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  description: SAMtools and BCFtools are widely used programs for processing and analysing
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  language:
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  license: MIT
  link:
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    type:
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  maturity: Mature
  name: SAMtools
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      journal: Bioinformatics
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      journal: GigaScience
      title: Twelve years of SAMtools and BCFtools
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    type:
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    version: null
  - doi: 10.1093/bioinformatics/btr509
    metadata:
      abstract: ''
      authors: []
      citationCount: 4643
      date: '2011-11-01T00:00:00Z'
      journal: Bioinformatics
      title: A statistical framework for SNP calling, mutation discovery, association
        mapping and population genetical parameter estimation from sequencing data
    note: null
    pmcid: PMC3198575
    pmid: '21903627'
    type: []
    version: null
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  topic:
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    uri: http://edamontology.org/topic_0080
  - term: Sequencing
    uri: http://edamontology.org/topic_3168
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  validated: 1
  version:
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  description: The main purpose of HTSlib is to provide access to genomic information
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- accessibility: Open access
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  biotoolsCURIE: biotools:bcftools
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  description: BCFtools is a set of utilities that manipulate variant calls in the
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  documentation:
  - note: null
    type:
    - General
    url: http://www.htslib.org/doc/bcftools.html
  - note: A workflow for BCFtools.
    type:
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  language:
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  license: MIT
  link:
  - note: null
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  validated: 1
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  biotoolsCURIE: biotools:thaf
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    gridid: null
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    note: Verdanta is an early startup in Switzerland, providing curated RNASeq pipeline.
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    orcidid: https://orcid.org/0009-0006-1714-3691
    rorid: null
    typeEntity: Person
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  - note: README provides enough information to use the tool
    type:
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  download:
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    type: Other
    url: https://crates.io/crates/thaf
    version: 0.0.4
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    - data:
        term: DNA sequence
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    note: Produce transcriptome file from genomic DNA and gff3
    operation:
    - term: Sequence coordinate conversion
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    output:
    - data:
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  link:
  - note: Crates.io page providing installation instructions and README.
    type:
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  - note: Source code. Also, use GitHub issue tracker to send bug reports and extension
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    type:
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  maturity: Emerging
  name: thaf
  operatingSystem:
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  - Linux
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  otherID: []
  owner: Bourumir
  publication: []
  relation: []
  toolType:
  - Command-line tool
  topic:
  - term: Transcriptomics
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  - term: Bioinformatics
    uri: http://edamontology.org/topic_0091
  - term: RNA-Seq
    uri: http://edamontology.org/topic_3170
  validated: 0
  version:
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- accessibility: Open access
  additionDate: '2019-02-13T17:01:40Z'
  biotoolsCURIE: biotools:Jalview
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    gridid: null
    name: Jim Procter
    note: null
    orcidid: https://orcid.org/0000-0002-7865-7382
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  - email: null
    fundrefid: null
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    name: Geoff Barton
    note: null
    orcidid: https://orcid.org/0000-0002-9014-5355
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  description: Jalview is a free cross-platform program for multiple sequence alignment
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  documentation:
  - note: null
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  - note: Hands-on exercises, Training courses and Training videos
    type:
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  - note: null
    type:
    - FAQ
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  - note: null
    type:
    - User manual
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  - note: null
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    version: null
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    type: Source code
    url: https://www.jalview.org/download/source/
    version: null
  - note: Binaries for all platforms
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    version: null
  - note: null
    type: Icon
    url: https://www.jalview.org/favicon.svg
    version: null
  - note: Executable JAR file
    type: Binaries
    url: https://www.jalview.org/download/other/jar/
    version: null
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        uri: http://edamontology.org/format_1929
      - term: FASTA-aln
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      - term: Pileup
        uri: http://edamontology.org/format_3015
      - term: GFF2-seq
        uri: http://edamontology.org/format_1938
      - term: BLC
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      - term: Format
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      - term: PHYLIP format
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      - term: VCF
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      - term: Stockholm format
        uri: http://edamontology.org/format_1961
      - term: GFF3-seq
        uri: http://edamontology.org/format_1939
      - term: GCG MSF
        uri: http://edamontology.org/format_1947
    - data:
        term: Structure alignment
        uri: http://edamontology.org/data_0886
      format:
      - term: PDB
        uri: http://edamontology.org/format_1476
    note: 'Other Input formats:

      AMSA (.amsa);

      JnetFile (.concise, .jnet);

      PFAM (.pfam);

      Substitution matrix (.matrix);

      Jalview Project File (.jvp);

      Jalview Feature File (.features, .jvfeatures);

      Jalview Annotations File (.annotations, .jvannotations);

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

      ...

      Other Output formats:

      PFAM (.pfam);

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

      Jalview Project File (.jvp);'
    operation:
    - term: Sequence alignment editing
      uri: http://edamontology.org/operation_3081
    - term: Phylogenetic tree analysis
      uri: http://edamontology.org/operation_0324
    - term: Sequence visualisation
      uri: http://edamontology.org/operation_0564
    output:
    - data:
        term: Sequence alignment
        uri: http://edamontology.org/data_0863
      format:
      - term: nbrf/pir
        uri: http://edamontology.org/format_1948
      - term: FASTA
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      - term: Pileup
        uri: http://edamontology.org/format_3015
      - term: BLC
        uri: http://edamontology.org/format_3313
      - term: BioJSON (Jalview)
        uri: http://edamontology.org/format_3774
      - term: ClustalW format
        uri: http://edamontology.org/format_1982
      - term: JSON
        uri: http://edamontology.org/format_3464
      - term: PHYLIP format
        uri: http://edamontology.org/format_1997
      - term: Stockholm format
        uri: http://edamontology.org/format_1961
      - term: GCG MSF
        uri: http://edamontology.org/format_1947
    - data:
        term: Plot
        uri: http://edamontology.org/data_2884
      format:
      - term: EPS
        uri: http://edamontology.org/format_3466
      - term: Format
        uri: http://edamontology.org/format_1915
      - term: HTML
        uri: http://edamontology.org/format_2331
      - term: SVG
        uri: http://edamontology.org/format_3604
      - term: PNG
        uri: http://edamontology.org/format_3603
  homepage: https://www.jalview.org/
  homepage_status: 0
  language: []
  lastUpdate: '2025-12-11T14:16:30.074724Z'
  license: GPL-3.0
  link:
  - note: null
    type:
    - Discussion forum
    url: https://discourse.jalview.org/
  - note: null
    type:
    - Issue tracker
    url: https://issues.jalview.org/
  - note: Latest development version
    type:
    - Other
    url: https://www.jalview.org/development/jalview_develop/
  - note: null
    type:
    - Repository
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  - note: Twitter feed
    type:
    - Social media
    url: https://twitter.com/Jalview
  - note: YouTube training videos
    type:
    - Social media
    url: https://www.youtube.com/channel/UCIjpnvZB770yz7ftbrJ0tfw
  - note: null
    type:
    - Social media
    url: https://www.linkedin.com/company/104771886/
  maturity: Mature
  name: Jalview
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  - Linux
  - Windows
  otherID: []
  owner: ben_s
  publication:
  - doi: 10.1093/bioinformatics/btp033
    metadata:
      abstract: ''
      authors: []
      citationCount: 7717
      date: '2009-05-07T00:00:00Z'
      journal: Bioinformatics
      title: Jalview Version 2-A multiple sequence alignment editor and analysis workbench
    note: null
    pmcid: PMC2672624
    pmid: '19151095'
    type: []
    version: null
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  toolType:
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  topic:
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    uri: http://edamontology.org/topic_0080
  - term: Data visualisation
    uri: http://edamontology.org/topic_0092
  validated: 1
  version:
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- accessibility: null
  additionDate: '2024-12-21T15:24:55.662209Z'
  biotoolsCURIE: biotools:stripepy
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  description: StripePy recognizes architectural stripes in 3C and Hi-C contact maps
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  - note: null
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  toolType:
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  topic:
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- accessibility: Open access (with restrictions)
  additionDate: '2025-12-09T09:22:22.735091Z'
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  biotoolsID: instanovo
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  confidence_flag: null
  cost: Free of charge (with restrictions)
  credit:
  - email: k.eloff@instadeep.com
    fundrefid: null
    gridid: null
    name: Kevin Eloff
    note: null
    orcidid: https://orcid.org/0000-0003-1355-8743
    rorid: null
    typeEntity: null
    typeRole:
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    url: null
  - email: konka@dtu.dk
    fundrefid: null
    gridid: null
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    note: null
    orcidid: https://orcid.org/0000-0003-3907-9281
    rorid: null
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    typeRole:
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    url: null
  - email: r.catzel@instadeep.com
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    note: null
    orcidid: https://orcid.org/0000-0002-2983-9833
    rorid: null
    typeEntity: null
    typeRole:
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    url: null
  - email: j.vangoey@instadeep.com
    fundrefid: null
    gridid: null
    name: Jeroen Van Goey
    note: null
    orcidid: https://orcid.org/0000-0003-4480-5567
    rorid: null
    typeEntity: null
    typeRole:
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    url: null
  - email: tpaje@dtu.dk
    fundrefid: null
    gridid: null
    name: Timothy P. Jenkins
    note: null
    orcidid: https://orcid.org/0000-0003-2979-5663
    rorid: null
    typeEntity: null
    typeRole:
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    url: null
  description: InstaNovo is a transformer neural network with the ability to translate
    fragment ion peaks into the sequence of amino acids that make up the studied peptide(s).
  documentation:
  - note: null
    type:
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    url: https://instadeepai.github.io/InstaNovo/
  - note: null
    type:
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    url: https://instadeepai.github.io/InstaNovo/tutorials/getting_started/#installation
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    type:
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    url: https://instadeepai.github.io/InstaNovo/tutorials/getting_started/
  - note: null
    type:
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    url: https://instadeepai.github.io/InstaNovo/reference/cli/
  - note: null
    type:
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    url: https://instadeepai.github.io/InstaNovo/API/summary/
  - note: null
    type:
    - Citation instructions
    url: https://instadeepai.github.io/InstaNovo/citation/
  download:
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  editPermission:
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  elixir_badge: 0
  function:
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        term: Mass spectrum
        uri: http://edamontology.org/data_0943
      format:
      - term: mzML
        uri: http://edamontology.org/format_3244
      - term: mzXML
        uri: http://edamontology.org/format_3654
      - term: MGF
        uri: http://edamontology.org/format_3651
    note: null
    operation:
    - term: de Novo sequencing
      uri: http://edamontology.org/operation_3644
    output:
    - data:
        term: Protein sequence record
        uri: http://edamontology.org/data_2886
      format:
      - term: CSV
        uri: http://edamontology.org/format_3752
  homepage: https://github.com/instadeepai/instanovo
  homepage_status: 0
  language:
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  lastUpdate: '2025-12-09T21:41:17.117080Z'
  license: Apache-2.0
  link:
  - note: null
    type:
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    url: https://github.com/instadeepai/instanovo
  - note: null
    type:
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  - note: null
    type:
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  - note: null
    type:
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  maturity: Mature
  name: InstaNovo
  operatingSystem:
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  - Mac
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  otherID: []
  owner: BioGeek
  publication:
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    metadata:
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      authors: []
      citationCount: 7
      date: '2025-04-01T00:00:00Z'
      journal: Nature Machine Intelligence
      title: InstaNovo enables diffusion-powered de novo peptide sequencing in large-scale
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    note: null
    pmcid: null
    pmid: null
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  relation:
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  topic:
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  - term: Proteins
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  - term: Proteomics experiment
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  - term: Machine learning
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  validated: 0
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- accessibility: null
  additionDate: '2024-04-18T08:31:46.459964Z'
  biotoolsCURIE: biotools:hictkpy
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  description: 'Python bindings for hictk: read and write .cool and .hic files directly
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  documentation:
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    note: null
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  toolType:
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  - term: Sequence analysis
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  validated: 0
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  additionDate: '2017-08-03T18:45:53Z'
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  description: "HBAT (Hydrogen Bond Analysis Tool) is a package to automate the analysis\
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    \ continue to be available via SourceForge. \n\nHBAT 2.0 was introduced in 2025\
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    version: 2.x
  - note: Mac and Linux Binaries including  AppImage, .deb, standalone executables.
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    version: 2.x
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      format:
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        uri: http://edamontology.org/format_1476
    note: null
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      format: []
  homepage: https://hbat.abhishek-tiwari.com
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  language:
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  lastUpdate: '2025-11-29T17:30:01.186940Z'
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    type:
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  owner: abhishektiwari
  publication:
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    metadata: null
    note: Peer-reviewed paper for HBAT 1.0
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  relation: []
  toolType:
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  topic:
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  validated: 1
  version:
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- accessibility: Open access
  additionDate: '2025-11-28T17:29:53.564906Z'
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    name: RECETOX SpecDatRI
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    url: https://www.recetox.muni.cz/en/services/data-services-2/spectrometric-data-processing-and-analysis
  description: 'This package performs in-silico MeOX + TMS derivatization (as described
    e.g. in https://doi.org/10.1021/acs.analchem.7b01010):


    Methoximation: ketone R(C=O)R'' and aldehyde (-HC=O) carbonyl groups are substituted
    with -C=NOCH3

    Trimethylsilylation: the acidic hydrogen in -OH, -SH, -COOH, -NH2, -NHR, =NH,
    the hydrogen is substituted with -Si(CH3)3 The substitution doesn''t always have
    to happen; its probability is currently hardcoded in the package. Typically, multiple
    substitution attempts are run on each input molecule, and all distinct results
    are gathered.

