orcid.org/0000-0001-8271-9294
    rorid: null
    typeEntity: null
    typeRole: []
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Jake Pearce
    note: null
    orcidid: null
    rorid: null
    typeEntity: null
    typeRole: []
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Caroline Sands
    note: null
    orcidid: null
    rorid: null
    typeEntity: null
    typeRole: []
    url: null
  description: R package for large-scale targeted extraction and integration of annotated
    metabolic features in LC-MS profiling datasets.
  documentation:
  - note: null
    type:
    - General
    url: https://phenomecentre.github.io/peakPantheR.github.io/
  download:
  - note: null
    type: Source code
    url: https://github.com/phenomecentre/peakPantheR/
    version: null
  editPermission:
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  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Natural product identification
      uri: http://edamontology.org/operation_3803
    - term: Feature extraction
      uri: http://edamontology.org/operation_3937
    - term: Peak detection
      uri: http://edamontology.org/operation_3215
    output: []
  homepage: https://phenomecentre.github.io/peakPantheR.github.io/
  homepage_status: 0
  language:
  - R
  lastUpdate: '2025-11-03T16:47:17.380949Z'
  license: GPL-3.0
  link:
  - note: null
    type:
    - Repository
    url: https://bioconductor.org/packages/peakPantheR/
  - note: null
    type:
    - Repository
    url: https://github.com/phenomecentre/metabotyping-dementia-urine
  maturity: null
  name: peakPantheR
  operatingSystem:
  - Mac
  - Linux
  - Windows
  otherID: []
  owner: Jennifer
  publication:
  - doi: 10.1093/bioinformatics/btab433
    metadata:
      abstract: 'Summary: Untargeted liquid chromatography-mass spectrometry (LC-MS)
        profiling assays are capable of measuring thousands of chemical compounds
        in a single sample, but unreliable feature extraction and metabolite identification
        remain considerable barriers to their interpretation and usefulness. peakPantheR
        (Peak Picking and ANnoTation of High-resolution Experiments in R) is an R
        package for the targeted extraction and integration of annotated features
        from LC-MS profiling experiments. It takes advantage of chromatographic and
        spectral databases and prior information of sample matrix composition to generate
        annotated and interpretable metabolic phenotypic datasets and power workflows
        for real-time data quality assessment.'
      authors:
      - name: Wolfer A.M.
      - name: Correia G.D.S.
      - name: Sands C.J.
      - name: Camuzeaux S.
      - name: Yuen A.H.Y.
      - name: Chekmeneva E.
      - name: Takats Z.
      - name: Pearce J.T.M.
      - name: Lewis M.R.
      citationCount: 21
      date: '2021-12-15T00:00:00Z'
      journal: Bioinformatics
      title: Extraction and integration of annotated metabolic features in LC-MS profiling
        datasets
    note: null
    pmcid: PMC8665750
    pmid: '34125879'
    type: []
    version: null
  relation: []
  toolType:
  - Library
  topic:
  - term: Metabolomics
    uri: http://edamontology.org/topic_3172
  - term: Endocrinology and metabolism
    uri: http://edamontology.org/topic_3407
  - term: Proteomics experiment
    uri: http://edamontology.org/topic_3520
  - term: Small molecules
    uri: http://edamontology.org/topic_0154
  - term: Workflows
    uri: http://edamontology.org/topic_0769
  validated: 1
  version: []
- accessibility: null
  additionDate: '2021-01-18T11:58:45Z'
  biotoolsCURIE: biotools:canopus
  biotoolsID: canopus
  collectionID: []
  confidence_flag: tool
  cost: null
  credit:
  - email: null
    fundrefid: null
    gridid: null
    name: Sebastian Böcker
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  description: CANOPUS is a tool for predicting compound classes directly from MS/MS.
    Because it does not depend on any database, CANOPUS is suitable for the classification
    of unknowns.
  documentation: []
  download: []
  editPermission:
    authors:
    - recetox-specdatri
    type: group
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Visualisation
      uri: http://edamontology.org/operation_0337
    - term: Spectrum calculation
      uri: http://edamontology.org/operation_3860
    - term: Natural product identification
      uri: http://edamontology.org/operation_3803
    - term: Spectral library search
      uri: http://edamontology.org/operation_3801
    - term: Deposition
      uri: http://edamontology.org/operation_3431
    output: []
  homepage: https://bio.informatik.uni-jena.de/software/canopus/
  homepage_status: 0
  language: []
  lastUpdate: '2025-11-03T16:47:13.400194Z'
  license: MIT
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/kaibioinfo/canopus_treemap
  maturity: null
  name: CANOPUS
  operatingSystem: []
  otherID: []
  owner: Kigaard
  publication:
  - doi: 10.1038/S41587-020-0740-8
    metadata:
      abstract: © 2020, The Author(s), under exclusive licence to Springer Nature
        America, Inc.Metabolomics using nontargeted tandem mass spectrometry can detect
        thousands of molecules in a biological sample. However, structural molecule
        annotation is limited to structures present in libraries or databases, restricting
        analysis and interpretation of experimental data. Here we describe CANOPUS
        (class assignment and ontology prediction using mass spectrometry), a computational
        tool for systematic compound class annotation. CANOPUS uses a deep neural
        network to predict 2,497 compound classes from fragmentation spectra, including
        all biologically relevant classes. CANOPUS explicitly targets compounds for
        which neither spectral nor structural reference data are available and predicts
        classes lacking tandem mass spectrometry training data. In evaluation using
        reference data, CANOPUS reached very high prediction performance (average
        accuracy of 99.7% in cross-validation) and outperformed four baseline methods.
        We demonstrate the broad utility of CANOPUS by investigating the effect of
        microbial colonization in the mouse digestive system, through analysis of
        the chemodiversity of different Euphorbia plants and regarding the discovery
        of a marine natural product, revealing biological insights at the compound
        class level.
      authors:
      - name: Duhrkop K.
      - name: Nothias L.-F.
      - name: Fleischauer M.
      - name: Reher R.
      - name: Ludwig M.
      - name: Hoffmann M.A.
      - name: Petras D.
      - name: Gerwick W.H.
      - name: Rousu J.
      - name: Dorrestein P.C.
      - name: Bocker S.
      citationCount: 24
      date: '2021-04-01T00:00:00Z'
      journal: Nature Biotechnology
      title: Systematic classification of unknown metabolites using high-resolution
        fragmentation mass spectra
    note: null
    pmcid: null
    pmid: '33230292'
    type: []
    version: null
  relation: []
  toolType:
  - Desktop application
  topic:
  - term: Metabolomics
    uri: http://edamontology.org/topic_3172
  - term: Proteomics experiment
    uri: http://edamontology.org/topic_3520
  - term: Machine learning
    uri: http://edamontology.org/topic_3474
  - term: Small molecules
    uri: http://edamontology.org/topic_0154
  - term: Plant biology
    uri: http://edamontology.org/topic_0780
  validated: 0
  version: []
- accessibility: Open access
  additionDate: '2022-09-04T23:10:37.868759Z'
  biotoolsCURIE: biotools:peakforest
  biotoolsID: peakforest
  collectionID: []
  confidence_flag: tool
  cost: Free of charge
  credit:
  - email: Franck.Giacomoni@inrae.fr
    fundrefid: null
    gridid: null
    name: Franck Giacomoni
    note: null
    orcidid: https://orcid.org/0000-0001-6063-4214
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Estelle Pujos-Guillot
    note: null
    orcidid: null
    rorid: null
    typeEntity: null
    typeRole: []
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Christophe Junot
    note: null
    orcidid: null
    rorid: null
    typeEntity: null
    typeRole: []
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: François Fenaille
    note: null
    orcidid: null
    rorid: null
    typeEntity: null
    typeRole: []
    url: null
  description: A multi-platform digital infrastructure for interoperable metabolite
    spectral data and metadata management.
  documentation: []
  download: []
  editPermission:
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    - recetox-specdatri
    type: group
  elixirCommunity: []
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  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Natural product identification
      uri: http://edamontology.org/operation_3803
    - term: Spectral library search
      uri: http://edamontology.org/operation_3801
    - term: Deposition
      uri: http://edamontology.org/operation_3431
    - term: Data retrieval
      uri: http://edamontology.org/operation_2422
    output: []
  homepage: https://peakforest.org
  homepage_status: 0
  language:
  - Java
  - JavaScript
  lastUpdate: '2025-11-03T16:47:12.424836Z'
  license: Other
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/peakforest
  maturity: null
  name: PeakForest
  operatingSystem:
  - Mac
  - Linux
  - Windows
  otherID: []
  owner: Jennifer
  publication:
  - doi: 10.1007/S11306-022-01899-3
    metadata:
      abstract: '© 2022, The Author(s).Introduction: Accuracy of feature annotation
        and metabolite identification in biological samples is a key element in metabolomics
        research. However, the annotation process is often hampered by the lack of
        spectral reference data in experimental conditions, as well as logistical
        difficulties in the spectral data management and exchange of annotations between
        laboratories. Objectives: To design an open-source infrastructure allowing
        hosting both nuclear magnetic resonance (NMR) and mass spectra (MS), with
        an ergonomic Web interface and Web services to support metabolite annotation
        and laboratory data management. Methods: We developed the PeakForest infrastructure,
        an open-source Java tool with automatic programming interfaces that can be
        deployed locally to organize spectral data for metabolome annotation in laboratories.
