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  toolType:
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  topic:
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  - term: Genomics
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  - term: Genetics
    uri: http://edamontology.org/topic_3053
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  description: Evolutionary simulation framework that combines a powerful engine for
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    note: Run individual-based eco-evolutionary simulations with explicit genetics
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  - note: GitHub repository for SLiM
    type:
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  maturity: Mature
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  publication:
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    metadata:
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      authors: []
      citationCount: 541
      date: '2019-03-01T00:00:00Z'
      journal: Molecular Biology and Evolution
      title: 'SLiM 3: Forward Genetic Simulations Beyond the Wright-Fisher Model'
    note: 'B.C. Haller, P.W. Messer. (2019). SLiM 3: Forward genetic simulations beyond
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    pmid: '30517680'
    type:
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  - doi: 10.1093/molbev/msy237
    metadata:
      abstract: ''
      authors: []
      citationCount: 13
      date: '2019-05-01T00:00:00Z'
      journal: Molecular Biology and Evolution
      title: Evolutionary Modeling in SLiM 3 for Beginners
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    pmid: '30590560'
    type:
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  - doi: 10.1111/1755-0998.12968
    metadata:
      abstract: ''
      authors: []
      citationCount: 123
      date: '2019-03-01T00:00:00Z'
      journal: Molecular Ecology Resources
      title: Tree-sequence recording in SLiM opens new horizons for forward-time simulation
        of whole genomes
    note: B.C. Haller, J. Galloway, J. Kelleher, P.W. Messer, P.L. Ralph. (2019).
      Tree-sequence recording in SLiM opens new horizons for forward-time simulation
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    pmid: '30565882'
    type:
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    version: '3.0'
  - doi: 10.1101/2025.08.07.669155
    metadata: null
    note: 'BC Haller, PL Ralph, PW Messer. (2025). SLiM 5: Eco-evolutionary simulations
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    pmid: '40832315'
    type:
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    version: '5.0'
  - doi: 10.1086/723601
    metadata:
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      citationCount: 124
      date: '2023-05-01T00:00:00Z'
      journal: American Naturalist
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    pmid: '37130229'
    type:
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    version: '4.0'
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  toolType:
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  topic:
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  - term: Molecular interactions, pathways and networks
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  - term: Genetic variation
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  - term: Evolutionary biology
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  validated: 0
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  additionDate: '2025-09-03T07:50:00.879412Z'
  biotoolsCURIE: biotools:cats-rf
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  language:
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  license: MIT
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  - term: Biology
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  description: Atomic Charge Calculator II (ACC II) is a web application for fast
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    note: Calculation of partial atomic charges
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  - C++
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      journal: Nucleic Acids Research
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    pmcid: PMC7319571
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  toolType:
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  topic:
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  validated: 0
  version:
  - '2'
- accessibility: Open access
  additionDate: '2019-02-13T17:01:40Z'
  biotoolsCURIE: biotools:Jalview
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  confidence_flag: null
  cost: Free of charge
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    fundrefid: null
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    name: Jim Procter
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  description: Jalview is a free cross-platform program for multiple sequence alignment
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    and explore molecular structures and annotation.
  documentation:
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  - note: null
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  - note: Binaries for all platforms
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      - term: FASTA-aln
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    note: 'Other Input formats:

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      PFAM (.pfam);

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      Other Output formats:

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

      Jalview Project File (.jvp);'
    operation:
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      - term: Stockholm format
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      - term: FASTA
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      - term: PHYLIP format
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      - term: BLC
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      - term: Pileup
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      - term: ClustalW format
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      - term: HTML
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      - term: EPS
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      - term: SVG
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      - term: Format
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  license: GPL-3.0
  link:
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  - note: null
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  - note: null
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  - note: YouTube training videos
    type:
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    url: https://www.youtube.com/channel/UCIjpnvZB770yz7ftbrJ0tfw
  maturity: Mature
  name: Jalview
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  otherID: []
  owner: ben_s
  publication:
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    metadata:
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      authors: []
      citationCount: 7499
      date: '2009-05-07T00:00:00Z'
      journal: Bioinformatics
      title: Jalview Version 2-A multiple sequence alignment editor and analysis workbench
    note: null
    pmcid: PMC2672624
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    type: []
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    type: uses
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    type: uses
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  toolType:
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  topic:
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  validated: 1
  version:
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  additionDate: '2025-09-03T08:01:20.173602Z'
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  description: CATS-rb evaluates transcriptome assemblies using the reference genome
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  description: Output reads with low quality bases trimmed (at the extremities) or
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    note: null
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      - name: Rasche E.