    Known limitation is methoximation on cycles which should be broken. This is not
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    - Command-line options
    url: https://github.com/RECETOX/gc-meox-tms/blob/master/README.md
  - note: null
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    - Training material
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  function:
  - cmd: add_derivatization_groups()
    input:
    - data:
        term: SMILES string
        uri: http://edamontology.org/data_2301
      format: []
    note: Produces MeOX/TMS derivatives of given compounds
    operation:
    - term: Sequence editing
      uri: http://edamontology.org/operation_0231
    output:
    - data:
        term: SMILES string
        uri: http://edamontology.org/data_2301
      format: []
  homepage: https://github.com/RECETOX/gc-meox-tms
  homepage_status: 0
  language:
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  lastUpdate: '2025-11-28T17:42:43.031944Z'
  license: MIT
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  maturity: Mature
  name: gc-meox-tms
  operatingSystem: []
  otherID: []
  owner: Ondrej_Bucek
  publication:
  - doi: 10.1021/acs.analchem.7b01010
    metadata:
      abstract: ''
      authors: []
      citationCount: 44
      date: '2017-06-20T00:00:00Z'
      journal: Analytical Chemistry
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    note: null
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    note: null
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  license: MIT
  link:
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    metadata:
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      authors: []
      citationCount: 2439
      date: '2017-11-01T00:00:00Z'
      journal: Nature Biotechnology
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    note: null
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    type: []
    version: null
  - doi: 10.1101/079681
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  - doi: 10.1038/s41467-018-04964-5
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      citationCount: 577
      date: '2018-12-01T00:00:00Z'
      journal: Nature Communications
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    note: null
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  - doi: 10.1093/bioinformatics/bty1057
    metadata:
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    pmid: null
    type: []
    version: null
  - doi: 10.1093/bioinformatics/btab184
    metadata:
      abstract: ''
      authors: []
      citationCount: 162
      date: '2021-09-15T00:00:00Z'
      journal: Bioinformatics
      title: Fast and sensitive taxonomic assignment to metagenomic contigs
    note: MMseqs2 Taxonomy
    pmcid: PMC8479651
    pmid: '33734313'
    type: []
    version: null
  - doi: 10.1101/2024.11.13.623350v1
    metadata: null
    note: MMseqs2-GPU preprint
    pmcid: null
    pmid: null
    type: []
    version: null
  - doi: 10.1038/s41592-025-02819-8
    metadata:
      abstract: ''
      authors: []
      citationCount: 0
      date: '2025-10-01T00:00:00Z'
      journal: Nature Methods
      title: GPU-accelerated homology search with MMseqs2
    note: MMseqs2-GPU
    pmcid: null
    pmid: null
    type: []
    version: null
  relation:
  - biotoolsID: mmseqs
    type: isNewVersionOf
  - biotoolsID: plass
    type: usedBy
  - biotoolsID: linclust
    type: includes
  - biotoolsID: metaeuk
    type: usedBy
  - biotoolsID: conterminator
    type: usedBy
  - biotoolsID: spacepharer
    type: usedBy
  toolType:
  - Command-line tool
  topic:
  - term: Metagenomics
    uri: http://edamontology.org/topic_3174
  - term: Sequence analysis
    uri: http://edamontology.org/topic_0080
  - term: Proteins
    uri: http://edamontology.org/topic_0078
  - term: Nucleic acids
    uri: http://edamontology.org/topic_0077
  - term: Gene and protein families
    uri: http://edamontology.org/topic_0623
  - term: Taxonomy
    uri: http://edamontology.org/topic_0637
  validated: 1
  version: []
- accessibility: null
  additionDate: '2025-11-10T08:25:02.385560Z'
  biotoolsCURIE: biotools:folddisco
  biotoolsID: folddisco
  collectionID: []
  confidence_flag: null
  cost: Free of charge
  credit: []
  description: Folddisco enables rapid detection of discontinuous or segment 3D motifs
    in large protein databses.
  documentation: []
  download: []
  editPermission:
    authors: []
    type: private
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function: []
  homepage: https://github.com/steineggerlab/folddisco
  homepage_status: 0
  language:
  - Rust
  lastUpdate: '2025-11-10T08:25:02.388051Z'
  license: GPL-3.0
  link:
  - note: null
    type:
    - Issue tracker
    url: https://github.com/steineggerlab/folddisco/issues
  - note: null
    type:
    - Service
    url: https://search.foldseek.com/folddisco
  maturity: Emerging
  name: Folddisco
  operatingSystem:
  - Linux
  - Mac
  otherID: []
  owner: milot-mirdita
  publication:
  - doi: 10.1101/2025.07.06.663357v1
    metadata: null
    note: null
    pmcid: null
    pmid: null
    type: []
    version: null
  relation: []
  toolType:
  - Command-line tool
  - Web application
  topic:
  - term: Protein sites, features and motifs
    uri: http://edamontology.org/topic_3510
  - term: Protein structural motifs and surfaces
    uri: http://edamontology.org/topic_0166
  validated: 0
  version: []
- accessibility: Open access
  additionDate: '2025-02-28T15:04:33.594183Z'
  biotoolsCURIE: biotools:prolfquapp
  biotoolsID: prolfquapp
  collectionID: []
  confidence_flag: null
  cost: Free of charge
  credit: []
  description: A command-line tool for differential expression analysis in quantitative
    proteomics
  documentation:
  - note: null
    type:
    - General
    url: https://github.com/prolfqua/prolfquapp/blob/master/README.md
  download:
  - note: null
    type: Downloads page
    url: https://github.com/prolfqua/prolfquapp/releases/tag/0.1.6
    version: 0.1.6
  editPermission:
    authors:
    - thatmariia
    type: group
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: './prolfqua_dea.sh -i data_dir/ -d annotation.xlsx -y config.yaml -w NameOfAnalysis
      -s DIANN

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

      # ./prolfquapp_docker.sh prolfqua_dea.sh -i data_dir/ -d annotation.xlsx -y
      config.yaml -w NameOfAnalysis -s DIANN'
    input:
    - data:
        term: Expression data
        uri: http://edamontology.org/data_2603
      format:
      - term: CSV
        uri: http://edamontology.org/format_3752
      - term: TSV
        uri: http://edamontology.org/format_3475
    - data:
        term: Sequence
        uri: http://edamontology.org/data_2044
      format:
      - term: FASTA
        uri: http://edamontology.org/format_1929
    note: null
    operation:
    - term: Differential protein expression profiling
      uri: http://edamontology.org/operation_3741
    output:
    - data:
        term: Expression data
        uri: http://edamontology.org/data_2603
      format:
      - term: xlsx
        uri: http://edamontology.org/format_3620
      - term: HTML
        uri: http://edamontology.org/format_2331
  - cmd: null
    input:
    - data:
        term: Expression data
        uri: http://edamontology.org/data_2603
      format:
      - term: xlsx
        uri: http://edamontology.org/format_3620
    note: null
    operation:
    - term: Validation
      uri: http://edamontology.org/operation_2428
    output:
    - data:
        term: Quality control report
        uri: http://edamontology.org/data_3914
      format:
      - term: HTML
        uri: http://edamontology.org/format_2331
  - cmd: null
    input:
    - data:
        term: Expression data
        uri: http://edamontology.org/data_2603
      format:
      - term: CSV
        uri: http://edamontology.org/format_3752
      - term: TSV
        uri: http://edamontology.org/format_3475
    - data:
        term: Protein sequence
        uri: http://edamontology.org/data_2976
      format:
      - term: FASTA
        uri: http://edamontology.org/format_1929
    note: null
    operation:
    - term: Expression data visualisation
      uri: http://edamontology.org/operation_0571
    output:
    - data:
        term: Expression data
        uri: http://edamontology.org/data_2603
      format:
      - term: HTML
        uri: http://edamontology.org/format_2331
      - term: PDF
        uri: http://edamontology.org/format_3508
  homepage: https://github.com/prolfqua/prolfquapp
  homepage_status: 0
  language:
  - R
  lastUpdate: '2025-11-06T14:37:12.116175Z'
  license: MIT
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/prolfqua/prolfquapp
  - note: null
    type:
    - Issue tracker
    url: https://github.com/prolfqua/prolfquapp/issues
  maturity: Emerging
  name: prolfquapp
  operatingSystem:
  - Mac
  - Linux
  otherID: []
  owner: n.m.palmblad@lumc.nl
  publication:
  - doi: 10.1021/acs.jproteome.4c00911
    metadata:
      abstract: ''
      authors: []
      citationCount: 1
      date: '2025-02-07T00:00:00Z'
      journal: Journal of Proteome Research
      title: prolfquapp ─ A User-Friendly Command-Line Tool Simplifying Differential
        Expression Analysis in Quantitative Proteomics
    note: null
    pmcid: null
    pmid: null
    type:
    - Primary
    version: 0.0.6
  relation: []
  toolType:
  - Command-line tool
  topic:
  - term: Proteomics
    uri: http://edamontology.org/topic_0121
  validated: 0
  version:
  - 0.1.6
- accessibility: Open access
  additionDate: '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:
    authors:
    - recetox-specdatri
    type: group
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  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: '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: '2019-08-26T14:34:55Z'
  biotoolsCURIE: biotools:MINERVA_Platform
  biotoolsID: MINERVA_Platform
  collectionID:
  - LCSB
  - ELIXIR-LU
  confidence_flag: null
  cost: Free of charge
  credit: []
  description: 'The MINERVA (Molecular Interaction NEtwoRk VisuAlization) platform
    is a standalone webserver for visualization, exploration and management of molecular
    networks encoded in SBGN-compliant format, including files produced using CellDesigner
    or SBGN editors. Visualization of uploaded networks generated by the platform
    is accessible via a web browser to all viewers with the weblink to the resource.