        Standardized operating procedures and formats were included to ensure data
        quality and interoperability, in line with international recommendations and
        FAIR principles. Results: PeakForest is able to capture and store experimental
        spectral MS and NMR metadata as well as collect and display signal annotations.
        This modular system provides a structured database with inbuilt tools to curate
        information, browse and reuse spectral information in data treatment. PeakForest
        offers data formalization and centralization at the laboratory level, facilitating
        shared spectral data across laboratories and integration into public databases.
        Conclusion: PeakForest is a comprehensive resource which addresses a technical
        bottleneck, namely large-scale spectral data annotation and metabolite identification
        for metabolomics laboratories with multiple instruments. PeakForest databases
        can be used in conjunction with bespoke data analysis pipelines in the Galaxy
        environment, offering the opportunity to meet the evolving needs of metabolomics
        research. Developed and tested by the French metabolomics community, PeakForest
        is freely-available at https://github.com/peakforest.'
      authors:
      - name: Paulhe N.
      - name: Canlet C.
      - name: Damont A.
      - name: Peyriga L.
      - name: Durand S.
      - name: Deborde C.
      - name: Alves S.
      - name: Bernillon S.
      - name: Berton T.
      - name: Bir R.
      - name: Bouville A.
      - name: Cahoreau E.
      - name: Centeno D.
      - name: Costantino R.
      - name: Debrauwer L.
      - name: Delabriere A.
      - name: Duperier C.
      - name: Emery S.
      - name: Flandin A.
      - name: Hohenester U.
      - name: Jacob D.
      - name: Joly C.
      - name: Jousse C.
      - name: Lagree M.
      - name: Lamari N.
      - name: Lefebvre M.
      - name: Lopez-Piffet C.
      - name: Lyan B.
      - name: Maucourt M.
      - name: Migne C.
      - name: Olivier M.-F.
      - name: Rathahao-Paris E.
      - name: Petriacq P.
      - name: Pinelli J.
      - name: Roch L.
      - name: Roger P.
      - name: Roques S.
      - name: Tabet J.-C.
      - name: Tremblay-Franco M.
      - name: Traikia M.
      - name: Warnet A.
      - name: Zhendre V.
      - name: Rolin D.
      - name: Jourdan F.
      - name: Thevenot E.
      - name: Moing A.
      - name: Jamin E.
      - name: Fenaille F.
      - name: Junot C.
      - name: Pujos-Guillot E.
      - name: Giacomoni F.
      citationCount: 0
      date: '2022-06-01T00:00:00Z'
      journal: Metabolomics
      title: 'PeakForest: a multi-platform digital infrastructure for interoperable
        metabolite spectral data and metadata management'
    note: null
    pmcid: PMC9197906
    pmid: '35699774'
    type: []
    version: null
  relation: []
  toolType:
  - Web application
  - Command-line tool
  topic:
  - term: Metabolomics
    uri: http://edamontology.org/topic_3172
  - term: Small molecules
    uri: http://edamontology.org/topic_0154
  - term: NMR
    uri: http://edamontology.org/topic_0593
  - term: Proteomics experiment
    uri: http://edamontology.org/topic_3520
  - term: Data submission, annotation and curation
    uri: http://edamontology.org/topic_0219
  validated: 1
  version: []
- accessibility: Open access
  additionDate: '2023-12-01T15:46:02.196263Z'
  biotoolsCURIE: biotools:buddy
  biotoolsID: buddy
  collectionID: []
  confidence_flag: tool
  cost: Free of charge
  credit:
  - email: thuan@chem.ubc.ca
    fundrefid: null
    gridid: null
    name: Tao Huan
    note: null
    orcidid: http://orcid.org/0000-0001-6295-2435
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  description: Open-source cheminformatic software platform developed for MS-based
    metabolomics research.
  documentation:
  - note: null
    type:
    - User manual
    url: https://philipbear.github.io/BUDDY_Metabolomics
  download: []
  editPermission:
    authors:
    - recetox-specdatri
    type: group
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Peptide database search
      uri: http://edamontology.org/operation_3646
    - term: de Novo sequencing
      uri: http://edamontology.org/operation_3644
    - term: Optimisation and refinement
      uri: http://edamontology.org/operation_2425
    output: []
  homepage: https://github.com/HuanLab/BUDDY
  homepage_status: 0
  language:
  - C#
  lastUpdate: '2025-11-03T16:45:48.375514Z'
  license: MIT
  link: []
  maturity: null
  name: BUDDY
  operatingSystem:
  - Mac
  - Linux
  - Windows
  otherID: []
  owner: Pub2Tools
  publication:
  - doi: 10.1038/s41592-023-01850-x
    metadata:
      abstract: A substantial fraction of metabolic features remains undetermined
        in mass spectrometry (MS)-based metabolomics, and molecular formula annotation
        is the starting point for unraveling their chemical identities. Here we present
        bottom-up tandem MS (MS/MS) interrogation, a method for de novo formula annotation.
        Our approach prioritizes MS/MS-explainable formula candidates, implements
        machine-learned ranking and offers false discovery rate estimation. Compared
        with the mathematically exhaustive formula enumeration, our approach shrinks
        the formula candidate space by 42.8% on average. Method benchmarking on annotation
        accuracy was systematically carried out on reference MS/MS libraries and real
        metabolomics datasets. Applied on 155,321 recurrent unidentified spectra,
        our approach confidently annotated >5,000 novel molecular formulae absent
        from chemical databases. Beyond the level of individual metabolic features,
        we combined bottom-up MS/MS interrogation with global optimization to refine
        formula annotations while revealing peak interrelationships. This approach
        allowed the systematic annotation of 37 fatty acid amide molecules in human
        fecal data. All bioinformatics pipelines are available in a standalone software,
        BUDDY (https://github.com/HuanLab/BUDDY).
      authors:
      - name: Xing S.
      - name: Shen S.
      - name: Xu B.
      - name: Li X.
      - name: Huan T.
      citationCount: 21
      date: '2023-06-01T00:00:00Z'
      journal: Nature Methods
      title: 'BUDDY: molecular formula discovery via bottom-up MS/MS interrogation'
    note: null
    pmcid: null
    pmid: '37055660'
    type: []
    version: null
  relation: []
  toolType:
  - Desktop application
  topic:
  - term: Metabolomics
    uri: http://edamontology.org/topic_3172
  - term: Proteomics experiment
    uri: http://edamontology.org/topic_3520
  - term: Cheminformatics
    uri: http://edamontology.org/topic_2258
  - term: Endocrinology and metabolism
    uri: http://edamontology.org/topic_3407
  - term: Biochemistry
    uri: http://edamontology.org/topic_3292
  validated: 0
  version: []
- accessibility: null
  additionDate: '2021-05-26T20:56:35Z'
  biotoolsCURIE: biotools:ms_dial
  biotoolsID: ms_dial
  collectionID: []
  confidence_flag: null
  cost: null
  credit:
  - email: makoto.arita@riken.jp
    fundrefid: null
    gridid: null
    name: Makoto Arita
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  - email: hiroshi.tsugawa@riken.jp
    fundrefid: null
    gridid: null
    name: Hiroshi Tsugawa
    note: null
    orcidid: https://orcid.org/0000-0002-2015-3958
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  description: MS-DIAL was launched as a universal program for untargeted metabolomics
    that supports multiple instruments (GC/MS, GC/MS/MS, LC/MS, and LC/MS/MS) and
    MS vendors (Agilent, Bruker, LECO, Sciex, Shimadzu, Thermo, and Waters)
  documentation:
  - note: null
    type:
    - General
    url: https://mtbinfo-team.github.io/mtbinfo.github.io/MS-DIAL/tutorial
  - note: null
    type:
    - FAQ
    url: http://prime.psc.riken.jp/compms/msdial/faq.html
  download: []
  editPermission:
    authors:
    - recetox-specdatri
    type: group
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Deisotoping
      uri: http://edamontology.org/operation_3629
    - term: Peak detection
      uri: http://edamontology.org/operation_3215
    - term: Natural product identification
      uri: http://edamontology.org/operation_3803
    - term: MRM/SRM
      uri: http://edamontology.org/operation_3636
    output: []
  homepage: http://prime.psc.riken.jp/compms/msdial/main.html
  homepage_status: 0
  language: []
  lastUpdate: '2025-11-03T16:45:45.835795Z'
  license: null
  link: []
  maturity: null
  name: MS-DIAL
  operatingSystem:
  - Mac
  - Linux
  - Windows
  otherID: []
  owner: Kigaard
  publication:
  - doi: 10.1038/s41587-020-0531-2
    metadata:
      abstract: © 2020, The Author(s), under exclusive licence to Springer Nature
        America, Inc.We present Mass Spectrometry-Data Independent Analysis software
        version 4 (MS-DIAL 4), a comprehensive lipidome atlas with retention time,
        collision cross-section and tandem mass spectrometry information. We formulated
        mass spectral fragmentations of lipids across 117 lipid subclasses and included
        ion mobility tandem mass spectrometry. Using human, murine, algal and plant
        biological samples, we annotated and semiquantified 8,051 lipids using MS-DIAL
        4 with a 1–2% estimated false discovery rate. MS-DIAL 4 helps standardize
        lipidomics data and discover lipid pathways.
      authors:
      - name: Tsugawa H.