      - name: Soranzo N.
      - name: Turaga N.
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    note: null
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  description: Detect duplicate reads. Outputs a list of read names corresponding
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      - name: Guerler A.
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      - name: Rasche E.
      - name: Soranzo N.
      - name: Turaga N.
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  - term: Nucleic acids
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        computational power. This has led to an acute crisis in life sciences, as
        researchers without informatics training attempt to perform computation-dependent
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  - doi: 10.7490/f1000research.1114334.1
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  additionDate: '2016-12-19T14:27:26Z'
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      format:
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    metadata:
      abstract: High-throughput data production technologies, particularly ‘next-generation’
        DNA sequencing, have ushered in widespread and disruptive changes to biomedical
        research. Making sense of the large datasets produced by these technologies
        requires sophisticated statistical and computational methods, as well as substantial
        computational power. This has led to an acute crisis in life sciences, as
        researchers without informatics training attempt to perform computation-dependent
        analyses. Since 2005, the Galaxy project has worked to address this problem
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        non experts. Galaxy seeks to make data-intensive research more accessible,
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      - name: Baker D.
      - name: van den Beek M.
      - name: Blankenberg D.
      - name: Bouvier D.
      - name: Cech M.
      - name: Chilton J.
      - name: Clements D.
      - name: Coraor N.
      - name: Eberhard C.
      - name: Gruning B.
      - name: Guerler A.
      - name: Hillman-Jackson J.
      - name: Kuster G.V.
      - name: Rasche E.
      - name: Soranzo N.
      - name: Turaga N.
      - name: Taylor J.
      - name: Nekrutenko A.
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      date: '2016-07-08T00:00:00Z'
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  description: EssSubgraph is a model algorithm that integrates omics data and network
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  description: a Python package library that allow to model and detect macromolecular
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    metadata:
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        System Finder (MacSyFinder) is a program that uses these properties to model
        and then annotate cellular functions in microbial genomes. This is done by
        integrating the identification of each individual gene at the level of the
        molecular system. We hereby present a major release of MacSyFinder (version
        2) coded in Python 3. The code was improved and rationalized to facilitate
        future maintainability. Several new features were added to allow more flexible
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        CONJscan to identify conjugative systems, and CasFinder to identify CRISPR
        associated proteins. MacSyFinder and the updated models are available at:
        https://github.com/gem-pasteur/macsyfinder.'
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      - name: Denise R.