    The MINERVA Platform is a webservice using the Java Server Faces 2 technology.
    The server side, including data parsing, integration, annotation and verification,
    is implemented in Java. The platform uses the Postgres SQL database for data storage
    and the Hibernate framework as a middle layer between web server and database.
    The user web-interface is generated using React.js. The displayed content is visualized
    by OpenLayers API, dedicated JavaScript and CSS.'
  documentation:
  - note: null
    type:
    - Quick start guide
    - Release notes
    - User manual
    - API documentation
    - Citation instructions
    - Terms of use
    url: https://minerva.uni.lu
  download:
  - note: Installation instructions, including debian package, virtual machine images
      and docker containers.
    type: Other
    url: https://minerva.pages.uni.lu/doc/install/
    version: 13.1.3 - 18.1.1
  editPermission:
    authors:
    - sascha.herzinger
    type: group
  elixirCommunity: []
  elixirNode:
  - Luxembourg
  elixirPlatform:
  - Tools
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: Visualise systems biology diagrams online, on a standalone web server
    operation:
    - term: Pathway visualisation
      uri: http://edamontology.org/operation_3926
    output: []
  - cmd: null
    input: []
    note: Visualise omics data from multiple datasets on top of the diagrams
    operation:
    - term: Expression data visualisation
      uri: http://edamontology.org/operation_0571
    output: []
  - cmd: null
    input: []
    note: 'Convert between main systems biology layout formats: CellDeslgners SBML,
      SBML layout+render, SBGN-ML, GPML'
    operation:
    - term: Conversion
      uri: http://edamontology.org/operation_3434
    output: []
  - cmd: null
    input: []
    note: Use MINERVA API to access systems biology formats for modelling
    operation:
    - term: Modelling and simulation
      uri: http://edamontology.org/operation_2426
    output: []
  homepage: https://minerva.uni.lu
  homepage_status: 0
  language: []
  lastUpdate: '2025-10-29T08:54:40.647322Z'
  license: AGPL-3.0
  link:
  - note: GiLab repository for core functionalities (data and format handling, service
      stability, API access)
    type:
    - Repository
    url: https://gitlab.lcsb.uni.lu/minerva/core/
  - note: Issue tracker for core functionalities (data and format handling, service
      stability, API access)
    type:
    - Issue tracker
    url: https://gitlab.lcsb.uni.lu/minerva/core/-/issues
  - note: GiLab repository for frontend functionalities
    type:
    - Repository
    url: https://gitlab.lcsb.uni.lu/minerva/frontend
  - note: Issue tracker for frontend functionalities
    type:
    - Issue tracker
    url: https://gitlab.lcsb.uni.lu/minerva/frontend/-/issues
  maturity: Mature
  name: The MINERVA Platform
  operatingSystem: []
  otherID: []
  owner: mjostaszewski
  publication:
  - doi: 10.1038/npjsba.2016.20
    metadata:
      abstract: ''
      authors: []
      citationCount: 71
      date: '2016-01-01T00:00:00Z'
      journal: npj Systems Biology and Applications
      title: MINERVA—A platform for visualization and curation of molecular interaction
        networks
    note: null
    pmcid: PMC5516855
    pmid: '28725475'
    type:
    - Primary
    version: '10.0'
  - doi: 10.1093/bioinformatics/btz286
    metadata:
      abstract: ''
      authors: []
      citationCount: 26
      date: '2019-11-01T00:00:00Z'
      journal: Bioinformatics
      title: 'MINERVA API and plugins: Opening molecular network analysis and visualization
        to the community'
    note: null
    pmcid: PMC6821317
    pmid: '31074494'
    type:
    - Primary
    version: 12.2.3
  - doi: 10.1093/bib/bbz067
    metadata:
      abstract: ''
      authors: []
      citationCount: 18
      date: '2019-07-10T00:00:00Z'
      journal: Briefings in Bioinformatics
      title: Closing the gap between formats for storing layout information in systems
        biology
    note: null
    pmcid: PMC7373180
    pmid: '31273380'
    type:
    - Primary
    version: 13.1.1
  - doi: 10.1089/big.2015.0057
    metadata:
      abstract: ''
      authors: []
      citationCount: 40
      date: '2016-06-01T00:00:00Z'
      journal: Big Data
      title: Integration and Visualization of Translational Medicine Data for Better
        Understanding of Human Diseases
    note: null
    pmcid: PMC4932659
    pmid: '27441714'
    type:
    - Usage
    version: '10.0'
  - doi: 10.1016/j.envpol.2019.04.005
    metadata:
      abstract: ''
      authors: []
      citationCount: 5
      date: '2019-07-01T00:00:00Z'
      journal: Environmental Pollution
      title: Genes associated with Parkinson's disease respond to increasing polychlorinated
        biphenyl levels in the blood of healthy females
    note: null
    pmcid: null
    pmid: '30991279'
    type: []
    version: 13.1.1
  relation:
  - biotoolsID: pathvisio
    type: uses
  - biotoolsID: sbgn
    type: uses
  - biotoolsID: libsbml
    type: uses
  toolType: []
  topic:
  - term: Molecular interactions, pathways and networks
    uri: http://edamontology.org/topic_0602
  - term: Omics
    uri: http://edamontology.org/topic_3391
  - term: Translational medicine
    uri: http://edamontology.org/topic_3342
  - term: Systems biology
    uri: http://edamontology.org/topic_2259
  validated: 0
  version:
  - 13.1.3
  - 13.2.0
  - 14.0.13
  - 15.0.3
  - 16.4.0
  - 17.1.3
  - 18.1.1
  - 19.1.0
- accessibility: Open access
  additionDate: '2024-03-07T20:51:08.529472Z'
  biotoolsCURIE: biotools:oncoanalyser
  biotoolsID: oncoanalyser
  collectionID: []
  confidence_flag: tool
  cost: Free of charge
  credit: []
  description: Oncoanalyser is an nf-core Nextflow implementation of the tools developed
    by Hartwig Medical Foundation. The workflow is designed to comprehensively detect
    all variant types (SNV. MNV, InDel, SV, CNV, Fusions, Viral insertions, Telomere
    length, Genetic Immune Escape, mutational processes) as well as key tumor characteristics
    (purity, ploidy, TMB, MSI) from data derived from different short read platforms.
    The tooling is optimised for paired whole genome samples (90x tumor, 30x normal)
    but can be run on exome or panel (targeted) data. There is support for GRCh37
    and GRCh38 human reference genome builds.
  documentation: []
  download: []
  editPermission:
    authors:
    - jdeligt
    - VKasalica
    type: group
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function: []
  homepage: https://github.com/nf-core/oncoanalyser/tree/dev
  homepage_status: 0
  language:
  - Java
  lastUpdate: '2025-10-09T07:39:49.943872Z'
  license: GPL-3.0
  link:
  - note: GitHub page for issue tracking of Nextflow workflow implementation
    type:
    - Issue tracker
    - Repository
    url: https://github.com/nf-core/oncoanalyser/tree/dev
  - note: GitHub repository of underlying tools with issue tracking
    type:
    - Repository
    - Issue tracker
    url: https://github.com/hartwigmedical/hmftools
  maturity: Mature
  name: oncoanalyser
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: jdeligt
  publication: []
  relation: []
  toolType:
  - Workflow
  topic:
  - term: Oncology
    uri: http://edamontology.org/topic_2640
  - term: Whole genome sequencing
    uri: http://edamontology.org/topic_3673
  - term: RNA-Seq
    uri: http://edamontology.org/topic_3170
  validated: 0
  version:
  - '5.34'
- accessibility: null
  additionDate: '2021-11-01T10:50:55.880296Z'
  biotoolsCURIE: biotools:pastaq
  biotoolsID: pastaq
  collectionID: []
  confidence_flag: tool
  cost: null
  credit:
  - email: p.l.horvatovich@rug.nl
    fundrefid: null
    gridid: null
    name: Peter Horvatovich
    note: null
    orcidid: https://orcid.org/0000-0003-2218-1140
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
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  description: GFFx is a Rust-based toolkit for ultra-fast and scalable genome annotation
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  maturity: Mature
  name: XNATpy
  operatingSystem:
  - Windows
  - Linux
  - Mac
  otherID: []
  owner: hachterberg
  publication: []
  relation:
  - biotoolsID: xnat-pic
    type: usedBy
  - biotoolsID: xnat
    type: uses
  toolType:
  - Library
  topic:
  - term: Data management
    uri: http://edamontology.org/topic_3071
  - term: FAIR data
    uri: http://edamontology.org/topic_4012
  - term: Medical imaging
    uri: http://edamontology.org/topic_3384
  validated: 0
  version: []
- accessibility: null
  additionDate: '2025-07-10T12:32:00.838316Z'
  biotoolsCURIE: biotools:inmoose
  biotoolsID: inmoose
  collectionID: []
  confidence_flag: null
  cost: null
  credit:
  - email: null
    fundrefid: null
    gridid: null
    name: Maximilien Colange
    note: null
    orcidid: https://orcid.org/0000-0003-4769-3302
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Epigene Labs
    note: null
    orcidid: null
    rorid: null
    typeEntity: null
    typeRole: []
    url: https://www.epigenelabs.com/
  description: InMoose, the INtegrated Multi-Omic Open-Source environment, ports to
    Python state-of-the-art R tools for the analysis of transcriptomic data.
  documentation:
  - note: null
    type:
    - General
    url: https://inmoose.readthedocs.io/en/stable/
  - note: null
    type:
    - Quick start guide
    url: https://colab.research.google.com/drive/1bzmNDZeaw1A6tSgfx61O6PFtaQDve6SV?usp=sharing
  download: []
  editPermission:
    authors: []
    type: private
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  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Count matrix
        uri: http://edamontology.org/data_3917
      format: []
    note: null
    operation:
    - term: Differential gene expression profiling
      uri: http://edamontology.org/operation_3223
    output: []
  homepage: https://github.com/epigenelabs/inmoose
  homepage_status: 0
  language:
  - Python
  lastUpdate: '2025-07-10T13:00:37.310588Z'
  license: GPL-3.0
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/epigenelabs/inmoose
  - note: null
    type:
    - Issue tracker
    url: https://github.com/epigenelabs/inmoose/issues
  maturity: Mature
  name: InMoose
  operatingSystem:
  - Mac
  - Linux
  - Windows
  otherID: []
  owner: maximilien.colange
  publication:
  - doi: 10.1038/s41598-025-03376-y
    metadata:
      abstract: We introduce InMoose, an open-source Python environment aimed at omic
        data analysis. We illustrate its capabilities for bulk transcriptomic data
        analysis. Due to its wide adoption, Python has grown as a de facto standard
        in fields increasingly important for bioinformatic pipelines, such as data
        science, machine learning, or artificial intelligence (AI). As a general-purpose
        language, Python is also recognized for its versatility and scalability. InMoose
        aims at bringing state-of-the-art tools, historically written in R, to the
        Python ecosystem. InMoose focuses on providing drop-in replacements for R
        tools, to ensure consistency and reproducibility between R-based and Python-based
        pipelines. The first development phase has focused on bulk transcriptomic
        data, with current capabilities encompassing data simulation, batch effect
        correction, and differential analysis and meta-analysis.
      authors:
      - name: Colange M.
      - name: Appe G.
      - name: Meunier L.
      - name: Weill S.
      - name: Johnson W.E.
      - name: Nordor A.
      - name: Behdenna A.
      citationCount: 1
      date: '2025-12-01T00:00:00Z'
      journal: Scientific Reports
      title: Bridging the gap between R and Python in bulk transcriptomic data analysis
        with InMoose
    note: null
    pmcid: null
    pmid: null
    type:
    - Primary
    - Usage
    version: null
  - doi: 10.1186/s12859-023-05578-5
    metadata:
      abstract: 'Background: Variability in datasets is not only the product of biological
        processes: they are also the product of technical biases. ComBat and ComBat-Seq
        are among the most widely used tools for correcting those technical biases,
        called batch effects, in, respectively, microarray and RNA-Seq expression
        data. Results: In this technical note, we present a new Python implementation
        of ComBat and ComBat-Seq. While the mathematical framework is strictly the
        same, we show here that our implementations: (i) have similar results in terms
        of batch effects correction; (ii) are as fast or faster than the original
        implementations in R and; (iii) offer new tools for the bioinformatics community
        to participate in its development. pyComBat is implemented in the Python language
        and is distributed under GPL-3.0 (https://www.gnu.org/licenses/gpl-3.0.en.html)
        license as a module of the inmoose package. Source code is available at https://github.com/epigenelabs/inmoose
        and Python package at https://pypi.org/project/inmoose . Conclusions: We present
        a new Python implementation of state-of-the-art tools ComBat and ComBat-Seq
        for the correction of batch effects in microarray and RNA-Seq data. This new
        implementation, based on the same mathematical frameworks as ComBat and ComBat-Seq,
        offers similar power for batch effect correction, at reduced computational
        cost.'
      authors:
      - name: Behdenna A.
      - name: Colange M.
      - name: Haziza J.
      - name: Gema A.
      - name: Appe G.
      - name: Azencott C.-A.
      - name: Nordor A.
      citationCount: 30
      date: '2023-12-01T00:00:00Z'
      journal: BMC Bioinformatics
      title: pyComBat, a Python tool for batch effects correction in high-throughput
        molecular data using empirical Bayes methods
    note: null
    pmcid: null
    pmid: null
    type:
    - Benchmarking study
    - Method
    version: null
  - doi: 10.1186/s12859-025-06180-7
    metadata:
      abstract: 'Background: Differential gene expression analysis is a prominent
        technique for the analysis of biomolecular data to identify genetic features
        associated with phenotypes. Limma—for microarray data –, and edgeR and DESeq2—for
        RNA-Seq data–, are the most widely used tools for differential gene expression
        analysis of bulk transcriptomic data. Results: We present the differential
        expression features of InMoose, a Python implementation of R tools limma,
        edgeR, and DESeq2. We experimentally show that InMoose stands as a drop-in
        replacement for those tools, with nearly identical results. This ensures reproducibility
        when interfacing both languages in bioinformatic pipelines. InMoose is an
        open source software released under the GPL3 license, available at www.github.com/epigenelabs/inmoose
        and https://inmoose.readthedocs.io. Conclusions: We present a new Python implementation
        of state-of-the-art tools limma, edgeR, and DESeq2, to perform differential
        gene expression analysis of bulk transcriptomic data. This new implementation
        exhibits results nearly identical to the original tools, improving interoperability
        and reproducibility between Python and R bioinformatics pipelines.'
      authors:
      - name: Colange M.
      - name: Appe G.
      - name: Meunier L.
      - name: Weill S.
      - name: Nordor A.
      - name: Behdenna A.
      citationCount: 0
      date: '2025-12-01T00:00:00Z'
      journal: BMC Bioinformatics
      title: Differential expression analysis with inmoose, the integrated multi-omic
        open-source environment in Python
    note: null
    pmcid: null
    pmid: null
    type:
    - Benchmarking study
    - Method
    version: null
  relation:
  - biotoolsID: deseq2
    type: isNewVersionOf
  - biotoolsID: limma
    type: isNewVersionOf
  - biotoolsID: edger
    type: isNewVersionOf
  toolType:
  - Library
  topic: []
  validated: 0
  version:
  - 0.8.0
- accessibility: Open access (with restrictions)
  additionDate: '2025-07-10T03:21:50.923918Z'
  biotoolsCURIE: biotools:colopola_dataset_for_colorectal_cancer_detection
  biotoolsID: colopola_dataset_for_colorectal_cancer_detection
  collectionID:
  - Dataset
  confidence_flag: null
  cost: Free of charge (with restrictions)
  credit: []
  description: The dataset consists of 572 slices (specimens) with 20,592 images.
    There are 284 cancer samples and 288 normal samples. The lists of samples for
    training (train+val) set and testing set are provided in the Zenodo repository.
    Source code in Github is to train and validate five deep learning models using
    ColoPola dataset.
  documentation: []
  download:
  - note: Python language
    type: Source code
    url: https://github.com/haile493/Colorectal-cancer-detection-using-ColoPola-dataset
    version: '1.0'
  - note: Dataset for running source code
    type: Test data
    url: https://zenodo.org/records/10554304
    version: '1.2'
  editPermission:
    authors: []
    type: private
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function: []
  homepage: https://github.com/haile493/Colorectal-cancer-detection-using-ColoPola-dataset
  homepage_status: 0
  language:
  - Python
  lastUpdate: '2025-07-10T03:33:52.616431Z'
  license: CC0-1.0
  link:
  - note: Source code
    type:
    - Repository
    url: https://github.com/haile493/Colorectal-cancer-detection-using-ColoPola-dataset
  - note: null
    type:
    - Issue tracker
    url: https://github.com/haile493/Colorectal-cancer-detection-using-ColoPola-dataset/issues
  maturity: Mature
  name: ColoPola dataset for colorectal cancer detection
  operatingSystem:
  - Windows
  otherID: []
  owner: haile
  publication: []
  relation: []
  toolType:
  - Script
  topic:
  - term: Computer science
    uri: http://edamontology.org/topic_3316
  validated: 0
  version:
  - '1.0'
- accessibility: Open access
  additionDate: '2017-01-17T15:07:47Z'
  biotoolsCURIE: biotools:copasi
  biotoolsID: copasi
  collectionID:
  - de.NBI
  - EBI Training Tools
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: null
    fundrefid: null
    gridid: null
    name: null
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: http://copasi.org/About/Team/
  - email: frank.bergmann@bioquant.uni-heidelberg.de
    fundrefid: null
    gridid: null
    name: Frank T. Bergmann
    note: null
    orcidid: https://orcid.org/0000-0001-5553-4702
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  description: Open-source software application for creating and solving mathematical
    models of biological processes such as metabolic networks, cell-signaling pathways,
    regulatory networks, infectious diseases, and many others. It includes features
    to define models of biological processes, simulate and analyze these models, generate
    analysis reports, and import/export models in SBML format.
  documentation:
  - note: null
    type:
    - User manual
    url: http://copasi.org/Support/User_Manual/
  download:
  - note: Source and binary packages are available for download.
    type: Binaries
    url: http://copasi.org/Download/
    version: null
  editPermission:
    authors: []
    type: private
  elixirCommunity: []
  elixirNode:
  - Germany
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Pathway or network
        uri: http://edamontology.org/data_2600
      format:
      - term: SBML
        uri: http://edamontology.org/format_2585
      - term: CopasiML
        uri: http://edamontology.org/format_3239
      - term: SED-ML
        uri: http://edamontology.org/format_3685
      - term: COMBINE OMEX
        uri: http://edamontology.org/format_3686
    note: null
    operation:
    - term: Network simulation
      uri: http://edamontology.org/operation_3562
    - term: Modelling and simulation
      uri: http://edamontology.org/operation_2426
    - term: Metabolic network modelling
      uri: http://edamontology.org/operation_3660
    - term: Pathway visualisation
      uri: http://edamontology.org/operation_3926
    output:
    - data:
        term: Pathway or network
        uri: http://edamontology.org/data_2600
      format:
      - term: SBML
        uri: http://edamontology.org/format_2585
      - term: CopasiML
        uri: http://edamontology.org/format_3239
      - term: SED-ML
        uri: http://edamontology.org/format_3685
      - term: COMBINE OMEX
        uri: http://edamontology.org/format_3686
  homepage: http://copasi.org/
  homepage_status: 0
  language:
  - C++
  lastUpdate: '2025-07-07T11:17:37.638447Z'
  license: Artistic-2.0
  link:
  - note: User Forum
    type:
    - Discussion forum
    url: https://groups.google.com/g/copasi-user-forum
  - note: Issue tracker
    type:
    - Issue tracker
    url: http://tracker.copasi.org/
  - note: Github Repo
    type:
    - Repository
    url: https://github.com/copasi/COPASI
  - note: null
    type:
    - Social media
    url: https://fosstodon.org/@copasi
  maturity: Mature
  name: COPASI
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: frankbergmann
  publication:
  - doi: 10.1093/bioinformatics/btl485
    metadata:
      abstract: 'Motivation: Simulation and modeling is becoming a standard approach
        to understand complex biochemical processes. Therefore, there is a big need
        for software tools that allow access to diverse simulation and modeling methods
        as well as support for the usage of these methods. Results: Here, we present
        COPASI, a platform-independent and user-friendly biochemical simulator that
        offers several unique features. We discuss numerical issues with these features;
        in particular, the criteria to switch between stochastic and deterministic
        simulation methods, hybrid deterministic-stochastic methods, and the importance
        of random number generator numerical resolution in stochastic simulation.
        © 2006 Oxford University Press.'
      authors:
      - name: Hoops S.
      - name: Gauges R.
      - name: Lee C.
      - name: Pahle J.
      - name: Simus N.
      - name: Singhal M.
      - name: Xu L.
      - name: Mendes P.
      - name: Kummer U.
      citationCount: 2004
      date: '2006-12-15T00:00:00Z'
      journal: Bioinformatics
      title: COPASI - A COmplex PAthway SImulator
    note: null
    pmcid: null
    pmid: '17032683'
    type: []
    version: null
  - doi: 10.1007/978-1-59745-525-1_2
    metadata:
      abstract: Computational modeling and simulation of biochemical networks is at
        the core of systems biology and this includes many types of analyses that
        can aid understanding of how these systems work. COPASI is a generic software
        package for modeling and simulation of biochemical networks which provides
        many of these analyses in convenient ways that do not require the user to
        program or to have deep knowledge of the numerical algorithms. Here we provide
        a description of how these modeling techniques can be applied to biochemical
        models using COPASI. The focus is both on practical aspects of software usage
        as well as on the utility of these analyses in aiding biological understanding.
        Practical examples are described for steady-state and time-course simulations,
        stoichiometric analyses, parameter scanning, sensitivity analysis (including
        metabolic control analysis), global optimization, parameter estimation, and
        stochastic simulation. The examples used are all published models that are
        available in the BioModels database in SBML format. © 2009 Humana Press.
      authors:
      - name: Mendes P.
      - name: Hoops S.
      - name: Sahle S.
      - name: Gauges R.
      - name: Dada J.
      - name: Kummer U.
      citationCount: 171
      date: '2009-12-01T00:00:00Z'
      journal: Methods in Molecular Biology
      title: Computational modeling of biochemical networks using COPASI
    note: null
    pmcid: null
    pmid: '19399433'
    type: []
    version: null
  - doi: 10.1016/j.jbiotec.2017.06.1200
    metadata:
      abstract: COPASI is software used for the creation, modification, simulation
        and computational analysis of kinetic models in various fields. It is open-source,
        available for all major platforms and provides a user-friendly graphical user
        interface, but is also controllable via the command line and scripting languages.
        These are likely reasons for its wide acceptance. We begin this review with
        a short introduction describing the general approaches and techniques used
        in computational modeling in the biosciences. Next we introduce the COPASI
        package, and its capabilities, before looking at typical applications of COPASI
        in biotechnology.
      authors:
      - name: Bergmann F.T.
      - name: Hoops S.
      - name: Klahn B.
      - name: Kummer U.
      - name: Mendes P.
      - name: Pahle J.
      - name: Sahle S.
      citationCount: 81
      date: '2017-11-10T00:00:00Z'
      journal: Journal of Biotechnology
      title: COPASI and its applications in biotechnology
    note: null
    pmcid: PMC5623632
    pmid: '28655634'
    type: []
    version: null
  relation:
  - biotoolsID: corc
    type: usedBy
  - biotoolsID: pycotools
    type: usedBy
  - biotoolsID: biosimulations
    type: includedIn
  - biotoolsID: sbmlwebapp
    type: usedBy
  - biotoolsID: libsbml
    type: uses
  toolType:
  - Command-line tool
  - Library
  - Desktop application
  topic:
  - term: Systems biology
    uri: http://edamontology.org/topic_2259
  validated: 1
  version: []
- accessibility: Open access
  additionDate: '2019-11-14T18:08:10Z'
  biotoolsCURIE: biotools:purge_dups
  biotoolsID: purge_dups
  collectionID:
  - ONTeater
  confidence_flag: tool
  cost: Free of charge
  credit:
  - email: null
    fundrefid: null
    gridid: null
    name: Dengfeng Guan
    note: null
    orcidid: https://orcid.org/0000-0002-6376-3940
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: https://www.chatlink.com.cn
  description: 'Identifying and removing haplotypic duplication in primary genome
    assemblies | haplotypic duplication identification tool | scripts/pd_config.py:
    script to generate a configuration file used by run_purge_dups.py | purge haplotigs
    and overlaps in an assembly based on read depth | Given a primary assembly pri_asm
    and an alternative assembly hap_asm (optional, if you have one), follow the steps
    shown below to build your own purge_dups pipeline, steps with same number can
    be run simultaneously. Among all the steps, although step 4 is optional, we highly
    recommend our users to do so, because assemblers may produce overrepresented seqeuences.
    In such a case, The final step 4 can be applied to remove those seqeuences'
  documentation: []
  download: []
  editPermission:
    authors: []
    type: public
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Sequence set (nucleic acid)
        uri: http://edamontology.org/data_1234
      format:
      - term: FASTQ
        uri: http://edamontology.org/format_1930
    - data:
        term: Sequence set (nucleic acid)
        uri: http://edamontology.org/data_1234
      format:
      - term: FASTA
        uri: http://edamontology.org/format_1929
    note: null
    operation:
    - term: Genome assembly
      uri: http://edamontology.org/operation_0525
    - term: Read binning
      uri: http://edamontology.org/operation_3798
    - term: Scaffolding
      uri: http://edamontology.org/operation_3216
    output:
    - data:
        term: Sequence set (nucleic acid)
        uri: http://edamontology.org/data_1234
      format:
      - term: FASTA
        uri: http://edamontology.org/format_1929
  homepage: https://github.com/dfguan/purge_dups
  homepage_status: 0
  language:
  - Python
  - C
  lastUpdate: '2025-06-30T15:34:51.626796Z'
  license: MIT
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/dfguan/purge_dups
  - note: null
    type:
    - Issue tracker
    url: https://github.com/dfguan/purge_dups/issues
  maturity: null
  name: purge_dups
  operatingSystem:
  - Mac
  - Linux
  otherID: []
  owner: Pub2Tools
  publication:
  - doi: 10.1101/729962
    metadata: null
    note: null
    pmcid: null
    pmid: null
    type: []
    version: null
  relation: []
  toolType: []
  topic:
  - term: Sequence assembly
    uri: http://edamontology.org/topic_0196
  validated: 1
  version:
  - v.1.2.6
- accessibility: Open access
  additionDate: '2024-03-18T14:51:49.667412Z'
  biotoolsCURIE: biotools:compleasm
  biotoolsID: compleasm
  collectionID:
  - ONTeater
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: neng@ds.dfci.harvard.edu
    fundrefid: null
    gridid: null
    name: Neng Huang
    note: null
    orcidid: https://orcid.org/0000-0001-7187-0749
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: null
  description: 'Compleasm: a faster and more accurate reimplementation of BUSCO.