      - name: Ikeda K.
      - name: Takahashi M.
      - name: Satoh A.
      - name: Mori Y.
      - name: Uchino H.
      - name: Okahashi N.
      - name: Yamada Y.
      - name: Tada I.
      - name: Bonini P.
      - name: Higashi Y.
      - name: Okazaki Y.
      - name: Zhou Z.
      - name: Zhu Z.-J.
      - name: Koelmel J.
      - name: Cajka T.
      - name: Fiehn O.
      - name: Saito K.
      - name: Arita M.
      - name: Arita M.
      citationCount: 38
      date: '2020-10-01T00:00:00Z'
      journal: Nature Biotechnology
      title: A lipidome atlas in MS-DIAL 4
    note: null
    pmcid: null
    pmid: null
    type:
    - Primary
    version: null
  relation: []
  toolType:
  - Desktop application
  topic:
  - term: Proteomics experiment
    uri: http://edamontology.org/topic_3520
  - term: Lipids
    uri: http://edamontology.org/topic_0153
  - term: Metabolomics
    uri: http://edamontology.org/topic_3172
  validated: 0
  version: []
- accessibility: Open access
  additionDate: '2022-11-25T21:43:37.501728Z'
  biotoolsCURIE: biotools:tidymass
  biotoolsID: tidymass
  collectionID: []
  confidence_flag: tool
  cost: Free of charge
  credit:
  - email: caroline.johnson@yale.edu
    fundrefid: null
    gridid: null
    name: Caroline H. Johnson
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  - email: mpsnyder@stanford.edu
    fundrefid: null
    gridid: null
    name: Michael P. Snyder
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Xiaotao Shen
    note: null
    orcidid: http://orcid.org/0000-0002-9608-9964
    rorid: null
    typeEntity: null
    typeRole: []
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Hong Yan
    note: null
    orcidid: null
    rorid: null
    typeEntity: null
    typeRole: []
    url: null
  description: An Object-oriented Reproducible Analysis Framework for LC-MS Data.
  documentation: []
  download:
  - note: null
    type: Container file
    url: https://hub.docker.com/r/jaspershen/tidymass-case-study
    version: null
  - note: null
    type: Container file
    url: https://hub.docker.com/r/jaspershen/tidymass
    version: null
  - note: null
    type: Container file
    url: https://www.tidymass.org/start/tidymass_docker/
    version: null
  editPermission:
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    type: group
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Visualisation
      uri: http://edamontology.org/operation_0337
    output: []
  homepage: https://www.tidymass.org/
  homepage_status: 0
  language:
  - R
  lastUpdate: '2025-11-03T16:45:44.856713Z'
  license: MIT
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/tidymass
  - note: null
    type:
    - Other
    url: https://tidymass.tidymass.org/
  maturity: null
  name: tidyMass
  operatingSystem:
  - Mac
  - Linux
  - Windows
  otherID: []
  owner: Jennifer
  publication:
  - doi: 10.1038/s41467-022-32155-w
    metadata:
      abstract: Reproducibility, traceability, and transparency have been long-standing
        issues for metabolomics data analysis. Multiple tools have been developed,
        but limitations still exist. Here, we present the tidyMass project (https://www.tidymass.org/),
        a comprehensive R-based computational framework that can achieve the traceable,
        shareable, and reproducible workflow needs of data processing and analysis
        for LC-MS-based untargeted metabolomics. TidyMass is an ecosystem of R packages
        that share an underlying design philosophy, grammar, and data structure, which
        provides a comprehensive, reproducible, and object-oriented computational
        framework. The modular architecture makes tidyMass a highly flexible and extensible
        tool, which other users can improve and integrate with other tools to customize
        their own pipeline.
      authors:
      - name: Shen X.
      - name: Yan H.
      - name: Wang C.
      - name: Gao P.
      - name: Johnson C.H.
      - name: Snyder M.P.
      citationCount: 28
      date: '2022-12-01T00:00:00Z'
      journal: Nature Communications
      title: TidyMass an object-oriented reproducible analysis framework for LC–MS
        data
    note: null
    pmcid: PMC9334349
    pmid: '35902589'
    type: []
    version: null
  relation: []
  toolType:
  - Library
  topic:
  - term: Metabolomics
    uri: http://edamontology.org/topic_3172
  - term: Proteomics experiment
    uri: http://edamontology.org/topic_3520
  - term: Workflows
    uri: http://edamontology.org/topic_0769
  validated: 1
  version: []
- accessibility: Open access (with restrictions)
  additionDate: '2021-05-26T20:04:08Z'
  biotoolsCURIE: biotools:gnps
  biotoolsID: gnps
  collectionID: []
  confidence_flag: null
  cost: Free of charge (with restrictions)
  credit:
  - email: miw023@ucsd.edu
    fundrefid: null
    gridid: null
    name: Mingxun Wang
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  description: GNPS is a web-based mass spectrometry ecosystem that aims to be an
    open-access knowledge base for community-wide organization and sharing of raw,
    processed, or annotated fragmentation mass spectrometry data (MS/MS). GNPS aids
    in identification and discovery throughout the entire life cycle of data; from
    initial data acquisition/analysis to post publication.
  documentation:
  - note: null
    type:
    - General
    url: https://ccms-ucsd.github.io/GNPSDocumentation/
  - note: null
    type:
    - Quick start guide
    url: https://ccms-ucsd.github.io/GNPSDocumentation/quickstart/
  - note: null
    type:
    - API documentation
    url: https://ccms-ucsd.github.io/GNPSDocumentation/api/
  - note: null
    type:
    - FAQ
    url: https://ccms-ucsd.github.io/GNPSDocumentation/faq/
  download: []
  editPermission:
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    type: group
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  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Deposition
      uri: http://edamontology.org/operation_3431
    - term: Deisotoping
      uri: http://edamontology.org/operation_3629
    - term: Spectral counting
      uri: http://edamontology.org/operation_3637
    - term: Spectral library search
      uri: http://edamontology.org/operation_3801
    output: []
  homepage: https://gnps.ucsd.edu/
  homepage_status: 0
  language: []
  lastUpdate: '2025-11-03T16:45:43.961672Z'
  license: Other
  link:
  - note: null
    type:
    - Discussion forum
    url: https://groups.google.com/forum/#!forum/molecular_networking_bug_reports
  maturity: null
  name: GNPS
  operatingSystem: []
  otherID: []
  owner: Kigaard
  publication:
  - doi: 10.1038/NBT.3597
    metadata:
      abstract: © 2016 Nature America, Inc. All rights reserved.The potential of the
        diverse chemistries present in natural products (NP) for biotechnology and
        medicine remains untapped because NP databases are not searchable with raw
        data and the NP community has no way to share data other than in published
        papers. Although mass spectrometry (MS) techniques are well-suited to high-throughput
        characterization of NP, there is a pressing need for an infrastructure to
        enable sharing and curation of data. We present Global Natural Products Social
        Molecular Networking (GNPS; http://gnps.ucsd.edu), an open-access knowledge
        base for community-wide organization and sharing of raw, processed or identified
        tandem mass (MS/MS) spectrometry data. In GNPS, crowdsourced curation of freely
        available community-wide reference MS libraries will underpin improved annotations.
        Data-driven social-networking should facilitate identification of spectra
        and foster collaborations. We also introduce the concept of 'living data'
        through continuous reanalysis of deposited data.
      authors:
      - name: Wang M.
      - name: Carver J.J.
      - name: Phelan V.V.
      - name: Sanchez L.M.
      - name: Garg N.
      - name: Peng Y.
      - name: Nguyen D.D.
      - name: Watrous J.
      - name: Kapono C.A.
      - name: Luzzatto-Knaan T.
      - name: Porto C.