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  description: This is a computational workflow for detecting coordinates of microbial-like
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    accepts a reference genome in FASTA-format and outputs coordinates of microbial-like
    (human-like) regions in BED-format. The workflow builds a Bowtie2 index of the
    reference genome and aligns pre-computed microbial (GTDB v.214 or NCBI RefSeq
    release 213) or human (hg38) pseudo-reads to the reference, then custom scripts
    are used for detection of the positions of covered regions and quantification
    of most abundant microbial species, the latter is only when screening for microbial-like
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  publication:
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    metadata: null
    note: null
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    type: []
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  additionDate: '2024-04-18T08:31:46.459964Z'
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  documentation:
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  publication:
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    metadata:
      abstract: 'Motivation: Hi-C is gaining prominence as a method for mapping genome
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        data, efficient tools for processing Hi-C datasets at different resolutions
        are crucial. Over the past decade, the. hic and Cooler file formats have become
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  elixir_badge: 0
  function: []
  homepage: https://macpepdb.cubimed.rub.de/
  homepage_status: 0
  language:
  - Rust
  - JavaScript
  - Other
  lastUpdate: '2025-07-31T09:03:29.192901Z'
  license: null
  link:
  - note: Backend implementation written in Rust / Axum
    type:
    - Repository
    url: https://github.com/medbioinf/macpepdb
  - note: Frontend implementation written in Rust / Dioxus
    type:
    - Repository
    url: https://github.com/medbioinf/macpepdb-frontend
  maturity: Mature
  name: MaCPepDB - Mass Centric Peptide Database
  operatingSystem: []
  otherID: []
  owner: di_hardt
  publication:
  - doi: 10.1021/acs.jproteome.0c00967
    metadata:
      abstract: Protein sequence databases play a crucial role in the majority of
        the currently applied mass-spectrometry-based proteomics workflows. Here UniProtKB
        serves as one of the major sources, as it combines the information of several
        smaller databases and enriches the entries with additional biological information.
        For the identification of peptides in a sample by tandem mass spectra, as
        generated by data-dependent acquisition, protein sequence databases provide
        the basis for most spectrum identification search engines. In addition, for
        targeted proteomics approaches like selected reaction monitoring (SRM) and
        parallel reaction monitoring (PRM), knowledge of the peptide sequences, their
        masses, and whether they are unique for a protein is essential. Because most
        bottom-up proteomics approaches use trypsin to cleave the proteins in a sample,
        the tryptic peptides contained in a protein database are of great interest.
        We present a database, called MaCPepDB (mass-centric peptide database), that
        consists of the complete tryptic digest of the Swiss-Prot and TrEMBL parts
        of UniProtKB. This database is especially designed to not only allow queries
        of peptide sequences and return the respective information about connected
        proteins and thus whether a peptide is unique but also allow queries of specific
        masses of peptides or precursors of MS/MS spectra. Furthermore, posttranslational
        modifications can be considered in a query as well as different mass deviations
        for posttranslational modifications. Hence the database can be used by a sequence
        query not only to, for example, check in which proteins of the UniProt database
        a tryptic peptide can be found but also to find possibly interfering peptides
        in PRM/SRM experiments using the mass query. The complete database contains
        currently 5 939 244 990 peptides from 185 561 610 proteins (UniProt version
        2020_03), for which a single query usually takes less than 1 s. For easy exploration
        of the data, a web interface was developed. A REST application programming
        interface (API) for programmatic and workflow access is also available at
        https://macpepdb.mpc.rub.de.
      authors:
      - name: Uszkoreit J.
      - name: Winkelhardt D.
      - name: Barkovits K.
      - name: Wulf M.
      - name: Roocke S.
      - name: Marcus K.
      - name: Eisenacher M.
      citationCount: 9
      date: '2021-04-02T00:00:00Z'
      journal: Journal of Proteome Research
      title: 'MaCPepDB: A Database to Quickly Access All Tryptic Peptides of the UniProtKB'
    note: null
    pmcid: null
    pmid: '33724838'
    type:
    - Primary
    version: '1.0'
  relation: []
  toolType:
  - Database portal
  topic:
  - term: Proteomics
    uri: http://edamontology.org/topic_0121
  validated: 0
  version:
  - 3.0.0
- accessibility: Open access
  additionDate: '2019-11-05T10:40:37Z'
  biotoolsCURIE: biotools:WheatIS
  biotoolsID: WheatIS
  collectionID:
  - elixir-fr-sdp-2019
  - URGI
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: urgi-support@inrae.fr
    fundrefid: null
    gridid: null
    name: Support service
    note: null
    orcidid: null
    rorid: null
    typeEntity: null
    typeRole:
    - Primary contact
    - Support
    url: null
  description: "This project aims at building an International Wheat Information System\
    \ (WheatIS) to support the wheat research community. The main objective is to\
    \ provide a single-access web based system to access to the available data resources\
    \ and bioinformatics tools. The web portal indexes and makes findable any kind\
    \ of data from wheat related species. \nThe WheatIS search is an implementation\
    \ of DataDiscovery."