    It provides measures for quantitative assessment of genome assembly, gene set,
    and transcriptome completeness based on evolutionarily informed expectations of
    gene content from near-universal single-copy orthologs.'
  documentation:
  - note: null
    type:
    - General
    url: https://github.com/huangnengCSU/compleasm/blob/0.2.6/README.md
  download: []
  editPermission:
    authors: []
    type: public
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: compleasm run -l "$lineage" -a assembly.fa -o output_prefix
    input:
    - data:
        term: Sequence set (nucleic acid)
        uri: http://edamontology.org/data_1234
      format:
      - term: FASTA-like
        uri: http://edamontology.org/format_2546
    note: Runs compleasm using the BUSCO set corresponding to the lineage given.
    operation:
    - term: Sequence assembly validation
      uri: http://edamontology.org/operation_3180
    output:
    - data:
        term: Sequence report
        uri: http://edamontology.org/data_2955
      format: []
  homepage: https://github.com/huangnengCSU/compleasm
  homepage_status: 0
  language:
  - Python
  lastUpdate: '2025-06-30T15:30:41.266812Z'
  license: Apache-2.0
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/huangnengCSU/compleasm
  - note: null
    type:
    - Issue tracker
    url: https://github.com/huangnengCSU/compleasm/issues
  - note: List of accepted lineages (taxonomic groups with curated BUSCO sets)
    type:
    - Other
    url: https://busco.ezlab.org/list_of_lineages.html
  maturity: Mature
  name: Compleasm
  operatingSystem: []
  otherID: []
  owner: rlibouban
  publication:
  - doi: 10.1093/bioinformatics/btad595
    metadata:
      abstract: 'Motivation: Evaluating the gene completeness is critical to measuring
        the quality of a genome assembly. An incomplete assembly can lead to errors
        in gene predictions, annotation, and other downstream analyses. Benchmarking
        Universal Single-Copy Orthologs (BUSCO) is a widely used tool for assessing
        the completeness of genome assembly by testing the presence of a set of single-copy
        orthologs conserved across a wide range of taxa. However, BUSCO is slow particularly
        for large genome assemblies. It is cumbersome to apply BUSCO to a large number
        of assemblies. Results: Here, we present compleasm, an efficient tool for
        assessing the completeness of genome assemblies. Compleasm utilizes the miniprot
        protein-to-genome aligner and the conserved orthologous genes from BUSCO.
        It is 14 times faster than BUSCO for human assemblies and reports a more accurate
        completeness of 99.6% than BUSCO''s 95.7%, which is in close agreement with
        the annotation completeness of 99.5% for T2T-CHM13.'
      authors:
      - name: Huang N.
      - name: Li H.
      citationCount: 95
      date: '2023-10-01T00:00:00Z'
      journal: Bioinformatics
      title: 'compleasm: a faster and more accurate reimplementation of BUSCO'
    note: null
    pmcid: null
    pmid: null
    type: []
    version: null
  relation:
  - biotoolsID: busco
    type: isNewVersionOf
  toolType:
  - Command-line tool
  topic:
  - term: Sequence assembly
    uri: http://edamontology.org/topic_0196
  - term: Genomics
    uri: http://edamontology.org/topic_0622
  - term: Transcriptomics
    uri: http://edamontology.org/topic_3308
  - term: Sequence analysis
    uri: http://edamontology.org/topic_0080
  validated: 0
  version:
  - v.0.2.5
- accessibility: Open access (with restrictions)
  additionDate: '2021-07-06T20:27:27Z'
  biotoolsCURIE: biotools:nanoplot
  biotoolsID: nanoplot
  collectionID:
  - ONTeater
  confidence_flag: null
  cost: Free of charge (with restrictions)
  credit:
  - email: null
    fundrefid: null
    gridid: null
    name: Wouter De Coster
    note: null
    orcidid: https://orcid.org/0000-0002-5248-8197
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: https://gigabaseorgigabyte.wordpress.com/
  description: NanoPlot is a tool with various visualizations of sequencing data in
    bam, cram, fastq, fasta or platform-specific TSV summaries, mainly intended for
    long-read sequencing from Oxford Nanopore Technologies and Pacific Biosciences
  documentation:
  - note: null
    type:
    - Command-line options
    url: https://github.com/wdecoster/NanoPlot
  download:
  - note: null
    type: Command-line specification
    url: https://anaconda.org/bioconda/nanoplot
    version: null
  - note: null
    type: Command-line specification
    url: https://pypi.org/project/NanoPlot/
    version: null
  editPermission:
    authors: []
    type: public
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: DNA sequence
        uri: http://edamontology.org/data_3494
      format:
      - term: FASTA-like
        uri: http://edamontology.org/format_2546
      - term: nucleotide
        uri: http://edamontology.org/format_1207
    note: null
    operation:
    - term: Scatter plot plotting
      uri: http://edamontology.org/operation_2940
    - term: Box-Whisker plot plotting
      uri: http://edamontology.org/operation_2943
    output: []
  homepage: https://github.com/wdecoster/NanoPlot
  homepage_status: 0
  language:
  - Python
  lastUpdate: '2025-06-18T12:31:48.762608Z'
  license: GPL-3.0
  link:
  - note: Issue tracker and most up to date software version
    type:
    - Repository
    url: https://github.com/wdecoster/NanoPlot
  - note: Web service with more limited options compared to the command line tool
    type:
    - Service
    url: http://nanoplot.bioinf.be/
  maturity: Mature
  name: NanoPlot
  operatingSystem:
  - Mac
  - Linux
  - Windows
  otherID: []
  owner: wdecoster
  publication:
  - doi: 10.1093/bioinformatics/bty149
    metadata:
      abstract: 'Summary: Here we describe NanoPack, a set of tools developed for
        visualization and processing of long-read sequencing data from Oxford Nanopore
        Technologies and Pacific Biosciences. Availability and implementation: The
        NanoPack tools are written in Python3 and released under the GNU GPL3.0 License.
        The source code can be found at https://github.com/wdecoster/nanopack, together
        with links to separate scripts and their documentation. The scripts are compatible
        with Linux, Mac OS and the MS Windows 10 subsystem for Linux and are available
        as a graphical user interface, a web service at http://nanoplot.bioinf.be
        and command line tools.'
      authors:
      - name: De Coster W.
      - name: D'Hert S.
      - name: Schultz D.T.
      - name: Cruts M.
      - name: Van Broeckhoven C.
      citationCount: 1840
      date: '2018-08-01T00:00:00Z'
      journal: Bioinformatics
      title: 'NanoPack: Visualizing and processing long-read sequencing data'
    note: null
    pmcid: PMC6061794
    pmid: '29547981'
    type:
    - Method
    version: null
  relation:
  - biotoolsID: nanopack
    type: includedIn
  toolType:
  - Command-line tool
  - Web application
  topic:
  - term: Genomics
    uri: http://edamontology.org/topic_0622
  validated: 0
  version:
  - v.1.42.0
- accessibility: Open access
  additionDate: '2019-09-13T12:51:16Z'
  biotoolsCURIE: biotools:kraken2
  biotoolsID: kraken2
  collectionID:
  - ONTeater
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: null
    fundrefid: null
    gridid: null
    name: Derrick E. Wood
    note: null
    orcidid: http://orcid.org/0000-0002-7429-1854
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Jennifer Lu
    note: null
    orcidid: http://orcid.org/0000-0001-9167-2002
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  - email: langmea@cs.jhu.edu
    fundrefid: null
    gridid: null
    name: Ben Langmead
    note: null
    orcidid: http://orcid.org/0000-0003-2437-1976
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  description: 'Kraken 2 is the newest version of Kraken, a taxonomic classification
    system using exact k-mer matches to achieve high accuracy and fast classification
    speeds. This classifier matches each k-mer within a query sequence to the lowest
    common ancestor (LCA) of all genomes containing the given k-mer. The k-mer assignments
    inform the classification algorithm.