      - name: Bouslimani A.
      - name: Melnik A.V.
      - name: Meehan M.J.
      - name: Liu W.-T.
      - name: Crusemann M.
      - name: Boudreau P.D.
      - name: Esquenazi E.
      - name: Sandoval-Calderon M.
      - name: Kersten R.D.
      - name: Pace L.A.
      - name: Quinn R.A.
      - name: Duncan K.R.
      - name: Hsu C.-C.
      - name: Floros D.J.
      - name: Gavilan R.G.
      - name: Kleigrewe K.
      - name: Northen T.
      - name: Dutton R.J.
      - name: Parrot D.
      - name: Carlson E.E.
      - name: Aigle B.
      - name: Michelsen C.F.
      - name: Jelsbak L.
      - name: Sohlenkamp C.
      - name: Pevzner P.
      - name: Edlund A.
      - name: McLean J.
      - name: Piel J.
      - name: Murphy B.T.
      - name: Gerwick L.
      - name: Liaw C.-C.
      - name: Yang Y.-L.
      - name: Humpf H.-U.
      - name: Maansson M.
      - name: Keyzers R.A.
      - name: Sims A.C.
      - name: Johnson A.R.
      - name: Sidebottom A.M.
      - name: Sedio B.E.
      - name: Klitgaard A.
      - name: Larson C.B.
      - name: Boya C.A.P.
      - name: Torres-Mendoza D.
      - name: Gonzalez D.J.
      - name: Silva D.B.
      - name: Marques L.M.
      - name: Demarque D.P.
      - name: Pociute E.
      - name: O'Neill E.C.
      - name: Briand E.
      - name: Helfrich E.J.N.
      - name: Granatosky E.A.
      - name: Glukhov E.
      - name: Ryffel F.
      - name: Houson H.
      - name: Mohimani H.
      - name: Kharbush J.J.
      - name: Zeng Y.
      - name: Vorholt J.A.
      - name: Kurita K.L.
      - name: Charusanti P.
      - name: McPhail K.L.
      - name: Nielsen K.F.
      - name: Vuong L.
      - name: Elfeki M.
      - name: Traxler M.F.
      - name: Engene N.
      - name: Koyama N.
      - name: Vining O.B.
      - name: Baric R.
      - name: Silva R.R.
      - name: Mascuch S.J.
      - name: Tomasi S.
      - name: Jenkins S.
      - name: Macherla V.
      - name: Hoffman T.
      - name: Agarwal V.
      - name: Williams P.G.
      - name: Dai J.
      - name: Neupane R.
      - name: Gurr J.
      - name: Rodriguez A.M.C.
      - name: Lamsa A.
      - name: Zhang C.
      - name: Dorrestein K.
      - name: Duggan B.M.
      - name: Almaliti J.
      - name: Allard P.-M.
      - name: Phapale P.
      - name: Nothias L.-F.
      - name: Alexandrov T.
      - name: Litaudon M.
      - name: Wolfender J.-L.
      - name: Kyle J.E.
      - name: Metz T.O.
      - name: Peryea T.
      - name: Nguyen D.-T.
      - name: VanLeer D.
      - name: Shinn P.
      - name: Jadhav A.
      - name: Muller R.
      - name: Waters K.M.
      - name: Shi W.
      - name: Liu X.
      - name: Zhang L.
      - name: Knight R.
      - name: Jensen P.R.
      - name: Palsson B.O.
      - name: Pogliano K.
      - name: Linington R.G.
      - name: Gutierrez M.
      - name: Lopes N.P.
      - name: Gerwick W.H.
      - name: Moore B.S.
      - name: Dorrestein P.C.
      - name: Bandeira N.
      citationCount: 1024
      date: '2016-09-08T00:00:00Z'
      journal: Nature Biotechnology
      title: Sharing and community curation of mass spectrometry data with Global
        Natural Products Social Molecular Networking
    note: null
    pmcid: PMC5321674
    pmid: '27504778'
    type:
    - Primary
    version: null
  relation: []
  toolType:
  - Workbench
  topic:
  - term: Proteomics experiment
    uri: http://edamontology.org/topic_3520
  - term: Metabolomics
    uri: http://edamontology.org/topic_3172
  - term: Lipids
    uri: http://edamontology.org/topic_0153
  - term: Biotechnology
    uri: http://edamontology.org/topic_3297
  - term: Biochemistry
    uri: http://edamontology.org/topic_3292
  validated: 0
  version: []
- accessibility: null
  additionDate: '2021-01-18T10:24:45Z'
  biotoolsCURIE: biotools:gloryx
  biotoolsID: gloryx
  collectionID: []
  confidence_flag: tool
  cost: null
  credit: []
  description: 'Prediction of the Metabolites Resulting from Phase 1 and Phase 2 Biotransformations
    of Xenobiotics.


    New E-Resource for Drug Discovery.


    Regioselectivity prediction for phase 1 and phase 2 metabolism.'
  documentation: []
  download: []
  editPermission:
    authors:
    - recetox-specdatri
    type: group
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Phasing
      uri: http://edamontology.org/operation_3454
    - term: Metabolic pathway prediction
      uri: http://edamontology.org/operation_3929
    - term: PTM site prediction
      uri: http://edamontology.org/operation_0417
    output: []
  homepage: https://nerdd.zbh.uni-hamburg.de/
  homepage_status: 0
  language: []
  lastUpdate: '2025-11-03T16:44:03.823692Z'
  license: null
  link: []
  maturity: null
  name: GLORYx
  operatingSystem: []
  otherID: []
  owner: Niclaskn
  publication:
  - doi: 10.1021/acs.chemrestox.0c00224
    metadata:
      abstract: Predicting the structures of metabolites formed in humans can provide
        advantageous insights for the development of drugs and other compounds. Here
        we present GLORYx, which integrates machine learning-based site of metabolism
        (SoM) prediction with reaction rule sets to predict and rank the structures
        of metabolites that could potentially be formed by phase 1 and/or phase 2
        metabolism. GLORYx extends the approach from our previously developed tool
        GLORY, which predicted metabolite structures for cytochrome P450-mediated
        metabolism only. A robust approach to ranking the predicted metabolites is
        attained by using the SoM probabilities predicted by the FAME 3 machine learning
        models to score the predicted metabolites. On a manually curated test data
        set containing both phase 1 and phase 2 metabolites, GLORYx achieves a recall
        of 77% and an area under the receiver operating characteristic curve (AUC)
        of 0.79. Separate analysis of performance on a large amount of freely available
        phase 1 and phase 2 metabolite data indicates that achieving a meaningful
        ranking of predicted metabolites is more difficult for phase 2 than for phase
        1 metabolites. GLORYx is freely available as a web server at https://nerdd.zbh.uni-hamburg.de/
        and is also provided as a software package upon request. The data sets as
        well as all the reaction rules from this work are also made freely available.
      authors:
      - name: De Bruyn Kops C.
      - name: Sicho M.
      - name: Mazzolari A.
      - name: Kirchmair J.
      citationCount: 69
      date: '2021-02-15T00:00:00Z'
      journal: Chemical Research in Toxicology
      title: 'GLORYx: Prediction of the Metabolites Resulting from Phase 1 and Phase
        2 Biotransformations of Xenobiotics'
    note: null
    pmcid: PMC7887798
    pmid: '32786543'
    type: []
    version: null
  relation: []
  toolType:
  - Database portal
  topic:
  - term: Small molecules
    uri: http://edamontology.org/topic_0154
  - term: Metabolomics
    uri: http://edamontology.org/topic_3172
  - term: Drug discovery
    uri: http://edamontology.org/topic_3336
  - term: Endocrinology and metabolism
    uri: http://edamontology.org/topic_3407
  - term: Proteomics experiment
    uri: http://edamontology.org/topic_3520
  validated: 1
  version: []
- accessibility: Open access
  additionDate: '2019-07-04T14:05:39Z'
  biotoolsCURIE: biotools:CliqueMS
  biotoolsID: CliqueMS
  collectionID: []
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: oriol.senan@urv.cat
    fundrefid: null
    gridid: null
    name: Oriol Senan
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  description: Computational tool for annotating in-source metabolite ions from LC-MS
    untargeted metabolomics data based on a coelution similarity network.