  documentation:
  - note: null
    type:
    - General
    url: https://urgi.versailles.inra.fr/wheatis/about
  - note: null
    type:
    - Contributions policy
    url: https://urgi.versailles.inra.fr/wheatis/join
  - note: null
    type:
    - Terms of use
    url: https://urgi.versailles.inra.fr/wheatis/legal
  - note: null
    type:
    - User manual
    url: https://urgi.versailles.inra.fr/wheatis/help
  download: []
  editPermission:
    authors:
    - nfrancillon
    - raphael.flores
    - cmichotey
    type: group
  elixirCommunity: []
  elixirNode:
  - France
  elixirPlatform:
  - Tools
  - Data
  - Interoperability
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Keyword
        uri: http://edamontology.org/data_0968
      format: []
    - data:
        term: Ontology data
        uri: http://edamontology.org/data_2353
      format: []
    note: null
    operation:
    - term: Database search
      uri: http://edamontology.org/operation_2421
    - term: Relation extraction
      uri: http://edamontology.org/operation_3625
    - term: Indexing
      uri: http://edamontology.org/operation_0227
    - term: Information retrieval
      uri: http://edamontology.org/operation_3908
    output:
    - data:
        term: Database search results
        uri: http://edamontology.org/data_2080
      format: []
    - data:
        term: Data reference
        uri: http://edamontology.org/data_2093
      format: []
    - data:
        term: Identifier
        uri: http://edamontology.org/data_0842
      format: []
  homepage: https://urgi.versailles.inrae.fr/wheatis/
  homepage_status: 0
  language: []
  lastUpdate: '2025-07-29T13:42:41.391722Z'
  license: BSD-3-Clause
  link:
  - note: WheatIS website
    type:
    - Other
    url: http://www.wheatis.org/
  maturity: Mature
  name: WheatIS
  operatingSystem: []
  otherID: []
  owner: jison
  publication:
  - doi: 10.1186/s13059-018-1491-4
    metadata:
      abstract: © 2018 The Author(s).The Wheat@URGI portal has been developed to provide
        the international community of researchers and breeders with access to the
        bread wheat reference genome sequence produced by the International Wheat
        Genome Sequencing Consortium. Genome browsers, BLAST, and InterMine tools
        have been established for in-depth exploration of the genome sequence together
        with additional linked datasets including physical maps, sequence variations,
        gene expression, and genetic and phenomic data from other international collaborative
        projects already stored in the GnpIS information system. The portal provides
        enhanced search and browser features that will facilitate the deployment of
        the latest genomics resources in wheat improvement.
      authors:
      - name: Alaux M.
      - name: Rogers J.
      - name: Letellier T.
      - name: Flores R.
      - name: Alfama F.
      - name: Pommier C.
      - name: Mohellibi N.
      - name: Durand S.
      - name: Kimmel E.
      - name: Michotey C.
      - name: Guerche C.
      - name: Loaec M.
      - name: Laine M.
      - name: Steinbach D.
      - name: Choulet F.
      - name: Rimbert H.
      - name: Leroy P.
      - name: Guilhot N.
      - name: Salse J.
      - name: Feuillet C.
      - name: Paux E.
      - name: Eversole K.
      - name: Adam-Blondon A.-F.