    Any assumption that Kraken’s raw read assignments can be directly translated into
    species or strain-level abundance estimates is flawed. Bracken (Bayesian Reestimation
    of Abundance after Classification with KrakEN), estimates species abundances in
    metagenomics samples by probabilistically re-distributing reads in the taxonomic
    tree. (Lu, Jennifer et al. “Bracken: estimating species abundance in metagenomics
    data.”)'
  documentation:
  - note: null
    type:
    - User manual
    url: https://github.com/DerrickWood/kraken2/wiki/Manual
  - note: Links to multiple Kraken 2 and bracken databases and indexes
    type:
    - User manual
    url: https://benlangmead.github.io/aws-indexes/k2
  download:
  - note: null
    type: Source code
    url: https://github.com/DerrickWood/kraken2/archive/v2.0.8-beta.tar.gz
    version: 2.0.8-beta
  editPermission:
    authors:
    - vashokan
    - Keiler_Collier
    type: group
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: '`kraken2 --db <kraken2_database> <input.fastq>`'
    input:
    - data:
        term: DNA sequence
        uri: http://edamontology.org/data_3494
      format:
      - term: FASTQ
        uri: http://edamontology.org/format_1930
      - term: FASTA
        uri: http://edamontology.org/format_1929
    note: null
    operation:
    - term: Taxonomic classification
      uri: http://edamontology.org/operation_3460
    output:
    - data:
        term: Taxonomy
        uri: http://edamontology.org/data_3028
      format:
      - term: TSV
        uri: http://edamontology.org/format_3475
  homepage: https://ccb.jhu.edu/software/kraken2/
  homepage_status: 0
  language:
  - C++
  - Perl
  lastUpdate: '2025-06-18T12:24:26.657325Z'
  license: MIT
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/DerrickWood/kraken2
  - note: null
    type:
    - Issue tracker
    url: https://github.com/DerrickWood/kraken2/issues
  maturity: null
  name: kraken2
  operatingSystem: []
  otherID: []
  owner: anand-anshu
  publication:
  - doi: 10.1101/762302
    metadata: null
    note: null
    pmcid: null
    pmid: null
    type: []
    version: null
  relation:
  - biotoolsID: kraken
    type: isNewVersionOf
  - biotoolsID: bracken
    type: usedBy
  toolType:
  - Command-line tool
  topic:
  - term: Taxonomy
    uri: http://edamontology.org/topic_0637
  - term: Metagenomics
    uri: http://edamontology.org/topic_3174
  - term: Microbial ecology
    uri: http://edamontology.org/topic_3697
  - term: Microbiology
    uri: http://edamontology.org/topic_3301
  validated: 1
  version:
  - 2.0.8-beta
- accessibility: Open access
  additionDate: '2021-05-26T21:13:32Z'
  biotoolsCURIE: biotools:nextdenovo
  biotoolsID: nextdenovo
  collectionID:
  - ONTeater
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: support@nextomics.org
    fundrefid: null
    gridid: null
    name: Nextomics
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
    - Primary contact
    url: null
  description: NextDenovo is a string graph-based de novo assembler for long reads
    (CLR, HiFi and ONT). It uses a "correct-then-assemble" strategy similar to canu
    (no correction step for PacBio Hifi reads), but requires significantly less computing
    resources and storages.
  documentation:
  - note: null
    type:
    - User manual
    url: https://nextdenovo.readthedocs.io/en/latest/
  download:
  - note: null
    type: Source code
    url: https://github.com/Nextomics/NextDenovo/releases/tag/2.5.2
    version: null
  editPermission:
    authors:
    - jw
    - ELIXIR-CZ
    - Keiler_Collier
    type: group
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Sequence trace
        uri: http://edamontology.org/data_0924
      format:
      - term: FASTA
        uri: http://edamontology.org/format_1929
      - term: FASTQ
        uri: http://edamontology.org/format_1930
    note: null
    operation:
    - term: De-novo assembly
      uri: http://edamontology.org/operation_0524
    - term: Genome assembly
      uri: http://edamontology.org/operation_0525
    output:
    - data:
        term: Sequence assembly
        uri: http://edamontology.org/data_0925
      format:
      - term: Sequence assembly format (text)
        uri: http://edamontology.org/format_2561
      - term: FASTA
        uri: http://edamontology.org/format_1929
  homepage: https://github.com/Nextomics/NextDenovo
  homepage_status: 0
  language:
  - Python
  - C
  lastUpdate: '2025-06-18T12:20:23.607241Z'
  license: GPL-3.0
  link:
  - note: null
    type:
    - Issue tracker
    url: https://github.com/Nextomics/NextDenovo/issues
  maturity: Mature
  name: NextDenovo
  operatingSystem: []
  otherID: []
  owner: Kigaard
  publication:
  - doi: 10.1101/2023.03.09.531669.
    metadata: null
    note: null
    pmcid: null
    pmid: null
    type: []
    version: null
  relation: []
  toolType:
  - Command-line tool
  topic:
  - term: Sequencing
    uri: http://edamontology.org/topic_3168
  - term: Sequence assembly
    uri: http://edamontology.org/topic_0196
  validated: 0
  version:
  - v.2.5.2
- accessibility: Open access
  additionDate: '2021-05-27T09:04:45Z'
  biotoolsCURIE: biotools:quickmerge
  biotoolsID: quickmerge
  collectionID:
  - ONTeater
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: null
    fundrefid: null
    gridid: null
    name: Mahul Chakraborty
    note: null
    orcidid: https://orcid.org/0000-0003-2414-9187
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: https://mahulchakraborty.wordpress.com/
  description: Quickmerge is a program that uses complementary information from genomes
    assembled with long reads in order to improve contiguity, and works with assemblies
    derived from both Pacific Biosciences or Oxford Nanopore. Quickmerge will even
    work with hybrid assemblies made by combining long reads and Illumina short reads.
  documentation: []
  download: []
  editPermission:
    authors:
    - ELIXIR-CZ
    - Keiler_Collier
    type: group
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: merge_wrapper.py -pre output_prefix assembly_1.fa assembly_2.fa
    input:
    - data:
        term: Sequence set (nucleic acid)
        uri: http://edamontology.org/data_1234
      format:
      - term: FASTA
        uri: http://edamontology.org/format_1929
    note: 'Runs whole merge process on an input assembly.

      Assembly 2 will be used to fill gaps in assembly 1.'
    operation:
    - term: Genome assembly
      uri: http://edamontology.org/operation_0525
    - term: Scaffolding
      uri: http://edamontology.org/operation_3216
    - term: De-novo assembly
      uri: http://edamontology.org/operation_0524
    - term: Genotyping
      uri: http://edamontology.org/operation_3196
    output:
    - data:
        term: Sequence set (nucleic acid)
        uri: http://edamontology.org/data_1234
      format:
      - term: FASTA
        uri: http://edamontology.org/format_1929
  homepage: https://github.com/mahulchak/quickmerge
  homepage_status: 0
  language:
  - C++
  - C
  lastUpdate: '2025-06-18T12:17:20.983962Z'
  license: GPL-3.0
  link:
  - note: null
    type:
    - Issue tracker
    url: https://github.com/mahulchak/quickmerge/issues
  - note: null
    type:
    - Repository
    url: https://github.com/mahulchak/quickmerge
  maturity: null
  name: quickmerge
  operatingSystem:
  - Mac
  - Linux
  otherID: []
  owner: Kigaard
  publication:
  - doi: 10.1534/g3.118.200162
    metadata:
      abstract: Accurate and comprehensive characterization of genetic variation is
        essential for deciphering the genetic basis of diseases and other phenotypes.
        A vast amount of genetic variation stems from largescale sequence changes
        arising from the duplication, deletion, inversion, and translocation of sequences.
        In the past 10 years, high-throughput short reads have greatly expanded our
        ability to assay sequence variation due to single nucleotide polymorphisms.
        However, a recent de novo assembly of a second Drosophila melanogaster reference
        genome has revealed that short read genotyping methods miss hundreds of structural
        variants, including those affecting phenotypes. While genomes assembled using
        highcoverage long reads can achieve high levels of contiguity and completeness,
        concerns about cost, errors, and low yield have limited widespread adoption
        of such sequencing approaches. Here we resequenced the reference strain of
        D. melanogaster (ISO1) on a single Oxford Nanopore MinION flow cell run for
        24 hr. Using only reads longer than 1 kb or with at least 30x coverage, we
        assembled a highly contiguous de novo genome. The addition of inexpensive
        paired reads and subsequent scaffolding using an optical map technology achieved
        an assembly with completeness and contiguity comparable to the D. melanogaster
        reference assembly. Comparison of our assembly to the reference assembly of
        ISO1 uncovered a number of structural variants (SVs), including novel LTR
        transposable element insertions and duplications affecting genes with developmental,
        behavioral, and metabolic functions. Collectively, these SVs provide a snapshot
        of the dynamics of genome evolution. Furthermore, our assembly and comparison
        to the D. melanogaster reference genome demonstrates that high-quality de
        novo assembly of reference genomes and comprehensive variant discovery using
        such assemblies are now possible by a single lab for under $1,000 (USD).
      authors:
      - name: Solares E.A.
      - name: Chakraborty M.
      - name: Miller D.E.
      - name: Kalsow S.
      - name: Hall K.
      - name: Perera A.G.
      - name: Emerson J.J.
      - name: Scott Hawley R.
      citationCount: 70
      date: '2018-10-01T00:00:00Z'
      journal: 'G3: Genes, Genomes, Genetics'
      title: Rapid low-cost assembly of the drosophila melanogaster reference genome
        using low-coverage, long-read sequencing
    note: null
    pmcid: PMC6169397
    pmid: '30018084'
    type:
    - Primary
    version: null
  relation: []
  toolType:
  - Command-line tool
  topic:
  - term: Structural variation
    uri: http://edamontology.org/topic_3175
  - term: Sequence assembly
    uri: http://edamontology.org/topic_0196
  - term: DNA polymorphism
    uri: http://edamontology.org/topic_2885
  - term: Whole genome sequencing
    uri: http://edamontology.org/topic_3673
  - term: Genotype and phenotype
    uri: http://edamontology.org/topic_0625
  validated: 0
  version:
  - v.0.3
- accessibility: Open access
  additionDate: '2017-01-13T13:16:01Z'
  biotoolsCURIE: biotools:quast
  biotoolsID: quast
  collectionID:
  - ONTeater
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: quast.support@cab.spbu.ru
    fundrefid: null
    gridid: null
    name: QUAST Support
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  description: "QUAST stands for QUality ASsessment Tool.  \nIt evaluates a quality\
    \ of genome assemblies by computing various metrics and providing nice reports."
  documentation:
  - note: null
    type:
    - General
    url: http://quast.bioinf.spbau.ru/
  download: []
  editPermission:
    authors:
    - ELIXIR-CZ
    - Keiler_Collier
    type: group
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: quast -ek assembly.fa --out output_prefix
    input:
    - data:
        term: Sequence set (nucleic acid)
        uri: http://edamontology.org/data_1234
      format:
      - term: FASTA
        uri: http://edamontology.org/format_1929
    note: '# Running quast on a eukaryotic genome'
    operation:
    - term: Visualisation
      uri: http://edamontology.org/operation_0337
    - term: Sequence assembly validation
      uri: http://edamontology.org/operation_3180
    output: []
  homepage: http://quast.sourceforge.net/quast
  homepage_status: 0
  language:
  - Perl
  - Python
  - C
  lastUpdate: '2025-06-18T11:53:52.861712Z'
  license: GPL-2.0
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/ablab/quast
  - note: null
    type:
    - Issue tracker
    url: https://github.com/ablab/quast/issues
  maturity: Mature
  name: QUAST
  operatingSystem:
  - Linux
  - Mac
  otherID: []
  owner: seqwiki_import
  publication:
  - doi: 10.1093/bioinformatics/btt086
    metadata:
      abstract: Limitations of genome sequencing techniques have led to dozens of
        assembly algorithms, none of which is perfect. A number of methods for comparing
        assemblers have been developed, but none is yet a recognized benchmark. Further,
        most existing methods for comparing assemblies are only applicable to new
        assemblies of finished genomes; the problem of evaluating assemblies of previously
        unsequenced species has not been adequately considered. Here, we present QUAST
        - a quality assessment tool for evaluating and comparing genome assemblies.
        This tool improves on leading assembly comparison software with new ideas
        and quality metrics. QUAST can evaluate assemblies both with a reference genome,
        as well as without a reference. QUAST produces many reports, summary tables
        and plots to help scientists in their research and in their publications.
        In this study, we used QUAST to compare several genome assemblers on three
        datasets. QUAST tables and plots for all of them are available in the Supplementary
        Material, and interactive versions of these reports are on the QUAST website.
        © 2013 The Author.
      authors:
      - name: Gurevich A.
      - name: Saveliev V.
      - name: Vyahhi N.
      - name: Tesler G.
      citationCount: 6872
      date: '2013-04-15T00:00:00Z'
      journal: Bioinformatics
      title: 'QUAST: Quality assessment tool for genome assemblies'
    note: null
    pmcid: PMC3624806
    pmid: '23422339'
    type: []
    version: null
  relation: []
  toolType:
  - Workflow
  topic:
  - term: Sequence assembly
    uri: http://edamontology.org/topic_0196
  validated: 1
  version:
  - v.5.3.0
- accessibility: Open access
  additionDate: '2019-11-14T18:44:38Z'
  biotoolsCURIE: biotools:Racon
  biotoolsID: Racon
  collectionID:
  - ONTeater
  confidence_flag: tool
  cost: Free of charge
  credit:
  - email: cskang@korea.kr
    fundrefid: null
    gridid: null
    name: Chon-Sik Kang
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  - email: changsookim@cnu.ac.kr
    fundrefid: null
    gridid: null
    name: Changsoo Kim
    note: null
    orcidid: https://orcid.org/0000-0002-3596-2934
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  description: 'Consensus module for raw de novo DNA assembly of long uncorrected
    reads