  documentation:
  - note: Tutorial material
    type:
    - Training material
    url: https://github.com/osenan/cliqueMS/blob/master/vignettes/annotate_features.Rmd
  download:
  - note: null
    type: Source code
    url: https://cran.r-project.org/src/contrib/Archive/cliqueMS/
    version: null
  editPermission:
    authors:
    - recetox-specdatri
    type: group
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Read binning
      uri: http://edamontology.org/operation_3798
    - term: Natural product identification
      uri: http://edamontology.org/operation_3803
    output: []
  homepage: https://github.com/osenan/cliqueMS
  homepage_status: 0
  language:
  - R
  - C++
  lastUpdate: '2025-11-03T16:44:03.166147Z'
  license: GPL-3.0
  link:
  - note: null
    type:
    - Issue tracker
    url: https://github.com/osenan/cliqueMS/issues
  maturity: Mature
  name: CliqueMS
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: Ruta
  publication:
  - doi: 10.1093/bioinformatics/btz207
    metadata:
      abstract: 'The analysis of biological samples in untargeted metabolomic studies
        using LC-MS yields tens of thousands of ion signals. Annotating these features
        is of the utmost importance for answering questions as fundamental as, e.g.
        how many metabolites are there in a given sample.Results: Here, we introduce
        CliqueMS, a new algorithm for annotating in-source LC-MS1 data. CliqueMS is
        based on the similarity between coelution profiles and therefore, as opposed
        to most methods, allows for the annotation of a single spectrum. Furthermore,
        CliqueMS improves upon the state of the art in several dimensions: (i) it
        uses a more discriminatory feature similarity metric; (ii) it treats the similarities
        between features in a transparent way by means of a simple generativemodel;
        (iii) it uses a well-grounded maximum likelihood inference approach to group
        features; (iv) it uses empirical adduct frequencies to identify the parental
        mass and (v) it deals more flexibly with the identification of the parental
        mass by proposing and ranking alternative annotations. We validate our approach
        with simple mixtures of standards and with real complex biological samples.
        CliqueMS reduces the thousands of features typically obtained in complex samples
        to hundreds of metabolites, and it is able to correctly annotate more metabolites
        and adducts from a single spectrum than available tools.'
      authors:
      - name: Senan O.
      - name: Aguilar-Mogas A.
      - name: Navarro M.
      - name: Capellades J.
      - name: Noon L.
      - name: Burks D.
      - name: Yanes O.
      - name: Guimera R.
      - name: Sales-Pardo M.
      citationCount: 48
      date: '2019-10-15T00:00:00Z'
      journal: Bioinformatics
      title: 'CliqueMS: A computational tool for annotating in-source metabolite ions
        from LC-MS untargeted metabolomics data based on a coelution similarity network'
    note: null
    pmcid: PMC6792096
    pmid: '30903689'
    type:
    - Primary
    version: null
  relation: []
  toolType:
  - Library
  topic:
  - term: Small molecules
    uri: http://edamontology.org/topic_0154
  - term: Metabolomics
    uri: http://edamontology.org/topic_3172
  - term: Proteomics experiment
    uri: http://edamontology.org/topic_3520
  validated: 1
  version:
  - 0.3.2
- accessibility: Open access
  additionDate: '2022-07-06T15:00:55.171504Z'
  biotoolsCURIE: biotools:neatms
  biotoolsID: neatms
  collectionID: []
  confidence_flag: tool
  cost: Free of charge
  credit:
  - email: dieter.beule@bih-charite.de
    fundrefid: null
    gridid: null
    name: Dieter Beule
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Yoann Gloaguen
    note: null
    orcidid: https://orcid.org/0000-0003-0493-8592
    rorid: null
    typeEntity: null
    typeRole: []
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Jennifer A. Kirwan
    note: null
    orcidid: null
    rorid: null
    typeEntity: null
    typeRole: []
    url: null
  description: NeatMS is an open source python package for untargeted LCMS signal
    labelling and filtering. NeatMS enables automated filtering of false positive
    MS peaks reported by commonly used LCMS data processing pipelines. NeatMS relies
    on neural network based classification.
  documentation:
  - note: null
    type:
    - User manual
    url: https://neatms.readthedocs.io/en/latest/
  download: []
  editPermission:
    authors:
    - recetox-specdatri
    type: group
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Peak detection
      uri: http://edamontology.org/operation_3215
    - term: Filtering
      uri: http://edamontology.org/operation_3695
    - term: Network analysis
      uri: http://edamontology.org/operation_3927
    output: []
  homepage: https://anaconda.org/bioconda/neatms
  homepage_status: 0
  language:
  - Python
  lastUpdate: '2025-11-03T16:32:44.163513Z'
  license: MIT
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/bihealth/NeatMS
  maturity: null
  name: NeatMS
  operatingSystem:
  - Mac
  - Linux
  - Windows
  otherID: []
  owner: Jennifer
  publication:
  - doi: 10.1021/ACS.ANALCHEM.1C02220
    metadata:
      abstract: © 2022 American Chemical Society. All rights reserved.Available automated
        methods for peak detection in untargeted metabolomics suffer from poor precision.
        We present NeatMS, which uses machine learning based on a convoluted neural
        network to reduce the number and fraction of false peaks. NeatMS comes with
        a pre-trained model representing expert knowledge in the differentiation of
        true chemical signal from noise. Furthermore, it provides all necessary functions
        to easily train new models or improve existing ones by transfer learning.
        Thus, the tool improves peak curation and contributes to the robust and scalable
        analysis of large-scale experiments. We show how to integrate it into different
        liquid chromatography-mass spectrometry (LC-MS) analysis workflows, quantify
        its performance, and compare it to various other approaches. NeatMS software
        is available as open source on github under permissive MIT license and is
        also provided as easy-to-install PyPi and Bioconda packages.
      authors:
      - name: Gloaguen Y.
      - name: Kirwan J.A.
      - name: Beule D.
      citationCount: 0
      date: '2022-03-29T00:00:00Z'
      journal: Analytical Chemistry
      title: Deep Learning-Assisted Peak Curation for Large-Scale LC-MS Metabolomics
    note: null
    pmcid: PMC8969107
    pmid: '35290737'
    type: []
    version: null
  relation: []
  toolType:
  - Library
  topic:
  - term: Metabolomics
    uri: http://edamontology.org/topic_3172
  - term: Machine learning
    uri: http://edamontology.org/topic_3474
  - term: Workflows
    uri: http://edamontology.org/topic_0769
  - term: Proteomics experiment
    uri: http://edamontology.org/topic_3520
  validated: 1
  version: []
- accessibility: Open access
  additionDate: '2024-01-02T02:11:50.145026Z'
  biotoolsCURIE: biotools:umetaflow
  biotoolsID: umetaflow
  collectionID: []
  confidence_flag: tool
  cost: Free of charge
  credit:
  - email: tiwe@biosustain.dtu.dk
    fundrefid: null
    gridid: null
    name: Tilmann Weber
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  description: Untargeted metabolomics workflow for high-throughput data processing
    and analysis.
  documentation: []
  download: []
  editPermission:
    authors:
    - recetox-specdatri
    type: group
  elixirCommunity: []
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  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Imputation
      uri: http://edamontology.org/operation_3557
    - term: Data handling
      uri: http://edamontology.org/operation_2409
    - term: Deisotoping
      uri: http://edamontology.org/operation_3629
    output: []
  homepage: https://github.com/biosustain/snakemake_UmetaFlow
  homepage_status: 0
  language:
  - Python
  lastUpdate: '2025-11-03T16:16:27.787938Z'
  license: Apache-2.0
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/biosustain/pyOpenMS_UmetaFlow
  maturity: null
  name: UmetaFlow
  operatingSystem:
  - Mac
  - Linux
  - Windows
  otherID: []
  owner: Pub2Tools
  publication:
  - doi: 10.1186/s13321-023-00724-w
    metadata:
      abstract: 'Metabolomics experiments generate highly complex datasets, which
        are time and work-intensive, sometimes even error-prone if inspected manually.
        Therefore, new methods for automated, fast, reproducible, and accurate data
        processing and dereplication are required. Here, we present UmetaFlow, a computational
        workflow for untargeted metabolomics that combines algorithms for data pre-processing,
        spectral matching, molecular formula and structural predictions, and an integration
        to the GNPS workflows Feature-Based Molecular Networking and Ion Identity
        Molecular Networking for downstream analysis. UmetaFlow is implemented as
        a Snakemake workflow, making it easy to use, scalable, and reproducible. For
        more interactive computing, visualization, as well as development, the workflow
        is also implemented in Jupyter notebooks using the Python programming language
        and a set of Python bindings to the OpenMS algorithms (pyOpenMS). Finally,
        UmetaFlow is also offered as a web-based Graphical User Interface for parameter
        optimization and processing of smaller-sized datasets. UmetaFlow was validated
        with in-house LC–MS/MS datasets of actinomycetes producing known secondary
        metabolites, as well as commercial standards, and it detected all expected
        features and accurately annotated 76% of the molecular formulas and 65% of
        the structures. As a more generic validation, the publicly available MTBLS733
        and MTBLS736 datasets were used for benchmarking, and UmetaFlow detected more
        than 90% of all ground truth features and performed exceptionally well in
        quantification and discriminating marker selection. We anticipate that UmetaFlow
        will provide a useful platform for the interpretation of large metabolomics
        datasets. Graphical Abstract: [Figure not available: see fulltext.]'
      authors:
      - name: Kontou E.E.
      - name: Walter A.
      - name: Alka O.
      - name: Pfeuffer J.
      - name: Sachsenberg T.
      - name: Mohite O.S.
      - name: Nuhamunada M.
      - name: Kohlbacher O.
      - name: Weber T.
      citationCount: 7
      date: '2023-12-01T00:00:00Z'
      journal: Journal of Cheminformatics
      title: 'UmetaFlow: an untargeted metabolomics workflow for high-throughput data
        processing and analysis'
    note: null
    pmcid: PMC10176759
    pmid: '37173725'
    type: []
    version: null
  relation: []
  toolType:
  - Workflow
  topic:
  - term: Metabolomics
    uri: http://edamontology.org/topic_3172
  - term: Workflows
    uri: http://edamontology.org/topic_0769
  - term: Proteomics experiment
    uri: http://edamontology.org/topic_3520
  - term: Small molecules
    uri: http://edamontology.org/topic_0154
  validated: 0
  version: []
- accessibility: Open access
  additionDate: '2019-08-09T13:10:29Z'
  biotoolsCURIE: biotools:ThermoRawFileParser
  biotoolsID: ThermoRawFileParser
  collectionID: []
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: compomics.list@gmail.com
    fundrefid: null
    gridid: null
    name: Computational Omics and Systems Biology Group
    note: null
    orcidid: null
    rorid: null
    typeEntity: Division
    typeRole:
    - Primary contact
    url: null
  description: Open-source, crossplatform tool that converts Thermo RAW files into
    open file formats such as MGF and to the HUPO-PSI standard file format mzML
  documentation:
  - note: null
    type:
    - General
    url: https://github.com/compomics/ThermoRawFileParser/blob/master/README.md
  download:
  - note: null
    type: Source code
    url: https://github.com/compomics/ThermoRawFileParser/releases
    version: null
  editPermission:
    authors:
    - veits@bmb.sdu.dk
    - recetox-specdatri
    type: group
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Mass spectrum
        uri: http://edamontology.org/data_0943
      format:
      - term: Thermo RAW
        uri: http://edamontology.org/format_3712
    note: null
    operation:
    - term: Conversion
      uri: http://edamontology.org/operation_3434
    - term: Filtering
      uri: http://edamontology.org/operation_3695
    - term: Peak detection
      uri: http://edamontology.org/operation_3215
    output:
    - data:
        term: Mass spectrum
        uri: http://edamontology.org/data_0943
      format:
      - term: MGF
        uri: http://edamontology.org/format_3651
      - term: mzML
        uri: http://edamontology.org/format_3244
  homepage: https://github.com/compomics/ThermoRawFileParser
  homepage_status: 0
  language:
  - Java
  - C#
  lastUpdate: '2025-11-03T16:16:26.016194Z'
  license: Apache-2.0
  link:
  - note: ThermoRawFileParserGUI
    type:
    - Repository
    url: https://github.com/compomics/ThermoRawFileParserGUI
  maturity: Mature
  name: ThermoRawFileParser
  operatingSystem:
  - Linux
  - Mac
  otherID: []
  owner: hans
  publication:
  - doi: 10.1101/622852
    metadata: null
    note: null
    pmcid: null
    pmid: null
    type:
    - Primary
    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: Metabolomics
    uri: http://edamontology.org/topic_3172
  validated: 1
  version: []
- accessibility: Open access
  additionDate: '2016-10-20T10:31:19Z'
  biotoolsCURIE: biotools:peptideshaker
  biotoolsID: peptideshaker
  collectionID:
  - de.NBI
  - Proteomics
  - BioInfra.Prot
  confidence_flag: null
  cost: null
  credit:
  - email: null
    fundrefid: null
    gridid: null
    name: BioInfra.Prot
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
    - Provider
    url: null
  - email: dominik.kopczynski@isas.de
    fundrefid: null
    gridid: null
    name: Dominik Kopczynsk
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: http://compomics.github.io/projects/peptide-shaker.html
  description: PeptideShaker is a search engine independent platform for interpretation
    of proteomics identification results from multiple search engines, currently supporting
    X!Tandem, MS-GF+, MS Amanda, OMSSA, MyriMatch, Comet, Tide, Mascot, Andromeda
    and mzIdentML. By combining the results from multiple search engines, while re-calculating
    PTM localization scores and redoing the protein inference, PeptideShaker attempts
    to give you the best possible understanding of your proteomics data
  documentation:
  - note: null
    type:
    - General
    url: http://compomics.github.io/projects/peptide-shaker.html#read-me
  download:
  - note: null
    type: Source code
    url: https://github.com/compomics/peptide-shaker
    version: null
  editPermission:
    authors:
    - proteomics.bio.tools
    - veits@bmb.sdu.dk
    type: group
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Protein sequence
        uri: http://edamontology.org/data_2976
      format:
      - term: FASTA
        uri: http://edamontology.org/format_1929
    - data:
        term: Peptide identification
        uri: http://edamontology.org/data_0945
      format:
      - term: mzIdentML
        uri: http://edamontology.org/format_3247
    - data:
        term: Mass spectrometry data
        uri: http://edamontology.org/data_2536
      format:
      - term: MGF
        uri: http://edamontology.org/format_3651
    note: null
    operation:
    - term: Mass spectrum visualisation
      uri: http://edamontology.org/operation_3694
    - term: Peptide identification
      uri: http://edamontology.org/operation_3631
    - term: Validation
      uri: http://edamontology.org/operation_2428
    - term: PTM localisation
      uri: http://edamontology.org/operation_3755
    - term: Enrichment analysis
      uri: http://edamontology.org/operation_3501
    - term: Structure visualisation
      uri: http://edamontology.org/operation_0570
    - term: Protein identification
      uri: http://edamontology.org/operation_3767
    output:
    - data:
        term: Protein structure image
        uri: http://edamontology.org/data_2992
      format:
      - term: JPG
        uri: http://edamontology.org/format_3579
      - term: SVG
        uri: http://edamontology.org/format_3604
    - data:
        term: GO-term enrichment data
        uri: http://edamontology.org/data_3754
      format:
      - term: Textual format
        uri: http://edamontology.org/format_2330
    - data:
        term: Sequence image
        uri: http://edamontology.org/data_2969
      format:
      - term: Image format
        uri: http://edamontology.org/format_3547
    - data:
        term: Protein report
        uri: http://edamontology.org/data_0896
      format:
      - term: TSV
        uri: http://edamontology.org/format_3475
  homepage: http://compomics.github.io/projects/peptide-shaker.html
  homepage_status: 0
  language:
  - Java
  lastUpdate: '2025-11-01T15:59:45.423975Z'
  license: Apache-2.0
  link: []
  maturity: null
  name: PeptideShaker
  operatingSystem:
  - Mac
  - Linux
  otherID: []
  owner: BioInfra.Prot
  publication:
  - doi: 10.1038/nbt.3109
    metadata:
      abstract: ''
      authors: []
      citationCount: 449
      date: '2015-01-01T00:00:00Z'
      journal: Nature Biotechnology
      title: 'PeptideShaker enables reanalysis of MS-derived proteomics data sets:
        To the editor'
    note: null
    pmcid: null
    pmid: '25574629'
    type:
    - Primary
    version: null
  relation: []
  toolType:
  - Desktop application
  - Command-line tool
  topic:
  - term: Proteomics
    uri: http://edamontology.org/topic_0121
  - term: Proteomics experiment
    uri: http://edamontology.org/topic_3520
  - term: Proteome
    uri: http://edamontology.org/topic_0644
  validated: 1
  version:
  - 3.0.11
- accessibility: null
  additionDate: '2020-01-09T17:51:22Z'
  biotoolsCURIE: biotools:PTM-CrossTalkMapper
  biotoolsID: PTM-CrossTalkMapper
  collectionID: []
  confidence_flag: tool
  cost: null
  credit: []
  description: 'Visualization of the Dynamics of Histone Modifications and Their Crosstalk
    Using PTM-CrossTalkMapper.


    R scripts to create crosstalk maps that visualize multi-layered proteoform data.