    Racon is intended as a standalone consensus module to correct raw contigs generated
    by rapid assembly methods which do not include a consensus step. The goal of Racon
    is to generate genomic consensus which is of similar or better quality compared
    to the output generated by assembly methods which employ both error correction
    and consensus steps, while providing a speedup of several times compared to those
    methods. It supports data produced by both Pacific Biosciences and Oxford Nanopore
    Technologies.'
  documentation: []
  download: []
  editPermission:
    authors: []
    type: public
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: racon -u reads.fa mapped_reads.sam assembly.fa > assembly_racon.fa
    input:
    - data:
        term: Nucleic acid sequence alignment
        uri: http://edamontology.org/data_1383
      format:
      - term: BAM
        uri: http://edamontology.org/format_2572
      - term: SAM
        uri: http://edamontology.org/format_2573
    - data:
        term: Sequence set (nucleic acid)
        uri: http://edamontology.org/data_1234
      format:
      - term: FASTQ
        uri: http://edamontology.org/format_1930
    - data:
        term: Sequence set (nucleic acid)
        uri: http://edamontology.org/data_1234
      format:
      - term: FASTA
        uri: http://edamontology.org/format_1929
    note: '# The mapping file can be generated with any mapping program - eg, bwa-mem
      or minimap2.

      # The following is an example using minimap2 with ONT data

      minimap2 assembly.fa-ax map-ont reads.fa > mapped_reads.sam'
    operation:
    - term: Genome assembly
      uri: http://edamontology.org/operation_0525
    - term: Mapping assembly
      uri: http://edamontology.org/operation_0523
    output:
    - data:
        term: Sequence set (nucleic acid)
        uri: http://edamontology.org/data_1234
      format:
      - term: FASTA
        uri: http://edamontology.org/format_1929
  homepage: https://github.com/isovic/racon
  homepage_status: 0
  language:
  - C++
  - Python
  lastUpdate: '2025-06-18T11:42:42.378216Z'
  license: MIT
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/isovic/racon
  - note: null
    type:
    - Issue tracker
    url: https://github.com/isovic/racon/issues
  maturity: null
  name: Racon
  operatingSystem:
  - Mac
  - Linux
  otherID: []
  owner: Pub2Tools
  publication:
  - doi: 10.3390/plants8080270
    metadata:
      abstract: 'The whole genome sequencing (WGS) has become a crucial tool in understanding
        genome structure and genetic variation. The MinION sequencing of Oxford Nanopore
        Technologies (ONT) is an excellent approach for performing WGS and it has
        advantages in comparison with other Next-Generation Sequencing (NGS): It is
        relatively inexpensive, portable, has simple library preparation, can be monitored
        in real-time, and has no theoretical limits on reading length. Sorghum bicolor
        (L.) Moench is diploid (2n = 2x = 20) with a genome size of about 730 Mb,
        and its genome sequence information is released in the Phytozome database.
        Therefore, sorghum can be used as a good reference. However, plant species
        have complex and large genomes when compared to animals or microorganisms.
        As a result, complete genome sequencing is difficult for plant species. MinION
        sequencing that produces long-reads can be an excellent tool for overcoming
        the weak assembly of short-reads generated from NGS by minimizing the generation
        of gaps or covering the repetitive sequence that appears on the plant genome.
        Here, we conducted the genome sequencing for S. bicolor cv. BTx623 while using
        the MinION platform and obtained 895,678 reads and 17.9 gigabytes (Gb) (ca.
        25× coverage of reference) from long-read sequence data. A total of 6124 contigs
        (covering 45.9%) were generated from Canu, and a total of 2661 contigs (covering
        50%) were generated from Minimap and Miniasm with a Racon through a de novo
        assembly using two different tools and mapped assembled contigs against the
        sorghum reference genome. Our results provide an optimal series of long-read
        sequencing analysis for plant species while using the MinION platform and
        a clue to determine the total sequencing scale for optimal coverage that is
        based on various genome sizes.'
      authors:
      - name: Lee Y.G.
      - name: Choi S.C.
      - name: Kang Y.
      - name: Kim K.M.
      - name: Kang C.-S.
      - name: Kim C.
      citationCount: 13
      date: '2019-08-01T00:00:00Z'
      journal: Plants
      title: 'Constructing a reference genome in a single lab: The possibility to
        use oxford nanopore technology'
    note: null
    pmcid: PMC6724115
    pmid: '31390788'
    type: []
    version: null
  relation: []
  toolType: []
  topic:
  - term: Whole genome sequencing
    uri: http://edamontology.org/topic_3673
  - term: Sequence assembly
    uri: http://edamontology.org/topic_0196
  validated: 1
  version: []
- accessibility: Open access
  additionDate: '2019-11-14T20:08:20Z'
  biotoolsCURIE: biotools:Flye
  biotoolsID: Flye
  collectionID:
  - ONTeater
  confidence_flag: tool
  cost: Free of charge
  credit:
  - email: fenderglass@gmail.com
    fundrefid: null
    gridid: null
    name: Mikhail Kolmogorov
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    - Support
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Yu Lin
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Jeffrey Yuan
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: null
  description: 'Flye is a de novo assembler for single molecule sequencing reads,
    such as those produced by PacBio and Oxford Nanopore Technologies. It is designed
    for a wide range of datasets, from small bacterial projects to large mammalian-scale
    assemblies. The package represents a complete pipeline: it takes raw PB / ONT
    reads as input and outputs polished contigs.'
  documentation: []
  download: []
  editPermission:
    authors: []
    type: public
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Sequence set (nucleic acid)
        uri: http://edamontology.org/data_1234
      format:
      - term: FASTQ
        uri: http://edamontology.org/format_1930
    note: null
    operation:
    - term: Genome assembly
      uri: http://edamontology.org/operation_0525
    - term: De-novo assembly
      uri: http://edamontology.org/operation_0524
    - term: Mapping assembly
      uri: http://edamontology.org/operation_0523
    - term: Cross-assembly
      uri: http://edamontology.org/operation_3730
    output:
    - data:
        term: Sequence set (nucleic acid)
        uri: http://edamontology.org/data_1234
      format:
      - term: FASTA
        uri: http://edamontology.org/format_1929
  homepage: https://github.com/fenderglass/Flye
  homepage_status: 0
  language:
  - C++
  - Python
  - C
  lastUpdate: '2025-06-18T10:20:03.775603Z'
  license: BSD-3-Clause
  link:
  - note: null
    type:
    - Issue tracker
    url: https://github.com/fenderglass/Flye/issues
  - note: null
    type:
    - Repository
    url: https://github.com/mikolmogorov/Flye
  maturity: null
  name: Flye
  operatingSystem:
  - Mac
  - Linux
  otherID: []
  owner: Pub2Tools
  publication:
  - doi: 10.1099/mgen.0.000294
    metadata:
      abstract: Illumina sequencing allows rapid, cheap and accurate whole genome
        bacterial analyses, but short reads (<300 bp) do not usually enable complete
        genome assembly. Long-read sequencing greatly assists with resolving complex
        bacterial genomes, particularly when combined with short-read Illumina data
        (hybrid assembly). However, it is not clear how different long-read sequencing
        methods affect hybrid assembly accuracy. Relative automation of the assembly
        process is also crucial to facilitating high-throughput complete bacterial
        genome reconstruction, avoiding multiple bespoke filtering and data manipulation
        steps. In this study, we compared hybrid assemblies for 20 bacterial isolates,
        including two reference strains, using Illumina sequencing and long reads
        from either Oxford Nanopore Technologies (ONT) or SMRT Pacific Biosciences
        (PacBio) sequencing platforms. We chose isolates from the family Enterobacteriaceae,
        as these frequently have highly plastic, repetitive genetic structures, and
        complete genome reconstruction for these species is relevant for a precise
        understanding of the epidemiology of antimicrobial resistance. We de novo
        assembled genomes using the hybrid assembler Unicycler and compared different
        read processing strategies, as well as comparing to long-read-only assembly
        with Flye followed by short-read polishing with Pilon. Hybrid assembly with
        either PacBio or ONT reads facilitated high-quality genome reconstruction,
        and was superior to the longread assembly and polishing approach evaluated
        with respect to accuracy and completeness. Combining ONT and Illumina reads
        fully resolved most genomes without additional manual steps, and at a lower
        consumables cost per isolate in our setting. Automated hybrid assembly is
        a powerful tool for complete and accurate bacterial genome assembly.
      authors:
      - name: De Maio N.
      - name: Shaw L.P.
      - name: Hubbard A.
      - name: George S.
      - name: Sanderson N.D.
      - name: Swann J.
      - name: Wick R.
      - name: Oun M.A.
      - name: Stubberfield E.
      - name: Hoosdally S.J.
      - name: Crook D.W.
      - name: Peto T.E.A.
      - name: Sheppard A.E.
      - name: Bailey M.J.
      - name: Read D.S.
      - name: Anjum M.F.
      - name: Sarah Walker A.
      - name: Stoesser N.
      citationCount: 166
      date: '2019-01-01T00:00:00Z'
      journal: Microbial Genomics
      title: Comparison of long-read sequencing technologies in the hybrid assembly
        of complex bacterial genomes
    note: null
    pmcid: PMC6807382
    pmid: '31483244'
    type:
    - Usage
    version: null
  - doi: 10.1038/s41587-019-0072-8
    metadata:
      abstract: Accurate genome assembly is hampered by repetitive regions. Although
        long single molecule sequencing reads are better able to resolve genomic repeats
        than short-read data, most long-read assembly algorithms do not provide the
        repeat characterization necessary for producing optimal assemblies. Here,
        we present Flye, a long-read assembly algorithm that generates arbitrary paths
        in an unknown repeat graph, called disjointigs, and constructs an accurate
        repeat graph from these error-riddled disjointigs. We benchmark Flye against
        five state-of-the-art assemblers and show that it generates better or comparable
        assemblies, while being an order of magnitude faster. Flye nearly doubled
        the contiguity of the human genome assembly (as measured by the NGA50 assembly
        quality metric) compared with existing assemblers.
      authors:
      - name: Kolmogorov M.
      - name: Yuan J.
      - name: Lin Y.
      - name: Pevzner P.A.
      citationCount: 3077
      date: '2019-05-01T00:00:00Z'
      journal: Nature Biotechnology
      title: Assembly of long, error-prone reads using repeat graphs
    note: null
    pmcid: null
    pmid: '30936562'
    type:
    - Primary
    version: null
  - doi: 10.1038/s41592-020-00971-x
    metadata:
      abstract: Long-read sequencing technologies have substantially improved the
        assemblies of many isolate bacterial genomes as compared to fragmented short-read
        assemblies. However, assembling complex metagenomic datasets remains difficult
        even for state-of-the-art long-read assemblers. Here we present metaFlye,
        which addresses important long-read metagenomic assembly challenges, such
        as uneven bacterial composition and intra-species heterogeneity. First, we
        benchmarked metaFlye using simulated and mock bacterial communities and show
        that it consistently produces assemblies with better completeness and contiguity
        than state-of-the-art long-read assemblers. Second, we performed long-read
        sequencing of the sheep microbiome and applied metaFlye to reconstruct 63
        complete or nearly complete bacterial genomes within single contigs. Finally,
        we show that long-read assembly of human microbiomes enables the discovery
        of full-length biosynthetic gene clusters that encode biomedically important
        natural products.
      authors:
      - name: Kolmogorov M.
      - name: Bickhart D.M.
      - name: Behsaz B.
      - name: Gurevich A.
      - name: Rayko M.
      - name: Shin S.B.
      - name: Kuhn K.
      - name: Yuan J.
      - name: Polevikov E.
      - name: Smith T.P.L.
      - name: Pevzner P.A.
      citationCount: 511
      date: '2020-11-01T00:00:00Z'
      journal: Nature Methods
      title: 'metaFlye: scalable long-read metagenome assembly using repeat graphs'
    note: null
    pmcid: PMC10699202
    pmid: '33020656'
    type:
    - Primary
    version: null
  relation: []
  toolType:
  - Command-line tool
  - Workflow
  topic:
  - term: Sequence assembly
    uri: http://edamontology.org/topic_0196
  - term: Metagenomics
    uri: http://edamontology.org/topic_3174
  - term: Whole genome sequencing
    uri: http://edamontology.org/topic_3673
  - term: Genomics
    uri: http://edamontology.org/topic_0622
  validated: 1
  version:
  - 2.9.6
- accessibility: Open access
  additionDate: '2020-06-18T05:28:02Z'
  biotoolsCURIE: biotools:biosimulations
  biotoolsID: biosimulations
  collectionID: []
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: karr@mssm.edu
    fundrefid: null
    gridid: null
    name: Jonathan Karr
    note: null
    orcidid: https://orcid.org/0000-0002-2605-5080
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: https://www.karrlab.org
  - email: null
    fundrefid: null
    gridid: null
    name: Bilal Shaikh
    note: null
    orcidid: https://orcid.org/0000-0001-5801-5510
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: null
  description: BioSimulations is a web application for sharing and re-using biomodels,
    simulations, and visualizations of simulations results. BioSimulations supports
    a wide range of modeling frameworks (e.g., kinetic, constraint-based, and logical
    modeling), model formats (e.g., BNGL, CellML, SBML), and simulation tools (e.g.,
    COPASI, libRoadRunner/tellurium, NFSim, VCell). BioSimulations aims to help researchers
    discover published models that might be useful for their research and quickly
    try them via a simple web-based interface.
  documentation:
  - note: null
    type:
    - General
    url: https://docs.biosimulations.org
  - note: null
    type:
    - API documentation
    url: https://api.biosimulations.org/
  - note: null
    type:
    - Code of conduct
    url: https://docs.biosimulations.org/developers/conduct/
  - note: null