    PTM-CrossTalkMapper is a flexible toolkit to visualize multi-layered quantitative
    post-transcriptional modification (PTM) data. The preprint manuscript can be found
    on bioRxiv'
  documentation:
  - note: null
    type:
    - General
    url: https://github.com/veitveit/CrossTalkMapper?tab=readme-ov-file#documentation
  - note: null
    type:
    - User manual
    url: https://link.springer.com/protocol/10.1007/978-1-0716-2317-6_13
  download: []
  editPermission:
    authors: []
    type: public
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Quantification
      uri: http://edamontology.org/operation_3799
    - term: Post-translation modification site prediction
      uri: http://edamontology.org/operation_0417
    - term: PTM localisation
      uri: http://edamontology.org/operation_3755
    - term: Visualisation
      uri: http://edamontology.org/operation_0337
    output: []
  homepage: https://github.com/veitveit/CrossTalkMapper
  homepage_status: 0
  language:
  - R
  lastUpdate: '2025-10-27T17:06:26.845284Z'
  license: null
  link: []
  maturity: null
  name: PTM-CrossTalkMapper
  operatingSystem: []
  otherID: []
  owner: Pub2Tools
  publication:
  - doi: 10.1016/j.ymeth.2020.01.012
    metadata:
      abstract: ''
      authors: []
      citationCount: 17
      date: '2020-12-01T00:00:00Z'
      journal: Methods
      title: Visualization of the dynamics of histone modifications and their crosstalk
        using PTM-CrossTalkMapper
    note: null
    pmcid: null
    pmid: null
    type: []
    version: null
  relation: []
  toolType: []
  topic:
  - term: Epigenetics
    uri: http://edamontology.org/topic_3295
  - term: Proteomics
    uri: http://edamontology.org/topic_0121
  - term: Protein modifications
    uri: http://edamontology.org/topic_0601
  - term: Proteomics experiment
    uri: http://edamontology.org/topic_3520
  - term: Gene expression
    uri: http://edamontology.org/topic_0203
  validated: 1
  version: []
- accessibility: Open access
  additionDate: '2023-07-26T14:40:01.768324Z'
  biotoolsCURIE: biotools:ms_annika
  biotoolsID: ms_annika
  collectionID: []
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: viktoria.dorfer@fh-hagenberg.at
    fundrefid: null
    gridid: null
    name: Viktoria Dorfer
    note: null
    orcidid: https://orcid.org/0000-0002-5332-5701
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: http://bioinformatics.fh-hagenberg.at/
  - email: micha.birklbauer@fh-hagenberg.at
    fundrefid: null
    gridid: null
    name: Micha Birklbauer
    note: null
    orcidid: https://orcid.org/0009-0005-1051-179X
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: http://bioinformatics.fh-hagenberg.at/
  description: MS Annika is a crosslink search engine based on MS Amanda, aimed at
    identifying crosslinks of cleavable and non-cleavable crosslinkers from MS2 and
    MS3 spectra. It can deal with a wide variety of cross-linkers and provides robust
    and transparent FDR control based on a target-decoy approach. MS Annika is available
    free of charge as a plug-in for Proteome Discoverer.
  documentation:
  - note: null
    type:
    - General
    url: https://hgb-bin-proteomics.github.io/MSAnnika/
  - note: null
    type:
    - User manual
    url: https://github.com/hgb-bin-proteomics/MSAnnika/raw/master/MS_Annika_3.0_UserManual.pdf
  - note: Detailed tutorial how to use MS Annika
    type:
    - Training material
    url: https://github.com/hgb-bin-proteomics/MSAnnika/raw/master/tutorial/MS_Annika_3.0_Tutorial.pdf
  - note: Detailed tutorial how to use MS Annika
    type:
    - Training material
    url: https://www.youtube.com/watch?v=L1lVt35PYv4
  download:
  - note: Latest MS Annika version for Proteome Disoverer 3.2
    type: Software package
    url: https://github.com/hgb-bin-proteomics/MSAnnika/raw/master/releases/latest/PD3.2/latest.zip
    version: PD3.2:latest
  - note: Latest MS Annika version for Proteome Disoverer 3.1
    type: Software package
    url: https://github.com/hgb-bin-proteomics/MSAnnika/raw/master/releases/latest/PD3.1/latest.zip
    version: PD3.1:latest
  - note: Latest MS Annika version for Proteome Disoverer 3.0
    type: Software package
    url: https://github.com/hgb-bin-proteomics/MSAnnika/raw/master/releases/latest/PD3.0/latest.zip
    version: PD3.0:latest
  - note: Latest MS Annika version for Proteome Disoverer 2.5
    type: Software package
    url: https://github.com/hgb-bin-proteomics/MSAnnika/raw/master/releases/latest/PD2.5/latest.zip
    version: PD2.5:latest
  editPermission:
    authors: []
    type: private
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Mass spectrum
        uri: http://edamontology.org/data_0943
      format:
      - term: MGF
        uri: http://edamontology.org/format_3651
      - term: Thermo RAW
        uri: http://edamontology.org/format_3712
    - data:
        term: Protein sequence record
        uri: http://edamontology.org/data_2886
      format:
      - term: FASTA
        uri: http://edamontology.org/format_1929
    note: null
    operation:
    - term: Peptide identification
      uri: http://edamontology.org/operation_3631
    - term: Peptide database search
      uri: http://edamontology.org/operation_3646
    - term: PTM localisation
      uri: http://edamontology.org/operation_3755
    - term: PTM identification
      uri: http://edamontology.org/operation_3645
    - term: Target-Decoy
      uri: http://edamontology.org/operation_3649
    output:
    - data:
        term: Sequence search results
        uri: http://edamontology.org/data_0857
      format:
      - term: Textual format
        uri: http://edamontology.org/format_2330
  homepage: https://github.com/hgb-bin-proteomics/MSAnnika
  homepage_status: 0
  language:
  - C#
  lastUpdate: '2025-10-26T02:38:48.643054Z'
  license: Freeware
  link:
  - note: MS Annika version archive
    type:
    - Repository
    url: https://github.com/hgb-bin-proteomics/MSAnnika
  maturity: Mature
  name: MS Annika
  operatingSystem:
  - Windows
  otherID: []
  owner: michabirklbauer
  publication:
  - doi: 10.1021/acs.jproteome.0c01000
    metadata:
      abstract: ''
      authors: []
      citationCount: 22
      date: '2021-05-07T00:00:00Z'
      journal: Journal of Proteome Research
      title: 'MS Annika: A New Cross-Linking Search Engine'
    note: MS Annika for cleavable crosslink identification from MS2 spectra
    pmcid: PMC8155564
    pmid: '33852321'
    type:
    - Primary
    version: '1.0'
  - doi: 10.1021/acs.jproteome.3c00325
    metadata:
      abstract: ''
      authors: []
      citationCount: 5
      date: '2023-09-01T00:00:00Z'
      journal: Journal of Proteome Research
      title: MS Annika 2.0 Identifies Cross-Linked Peptides in MS2-MS3-Based Workflows
        at High Sensitivity and Specificity
    note: MS Annika 2.0 for cleavable crosslink identification from MS3 spectra
    pmcid: PMC10476269
    pmid: '37566781'
    type:
    - Primary
    version: '2.0'
  - doi: 10.1038/s42004-024-01386-x
    metadata:
      abstract: ''
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  biotoolsID: macpepdb_-_mass_centric_peptide_database
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  - email: null
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    name: Julian Uszkoreit
    note: null
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    rorid: null
    typeEntity: null
    typeRole: []
    url: null
  - email: dirk.winkelhardt@rub.de
    fundrefid: null
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    name: Dirk Winkelhardt
    note: null
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    rorid: null
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    url: null
  - email: null
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    name: PD Dr. Martin Eisenacher
    note: null
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    url: null
  description: A Database to Quickly Access All Tryptic Peptides of the UniProtKB
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    - API documentation
    url: https://docs.rs/macpepdb/latest/macpepdb/web/index.html
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  - JavaScript
  - Other
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  license: null
  link:
  - note: Backend implementation written in Rust / Axum
    type:
    - Repository
    url: https://github.com/medbioinf/macpepdb
  - note: Frontend implementation written in Rust / Dioxus
    type:
    - Repository
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  maturity: Mature
  name: MaCPepDB - Mass Centric Peptide Database
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  owner: di_hardt
  publication:
  - 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'
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    - Primary
    version: '1.0'
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  - term: Proteomics
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  validated: 0
  version:
  - 3.0.0
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  additionDate: '2019-11-27T10:47:08Z'
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  description: Quercus robur annotation database
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    input:
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    note: null
    operation:
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    - term: Visualisation
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    - term: Gene-set enrichment analysis
      uri: http://edamontology.org/operation_2436
    - term: Query and retrieval
      uri: http://edamontology.org/operation_0224
    output:
    - data:
        term: Over-representation data
        uri: http://edamontology.org/data_3753
      format: []
    - data:
        term: Query script
        uri: http://edamontology.org/data_3786
      format: []
    - data:
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        uri: http://edamontology.org/data_1255
      format: []
  homepage: https://urgi.versailles.inra.fr/OakMine_PM1N
  homepage_status: 0
  language:
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  - Ruby
  - Java
  - Python
  - JavaScript
  - Perl
  lastUpdate: '2025-07-29T13:42:35.424110Z'
  license: LGPL-2.1
  link:
  - note: null
    type:
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    url: https://registry.intermine.org
  - note: null
    type:
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    url: http://intermine.org
  maturity: Mature
  name: OakMine
  operatingSystem:
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  otherID: []
  owner: InterMine
  publication:
  - doi: 10.1093/bioinformatics/bts577
    metadata:
      abstract: InterMine is an open-source data warehouse system that facilitates
        the building of databases with complex data integration requirements and a
        need for a fast customizable query facility. Using InterMine, large biological
        databases can be created from a range of heterogeneous data sources, and the
        extensible data model allows for easy integration of new data types. The analysis
        tools include a flexible query builder, genomic region search and a library
        of 'widgets' performing various statistical analyses. The results can be exported
        in many commonly used formats. InterMine is a fully extensible framework where
        developers can add new tools and functionality. Additionally, there is a comprehensive
        set of web services, for which client libraries are provided in five commonly
        used programming languages. © The Author 2012. Published by Oxford University
        Press. All rights reserved.
      authors:
      - name: Smith R.N.