    type:
    - Terms of use
    url: https://docs.biosimulations.org/about/terms/
  download: []
  editPermission:
    authors:
    - bilalshaikh42
    - Bioinfo
    type: group
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Mathematical model
        uri: http://edamontology.org/data_0950
      format:
      - term: SBML
        uri: http://edamontology.org/format_2585
      - term: CellML
        uri: http://edamontology.org/format_3240
    note: null
    operation:
    - term: Visualisation
      uri: http://edamontology.org/operation_0337
    - term: Modelling and simulation
      uri: http://edamontology.org/operation_2426
    output:
    - data:
        term: Trajectory data
        uri: http://edamontology.org/data_3870
      format:
      - term: CSV
        uri: http://edamontology.org/format_3752
      - term: SVG
        uri: http://edamontology.org/format_3604
  homepage: https://www.biosimulations.org/
  homepage_status: 0
  language:
  - JavaScript
  - Python
  lastUpdate: '2025-06-17T16:32:28.548746Z'
  license: MIT
  link:
  - note: null
    type:
    - Issue tracker
    url: https://github.com/reproducible-biomedical-modeling/Biosimulations/issues
  - note: null
    type:
    - Repository
    url: https://github.com/reproducible-biomedical-modeling/Biosimulations
  - note: null
    type:
    - Service
    url: https://api.biosimulations.org/
  maturity: Emerging
  name: BioSimulations
  operatingSystem: []
  otherID:
  - type: rrid
    value: RRID:SCR_018733
    version: null
  owner: Bioinfo
  publication: []
  relation:
  - biotoolsID: runbiosimulations
    type: uses
  - biotoolsID: biosimulators
    type: uses
  - biotoolsID: biomodels
    type: uses
  - biotoolsID: sbml
    type: uses
  - biotoolsID: bionetgen
    type: uses
  - biotoolsID: cobrapy
    type: uses
  - biotoolsID: copasi
    type: uses
  - biotoolsID: libroadrunner
    type: uses
  toolType:
  - Command-line tool
  - Web API
  - Web application
  - Web service
  topic:
  - term: Systems biology
    uri: http://edamontology.org/topic_2259
  - term: Molecular interactions, pathways and networks
    uri: http://edamontology.org/topic_0602
  validated: 1
  version: []
- accessibility: null
  additionDate: '2017-08-20T15:17:20Z'
  biotoolsCURIE: biotools:bracken
  biotoolsID: bracken
  collectionID:
  - Animal and Crop Genomics
  confidence_flag: null
  cost: null
  credit:
  - email: jlu26@jhmi.edu
    fundrefid: null
    gridid: null
    name: null
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  description: Bracken is a companion program to Kraken 1, KrakenUniq, or Kraken 2
    While Kraken classifies reads to multiple levels in the taxonomic tree, Bracken
    allows estimation of abundance at a single level using those classifications (e.g.
    Bracken can estimate abundance of species within a sample).
  documentation:
  - note: null
    type:
    - User manual
    url: https://ccb.jhu.edu/software/bracken/index.shtml?t=manual
  download: []
  editPermission:
    authors:
    - animalandcropgenomics
    - ELIXIR-CZ
    - bebatut
    - vashokan
    type: group
  elixirCommunity: []
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  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Statistical calculation
      uri: http://edamontology.org/operation_2238
    output: []
  homepage: https://ccb.jhu.edu/software/bracken/
  homepage_status: 0
  language:
  - Perl
  - Python
  lastUpdate: '2025-06-11T12:25:29.118910Z'
  license: GPL-3.0
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/jenniferlu717/Bracken
  - note: null
    type:
    - Issue tracker
    url: https://github.com/jenniferlu717/Bracken/issues
  maturity: null
  name: Bracken
  operatingSystem:
  - Linux
  otherID: []
  owner: admin
  publication:
  - doi: 10.7717/peerj-cs.104
    metadata:
      abstract: Metagenomic experiments attempt to characterize microbial communities
        using high-throughput DNA sequencing. Identification of the microorganisms
        in a sample provides information about the genetic profile, population structure,
        and role of microorganisms within an environment. Until recently, most metagenomics
        studies focused on high-level characterization at the level of phyla, or alternatively
        sequenced the 16S ribosomalRNAgene that is present in bacterial species. As
        the cost of sequencing has fallen, though, metagenomics experiments have increasingly
        used unbiased shotgun sequencing to capture all the organisms in a sample.
        This approach requires a method for estimating abundance directly from the
        raw read data. Here we describe a fast, accurate new method that computes
        the abundance at the species level using the reads collected in a metagenomics
        experiment. Bracken (Bayesian Reestimation of Abundance after Classification
        with KrakEN) uses the taxonomic assignments made by Kraken, a very fast read-level
        classifier, along with information about the genomes themselves to estimate
        abundance at the species level, the genus level, or above. We demonstrate
        that Bracken can produce accurate species- and genus-level abundance estimates
        even when a sample contains multiple near-identical species.
      authors:
      - name: Lu J.
      - name: Breitwieser F.P.
      - name: Thielen P.
      - name: Salzberg S.L.
      citationCount: 1084
      date: '2017-01-01T00:00:00Z'
      journal: PeerJ Computer Science
      title: 'Bracken: Estimating species abundance in metagenomics data'
    note: null
    pmcid: null
    pmid: null
    type:
    - Primary
    version: null
  relation:
  - biotoolsID: kraken2
    type: uses
  toolType:
  - Command-line tool
  topic:
  - term: Metagenomics
    uri: http://edamontology.org/topic_3174
  - term: Microbial ecology
    uri: http://edamontology.org/topic_3697
  validated: 1
  version: []
- accessibility: null
  additionDate: '2023-08-30T09:06:30.320364Z'
  biotoolsCURIE: biotools:pym2aia
  biotoolsID: pym2aia
  collectionID: []
  confidence_flag: null
  cost: null
  credit:
  - email: null
    fundrefid: null
    gridid: null
    name: Jonas Cordes
    note: null
    orcidid: https://orcid.org/0000-0003-3148-4282
    rorid: null
    typeEntity: null
    typeRole: []
    url: null
  description: pyM²aia is a Python package for memory-efficient access and processing
    of mass spectrometry image data. The I/O functionality is derived from the interactive
    desktop application M²aia. Special features are the batch generator utilities
    for deep learning applications.
  documentation:
  - note: null
    type:
    - General
    url: https://data.jtfc.de/pym2aia/sphinx-build/html/index.html
  download:
  - note: null
    type: Source code
    url: https://github.com/m2aia/pym2aia
    version: null
  editPermission:
    authors: []
    type: public
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Mass spectrometry data
        uri: http://edamontology.org/data_2536
      format:
      - term: imzML metadata file
        uri: http://edamontology.org/format_3682
    - data:
        term: Mass spectrometry data
        uri: http://edamontology.org/data_2536
      format:
      - term: ibd
        uri: http://edamontology.org/format_3839
    note: null
    operation:
    - term: Standardisation and normalisation
      uri: http://edamontology.org/operation_3435
    output:
    - data:
        term: Mass spectrometry data
        uri: http://edamontology.org/data_2536
      format:
      - term: imzML metadata file
        uri: http://edamontology.org/format_3682
    - data:
        term: Mass spectrometry data
        uri: http://edamontology.org/data_2536
      format:
      - term: ibd
        uri: http://edamontology.org/format_3839
  homepage: https://m2aia.de/pym2aia.html
  homepage_status: 0
  language:
  - Python
  - C++
  lastUpdate: '2025-06-05T12:19:20.571346Z'
  license: BSD-3-Clause
  link:
  - note: null
    type:
    - Issue tracker
    - Repository
    url: https://github.com/m2aia/pym2aia
  maturity: null
  name: pyM2aia
  operatingSystem:
  - Mac
  - Linux
  - Windows
  otherID: []
  owner: jtfc
  publication:
  - doi: 10.1093/gigascience/giab049
    metadata:
      abstract: 'Background: Mass spectrometry imaging (MSI) is a label-free analysis
        method for resolving bio-molecules or pharmaceuticals in the spatial domain.
        It offers unique perspectives for the examination of entire organs or other
        tissue specimens. Owing to increasing capabilities of modern MSI devices,
        the use of 3D and multi-modal MSI becomes feasible in routine applications-resulting
        in hundreds of gigabytes of data. To fully leverage such MSI acquisitions,
        interactive tools for 3D image reconstruction, visualization, and analysis
        are required, which preferably should be open-source to allow scientists to
        develop custom extensions. Findings: We introduce M2aia (MSI applications
        for interactive analysis in MITK), a software tool providing interactive and
        memory-efficient data access and signal processing of multiple large MSI datasets
        stored in imzML format. M2aia extends MITK, a popular open-source tool in
        medical image processing. Besides the steps of a typical signal processing
        workflow, M2aia offers fast visual interaction, image segmentation, deformable
        3D image reconstruction, and multi-modal registration. A unique feature is
        that fused data with individual mass axes can be visualized in a shared coordinate
        system. We demonstrate features of M2aia by reanalyzing an N-glycan mouse
        kidney dataset and 3D reconstruction and multi-modal image registration of
        a lipid and peptide dataset of a mouse brain, which we make publicly available.
        Conclusions: To our knowledge, M2aia is the first extensible open-source application
        that enables a fast, user-friendly, and interactive exploration of large datasets.
        M2aia is applicable to a wide range of MSI analysis tasks.'
      authors:
      - name: Cordes J.
      - name: Enzlein T.
      - name: Marsching C.
      - name: Hinze M.
      - name: Engelhardt S.
      - name: Hopf C.
      - name: Wolf I.
      citationCount: 17
      date: '2021-07-01T00:00:00Z'
      journal: GigaScience
      title: M2aia-Interactive, fast, and memory-efficient analysis of 2D and 3D multi-modal
        mass spectrometry imaging data
    note: 'Cordes J; Enzlein T; Marsching C; Hinze M; Engelhardt S; Hopf C; Wolf I
      (July, 2021): M²aia - Interactive, fast and memory efficient analysis of 2D
      and 3D multi-modal mass spectrometry imaging data https://doi.org/10.1093/gigascience/giab049'
    pmcid: PMC8290197
    pmid: '34282451'
    type: []
    version: null
  relation:
  - biotoolsID: m2aia
    type: uses
  toolType:
  - Library
  topic:
  - term: Metabolomics
    uri: http://edamontology.org/topic_3172
  - term: Data visualisation
    uri: http://edamontology.org/topic_0092
  - term: Bioinformatics
    uri: http://edamontology.org/topic_0091
  validated: 0
  version: []
- accessibility: Open access
  additionDate: '2021-05-26T20:42:18Z'
  biotoolsCURIE: biotools:maldi_quant
  biotoolsID: maldi_quant
  collectionID: []
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: mail@sebastiangibb.de
    fundrefid: null
    gridid: null
    name: Sebastian Gibb
    note: null
    orcidid: https://orcid.org/0000-0001-7406-4443
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    - Developer
    - Maintainer
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Korbinian Strimmer
    note: null
    orcidid: https://orcid.org/0000-0001-7917-2056
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: null
  description: MALDIquant is a complete analysis pipeline for matrix-assisted laser
    desorption/ionization-time-of-flight (MALDI-TOF) and other two-dimensional mass
    spectrometry data. In addition to commonly used plotting and processing methods
    it includes distinctive features, namely baseline subtraction methods such as
    morphological filters (TopHat) or the statistics-sensitive non-linear iterative
    peak-clipping algorithm (SNIP), peak alignment using warping functions, handling
    of replicated measurements as well as allowing spectra with different resolutions.
  documentation:
  - note: null
    type:
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    output:
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      format:
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  homepage_status: 0
  language:
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  lastUpdate: '2025-06-05T11:28:57.497366Z'
  license: GPL-3.0
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    type:
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    url: https://github.com/sgibb/MALDIquant/
  - note: null
    type:
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    url: https://github.com/sgibb/MALDIquant/issues
  - note: null
    type:
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    url: http://strimmerlab.org/software/maldiquant/
  maturity: null
  name: MALDIquant
  operatingSystem: []
  otherID: []
  owner: Kigaard
  publication:
  - doi: 10.1093/bioinformatics/bts447
    metadata:
      abstract: MALDIquant is an R package providing a complete and modular analysis
        pipeline for quantitative analysis of mass spectrometry data. MALDIquant is
        specifically designed with application in clinical diagnostics in mind and
        implements sophisticated routines for importing raw data, preprocessing, non-linear
        peak alignment and calibration. It also handles technical replicates as well
        as spectra with unequal resolution. © The Author 2012. Published by Oxford
        University Press. All rights reserved.
      authors:
      - name: Gibb S.
      - name: Strimmer K.
      citationCount: 499
      date: '2012-09-01T00:00:00Z'
      journal: Bioinformatics
      title: 'Maldiquant: A versatile R package for the analysis of mass spectrometry
        data'
    note: null
    pmcid: null
    pmid: '22796955'
    type:
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  relation: []
  toolType:
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  topic:
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  - term: Proteomics
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  validated: 0
  version: []
- accessibility: Open access
  additionDate: '2019-09-28T12:06:10Z'
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  cost: Free of charge
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    rorid: null
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  description: 'AMICI provides a multi-language (Python, C++, Matlab) interface for
    the SUNDIALS solvers CVODES (for ordinary differential equations) and IDAS (for
    algebraic differential equations). AMICI allows the user to read differential
    equation models specified as SBML or PySB and automatically compiles such models
    into .mex simulation files (Matlab), C++ executables or Python modules.