      - name: Aleksic J.
      - name: Butano D.
      - name: Carr A.
      - name: Contrino S.
      - name: Hu F.
      - name: Lyne M.
      - name: Lyne R.
      - name: Kalderimis A.
      - name: Rutherford K.
      - name: Stepan R.
      - name: Sullivan J.
      - name: Wakeling M.
      - name: Watkins X.
      - name: Micklem G.
      citationCount: 202
      date: '2012-12-01T00:00:00Z'
      journal: Bioinformatics
      title: 'InterMine: A flexible data warehouse system for the integration and
        analysis of heterogeneous biological data'
    note: null
    pmcid: PMC3516146
    pmid: '23023984'
    type:
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    version: null
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  toolType:
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  - Web service
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  topic:
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  - term: Genomics
    uri: http://edamontology.org/topic_0622
  - term: Proteomics
    uri: http://edamontology.org/topic_0121
  validated: 1
  version:
  - '2.3'
- accessibility: null
  additionDate: '2019-11-27T10:47:40Z'
  biotoolsCURIE: biotools:WheatMine
  biotoolsID: WheatMine
  collectionID: []
  confidence_flag: null
  cost: Free of charge
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  description: Wheat IWGSC RefSeq v1.0
  documentation:
  - note: null
    type:
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    operation:
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    - term: Query and retrieval
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      format: []
    - data:
        term: Sequence features
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      format: []
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  homepage_status: 0
  language:
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  - Ruby
  - Java
  - Python
  - JavaScript
  - Perl
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  - note: null
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    url: https://registry.intermine.org
  - note: null
    type:
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    url: http://intermine.org
  maturity: Mature
  name: WheatMine
  operatingSystem:
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  otherID: []
  owner: InterMine
  publication:
  - doi: 10.1093/bioinformatics/bts577
    metadata:
      abstract: InterMine is an open-source data warehouse system that facilitates
        the building of databases with complex data integration requirements and a
        need for a fast customizable query facility. Using InterMine, large biological
        databases can be created from a range of heterogeneous data sources, and the
        extensible data model allows for easy integration of new data types. The analysis
        tools include a flexible query builder, genomic region search and a library
        of 'widgets' performing various statistical analyses. The results can be exported
        in many commonly used formats. InterMine is a fully extensible framework where
        developers can add new tools and functionality. Additionally, there is a comprehensive
        set of web services, for which client libraries are provided in five commonly
        used programming languages. © The Author 2012. Published by Oxford University
        Press. All rights reserved.
      authors:
      - name: Smith R.N.
      - name: Aleksic J.
      - name: Butano D.
      - name: Carr A.
      - name: Contrino S.
      - name: Hu F.
      - name: Lyne M.
      - name: Lyne R.
      - name: Kalderimis A.
      - name: Rutherford K.
      - name: Stepan R.
      - name: Sullivan J.
      - name: Wakeling M.
      - name: Watkins X.
      - name: Micklem G.
      citationCount: 202
      date: '2012-12-01T00:00:00Z'
      journal: Bioinformatics
      title: 'InterMine: A flexible data warehouse system for the integration and
        analysis of heterogeneous biological data'
    note: null
    pmcid: PMC3516146
    pmid: '23023984'
    type:
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    version: null
  relation: []
  toolType:
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  - Database portal
  topic:
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    uri: http://edamontology.org/topic_3071
  - term: Genomics
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  - term: Proteomics
    uri: http://edamontology.org/topic_0121
  validated: 1
  version: []
- accessibility: null
  additionDate: '2024-03-13T15:03:34.764536Z'
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  description: QFeatures is a Bioconductor package that provides infrastructure to
    management and process quantitative features for high-throughput mass spectrometry
    assays. It provides a familiar Bioconductor user experience to manage quantitative
    data across different assay levels (such as precursors, peptide spectrum matches,
    peptides and proteins or protein groups) in a coherent and tractable format.
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    type:
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  license: Artistic-2.0
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  maturity: null
  name: qfeatures
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  owner: pavanvidem
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  toolType:
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  topic:
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    uri: http://edamontology.org/topic_0078
  - term: Bioinformatics
    uri: http://edamontology.org/topic_0091
  - term: Proteomics
    uri: http://edamontology.org/topic_0121
  - term: Proteomics experiment
    uri: http://edamontology.org/topic_3520
  validated: 0
  version: []
- accessibility: null
  additionDate: '2017-01-17T14:50:32Z'
  biotoolsCURIE: biotools:pyteomics
  biotoolsID: pyteomics
  collectionID:
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  confidence_flag: null
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  credit:
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    name: Pyteomics Google Groups
    note: null
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    typeEntity: Person
    typeRole:
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    url: null
  - email: null
    fundrefid: null
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    name: Issue tracker
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    rorid: null
    typeEntity: Person
    typeRole:
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    url: https://github.com/levitsky/pyteomics/issues
  description: Framework for proteomics data analysis, supporting mzML, MGF, pepXML
    and more.
  documentation:
  - note: null
    type:
    - User manual
    url: https://pyteomics.readthedocs.io/
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    type: Software package
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  function:
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    input:
    - data:
        term: Data
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      - term: mzML
        uri: http://edamontology.org/format_3244
      - term: mzXML
        uri: http://edamontology.org/format_3654
    note: null
    operation:
    - term: Protein identification
      uri: http://edamontology.org/operation_3767
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  homepage: https://pyteomics.readthedocs.io/
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  license: Apache-2.0
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  name: Pyteomics
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  owner: msutils_import
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    metadata:
      abstract: 'Pyteomics is a cross-platform, open-source Python library providing
        a rich set of tools for MS-based proteomics. It provides modules for reading
        LC-MS/MS data, search engine output, protein sequence databases, theoretical
        prediction of retention times, electrochemical properties of polypeptides,
        mass and m/z calculations, and sequence parsing. Pyteomics is available under
        Apache license; release versions are available at the Python Package Index
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        is available at http://packages.python.org/pyteomics.biolccc/. Questions on
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        [Figure not available: see fulltext.] © 2013 American Society for Mass Spectrometry.'
      authors:
      - name: Goloborodko A.A.
      - name: Levitsky L.I.
      - name: Ivanov M.V.
      - name: Gorshkov M.V.
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      journal: Journal of the American Society for Mass Spectrometry
      title: Pyteomics - A python framework for exploratory data analysis and rapid
        software prototyping in proteomics
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  - doi: 10.1021/acs.jproteome.8b00717
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      abstract: Many of the novel ideas that drive today's proteomic technologies
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        and programs, to projects built using general-purpose or specialized workflow
        engines; a large part of routine data processing is performed manually or
        with custom scripts that remain unpublished. Facilitating the development
        of reproducible data-processing workflows becomes essential for increasing
        the efficiency of proteomic research. To assist in overcoming the bioinformatics
        challenges in the daily practice of proteomic laboratories, 5 years ago we
        developed and announced Pyteomics, a freely available open-source library
        providing Python interfaces to proteomic data. We summarize the new functionality
        of Pyteomics developed during the time since its introduction.
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      - name: Klein J.A.
      - name: Ivanov M.V.
      - name: Gorshkov M.V.
      citationCount: 117
      date: '2019-02-01T00:00:00Z'
      journal: Journal of Proteome Research
      title: 'Pyteomics 4.0: Five Years of Development of a Python Proteomics Framework'
    note: null
    pmcid: null
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    type:
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    version: null
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  toolType:
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  topic:
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  - term: Proteomics experiment
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  biotoolsCURIE: biotools:OmicsQ
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  description: OmicsQ is a Shiny-based web application designed for preprocessing
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    for subsequent analysis using specialized tools such as PolySTest for statistical
    testing and VSClust for clustering analysis.
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  - note: null
    type:
    - User manual
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    output:
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      format:
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        uri: http://edamontology.org/format_3752
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    - data:
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    metadata: null
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  topic:
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