    Beyond forward integration, the compiled simulation file also allows for forward
    sensitivity analysis, steady state sensitivity analysis and adjoint sensitivity
    analysis for likelihood-based output functions.


    The interface was designed to provide routines for efficient gradient computation
    in parameter estimation of biochemical reaction models but it is also applicable
    to a wider range of differential equation constrained optimization problems.'
  documentation:
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    input:
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      - term: PEtab
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    note: null
    operation:
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    - term: Modelling and simulation
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    output:
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      format:
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  homepage: https://github.com/AMICI-dev/AMICI
  homepage_status: 0
  language:
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  - C++
  - Python
  lastUpdate: '2025-05-08T07:28:52.817175Z'
  license: BSD-3-Clause
  link:
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  maturity: Mature
  name: AMICI
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  - Windows
  - Mac
  otherID: []
  owner: dweindl
  publication:
  - doi: 10.1093/bioinformatics/btab227
    metadata:
      abstract: Ordinary differential equation models facilitate the understanding
        of cellular signal transduction and other biological processes. However, for
        large and comprehensive models, the computational cost of simulating or calibrating
        can be limiting. AMICI is a modular toolbox implemented in C++/Python/MATLAB
        that provides efficient simulation and sensitivity analysis routines tailored
        for scalable, gradient-based parameter estimation and uncertainty quantification.
      authors:
      - name: Frohlich F.
      - name: Weindl D.
      - name: Schalte Y.
      - name: Pathirana D.
      - name: Paszkowski L.
      - name: Lines G.T.
      - name: Stapor P.
      - name: Hasenauer J.
      citationCount: 37
      date: '2021-10-15T00:00:00Z'
      journal: Bioinformatics
      title: 'AMICI: high-performance sensitivity analysis for large ordinary differential
        equation models'
    note: null
    pmcid: PMC8545331
    pmid: '33821950'
    type:
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    version: null
  relation: []
  toolType:
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  topic:
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    uri: http://edamontology.org/topic_2259
  validated: 1
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- accessibility: Open access
  additionDate: '2019-08-09T13:16:33Z'
  biotoolsCURIE: biotools:pyOpenMS
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  collectionID: []
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  cost: Free of charge
  credit:
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    fundrefid: null
    gridid: null
    name: Hannes L. Rost
    note: null
    orcidid: null
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    typeEntity: Person
    typeRole:
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    url: null
  description: Python library for mass spectrometry, specifically for the analysis
    of proteomics and metabolomics data.
  documentation:
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    type:
    - User manual
    url: https://pyopenms.readthedocs.io
  download: []
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  homepage: https://github.com/OpenMS/pyopenms-extra/blob/master/docs/source/index.rst
  homepage_status: 0
  language:
  - Python
  lastUpdate: '2025-04-30T11:39:29.549782Z'
  license: BSD-3-Clause
  link:
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    type:
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    url: https://github.com/OpenMS/pyopenms-extra
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  maturity: Mature
  name: pyOpenMS
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  otherID: []
  owner: samwein
  publication:
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    metadata: null
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  relation: []
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  topic:
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  - term: Protein modifications
    uri: http://edamontology.org/topic_0601
  validated: 1
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- accessibility: Open access (with restrictions)
  additionDate: '2017-04-22T17:35:18Z'
  biotoolsCURIE: biotools:gemma
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  cost: Free of charge (with restrictions)
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    fundrefid: null
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    name: Pavlidis Lab Support
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  description: Gemma provides data, experimental design annotations, and differential
    expression analysis results for thousands of microarray and RNA-seq experiments.
    We re-analyze raw data from public sources (primarily NCBI GEO), annotate experimental
    conditions, conduct quality control and compute differential expression using
    standardized procedures. We have especially good coverage of experiments relevant
    to the nervous system.
  documentation:
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    type:
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    url: https://pavlidislab.github.io/Gemma/
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      format: []
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  homepage: https://gemma.msl.ubc.ca/
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  license: CC-BY-NC-4.0
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  maturity: Mature
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  otherID: []
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  publication:
  - doi: 10.1093/bioinformatics/btp259
    metadata:
      abstract: 'Motivation: Many microarray datasets are available online with formalized
        standards describing the probe sequences and expression values. Unfortunately,
        the description, conditions and parameters of the experiments are less commonly
        formalized and often occur as natural language text. This hinders searching,
        high-throughput analysis, organization and integration of the datasets. Results:
        We use the lexical resources and software tools from the Unified Medical Language
        System (UMLS) to extract concepts from text. We then link the UMLS concepts
        to classes in open biomedical ontologies. The result is accessible and clear
        semantic annotations of gene expression experiments. We applied the method
        to 595 expression experiments from Gemma, a resource for re-use and meta-analysis
        of gene expression profiling data. We evaluated and corrected all stages of
        the annotation process. The majority of missed annotations were due to a lack
        of cross-references. The most error-prone stage was the extraction of concepts
        from phrases. Final review of the annotations in context of the experiments
        revealed 89% precision. A naive system, lacking the phrase to concept corrections
        is 68% precise. We have integrated this annotation pipeline into Gemma. ©
        2009 The Author(s).'
      authors:
      - name: French L.
      - name: Lane S.
      - name: Law T.
      - name: Xu L.
      - name: Pavlidis P.
      citationCount: 9
      date: '2009-06-09T00:00:00Z'
      journal: Bioinformatics
      title: Application and evaluation of automated semantic annotation of gene expression
        experiments
    note: null
    pmcid: PMC2687992
    pmid: '19376825'
    type:
    - Primary
    version: null
  - doi: 10.1093/database/baab006
    metadata:
      abstract: 'Vast amounts of transcriptomic data reside in public repositories,
        but effective reuse remains challenging. Issues include unstructured dataset
        metadata, inconsistent data processing and quality control, and inconsistent
        probe-gene mappings across microarray technologies. Thus, extensive curation
        and data reprocessing are necessary prior to any reuse. The Gemma bioinformatics
        system was created to help address these issues. Gemma consists of a database
        of curated transcriptomic datasets, analytical software, a web interface and
        web services. Here we present an update on Gemma''s holdings, data processing
        and analysis pipelines, our curation guidelines, and software features. As
        of June 2020, Gemma contains 10 811 manually curated datasets (primarily human,
        mouse and rat), over 395 000 samples and hundreds of curated transcriptomic
        platforms (both microarray and RNA sequencing). Dataset topics were represented
        with 10 215 distinct terms from 12 ontologies, for a total of 54 316 topic
        annotations (mean topics/dataset = 5.2). While Gemma has broad coverage of
        conditions and tissues, it captures a large majority of available brain-related
        datasets, accounting for 34% of its holdings. Users can access the curated
        data and differential expression analyses through the Gemma website, RESTful
        service and an R package. Database URL: https://gemma.msl.ubc.ca/home.html'
      authors:
      - name: Lim N.
      - name: Tesar S.
      - name: Belmadani M.
      - name: Poirier-Morency G.
      - name: Mancarci B.O.
      - name: Sicherman J.
      - name: Jacobson M.
      - name: Leong J.
      - name: Tan P.
      - name: Pavlidis P.
      citationCount: 21
      date: '2021-01-01T00:00:00Z'
      journal: Database
      title: Curation of over 10 000 transcriptomic studies to enable data reuse
    note: null
    pmcid: PMC7904053
    pmid: '33599246'
    type:
    - Primary
    version: null
  relation:
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    type: uses
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    type: uses
  - biotoolsID: star
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  - biotoolsID: ncbi_geo
    type: uses
  - biotoolsID: sradb
    type: uses
  - biotoolsID: ncbi_gene
    type: uses
  toolType:
  - Web application
  - Web API
  topic:
  - term: RNA-Seq
    uri: http://edamontology.org/topic_3170
  - term: Gene expression
    uri: http://edamontology.org/topic_0203
  - term: Genetics
    uri: http://edamontology.org/topic_3053
  - term: Microarray experiment
    uri: http://edamontology.org/topic_3518
  - term: Data curation and archival
    uri: http://edamontology.org/topic_0219
  validated: 1
  version:
  - 1.31.13
- accessibility: Open access
  additionDate: '2025-04-11T13:56:02.037873Z'
  biotoolsCURIE: biotools:pr2-reference
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  collectionID: []
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  cost: Free of charge
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  description: The PR2 reference sequence database was initiated in 2010 in the frame
    of the BioMarks project from work that had developed in the previous ten years
    in the Plankton Group of the Station Biologique of Roscoff. It aims to provide
    a reference database of carefully annotated 18S rRNA sequences using nine unique
    taxonomic fields (from domain to species). At present, it contains over 240,000
    sequences. Although it focuses on protists, it also contains sequences from metazoa,
    fungi and plants as well a limited set of 16S sequences from plastids and bacteria.
    Several metadata fields are available for many sequences, including geo-localisation,
    whether it originates from a culture or a natural sample, host type etc… The annotation
    of PR2 is performed by experts from each taxonomic groups.
  documentation:
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    type:
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    metadata:
      abstract: The interrogation of genetic markers in environmental meta-barcoding
        studies is currently seriously hindered by the lack of taxonomically curated
        reference data sets for the targeted genes. The Protist Ribosomal Reference
        database (PR2, http://ssu-rrna.org/) provides a unique access to eukaryotic
        small sub-unit (SSU) ribosomal RNA and DNA sequences, with curated taxonomy.
        The database mainly consists of nuclear-encoded protistan sequences. However,
        metazoans, land plants, macrosporic fungi and eukaryotic organelles (mitochondrion,
        plastid and others) are also included because they are useful for the analysis
        of high-troughput sequencing data sets. Introns and putative chimeric sequences
        have been also carefully checked. Taxonomic assignation of sequences consists
        of eight unique taxonomic fields. In total, 136866 sequences are nuclear encoded,
        45708 (36 501 mitochondrial and 9657 chloroplastic) are from organelles, the
        remaining being putative chimeric sequences. The website allows the users
        to download sequences from the entire and partial databases (including representative
        sequences after clustering at a given level of similarity). Different web
        tools also allow searches by sequence similarity. The presence of both rRNA
        and rDNA sequences, taking into account introns (crucial for eukaryotic sequences),
        a normalized eight terms ranked-taxonomy and updates of new GenBank releases
        were made possible by a long-term collaboration between experts in taxonomy
        and computer scientists. © The Author(s) 2012.
      authors:
      - name: Guillou L.
      - name: Bachar D.
      - name: Audic S.
      - name: Bass D.
      - name: Berney C.
      - name: Bittner L.
      - name: Boutte C.
      - name: Burgaud G.
      - name: De Vargas C.
      - name: Decelle J.
      - name: Del Campo J.
      - name: Dolan J.R.
      - name: Dunthorn M.
      - name: Edvardsen B.
      - name: Holzmann M.
      - name: Kooistra W.H.C.F.
      - name: Lara E.
      - name: Le Bescot N.
      - name: Logares R.
      - name: Mahe F.
      - name: Massana R.
      - name: Montresor M.
      - name: Morard R.
      - name: Not F.
      - name: Pawlowski J.
      - name: Probert I.
      - name: Sauvadet A.-L.
      - name: Siano R.
      - name: Stoeck T.
      - name: Vaulot D.
      - name: Zimmermann P.
      - name: Christen R.
      citationCount: 1456
      date: '2013-01-01T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'The Protist Ribosomal Reference database (PR2): A catalog of unicellular
        eukaryote Small Sub-Unit rRNA sequences with curated taxonomy'
    note: null
    pmcid: null
    pmid: null
    type:
    - Primary
    version: null
  relation: []
  toolType:
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  - Web application
  topic:
  - term: Metabarcoding
    uri: http://edamontology.org/topic_4038
  validated: 0
  version:
  - 5.1.0
next: ?page=2
previous: null