      - name: Quesneville H.
      citationCount: 88
      date: '2018-08-17T00:00:00Z'
      journal: Genome Biology
      title: Linking the International Wheat Genome Sequencing Consortium bread wheat
        reference genome sequence to wheat genetic and phenomic data
    note: Alaux M, Rogers J, Letellier T, Flores R, Alfama  F, Pommier C, Mohellibi
      N, Durand S, Kimmel E, Michotey C, Guerche C, Loaec M, Lainé M, Steinbach D,
      Choulet F, Rimbert H, Leroy P, Guilhot N, Salse J, Feuillet C, International
      Wheat Genome Sequencing Consortium, Paux E, Eversole K, Adam-Blondon A-F, Quesneville
      H (2018) Linking the International Wheat Genome Sequencing Consortium bread
      wheat reference genome sequence to wheat genetic and phenomic data. Genome Biology,
      19:111
    pmcid: null
    pmid: null
    type:
    - Primary
    version: null
  relation:
  - biotoolsID: gnpis
    type: uses
  - biotoolsID: DataDiscovery
    type: uses
  toolType:
  - Web API
  - Web application
  - Web service
  - Database portal
  topic:
  - term: Plant biology
    uri: http://edamontology.org/topic_0780
  - term: Ecology
    uri: http://edamontology.org/topic_0610
  - term: Biological databases
    uri: http://edamontology.org/topic_3071
  - term: Bioinformatics
    uri: http://edamontology.org/topic_0091
  - term: Agricultural science
    uri: http://edamontology.org/topic_3810
  validated: 1
  version: []
- accessibility: Restricted access
  additionDate: '2017-03-23T14:24:24Z'
  biotoolsCURIE: biotools:gnpis
  biotoolsID: gnpis
  collectionID:
  - elixir-fr-sdp-2019
  - Animal and Crop Genomics
  confidence_flag: null
  cost: null
  credit:
  - email: urgi-contact@versailles.inra.fr
    fundrefid: null
    gridid: null
    name: null
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  description: A multispecies integrative information system dedicated to plant and
    fungi pests.. It allows researchers to access genetic, phenotypic and genomic
    data. It is used by both large international projects and the French National
    Research Institute for Agriculture, Food and Environment
  documentation:
  - note: null
    type:
    - General
    url: https://urgi.versailles.inra.fr/gnpis/
  download: []
  editPermission:
    authors:
    - urgi-contact
    - animalandcropgenomics
    - nfrancillon
    - cmichotey
    type: group
  elixirCommunity: []
  elixirNode:
  - France
  elixirPlatform:
  - Tools
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Genome visualisation
      uri: http://edamontology.org/operation_3208
    - term: Data handling
      uri: http://edamontology.org/operation_2409
    - term: Indexing
      uri: http://edamontology.org/operation_0227
    - term: Query and retrieval
      uri: http://edamontology.org/operation_0224
    - term: Ontology visualisation
      uri: http://edamontology.org/operation_3559
    output:
    - data:
        term: Sequence variations
        uri: http://edamontology.org/data_3498
      format: []
    - data:
        term: Sequence set
        uri: http://edamontology.org/data_0850
      format: []
    - data:
        term: Sequence features
        uri: http://edamontology.org/data_1255
      format: []
    - data:
        term: Sequence
        uri: http://edamontology.org/data_2044
      format: []
    - data:
        term: Ontology data
        uri: http://edamontology.org/data_2353
      format: []
    - data:
        term: Database search results
        uri: http://edamontology.org/data_2080
      format: []
    - data:
        term: Genotype/phenotype report
        uri: http://edamontology.org/data_0920
      format: []
    - data:
        term: Identifier
        uri: http://edamontology.org/data_0842
      format: []
  homepage: https://urgi.versailles.inrae.fr/gnpis
  homepage_status: 0
  language:
  - JavaScript
  - C#
  lastUpdate: '2025-07-29T13:42:38.871501Z'
  license: CC-BY-4.0
  link: []
  maturity: Mature
  name: Genetic and Genomic Information System (GnpIS)
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: cpommier
  publication:
  - doi: 10.1093/database/bat058
    metadata:
      abstract: Data integration is a key challenge for modern bioinformatics. It
        aims to provide biologists with tools to explore relevant data produced by
        different studies. Large-scale international projects can generate lots of
        heterogeneous and unrelated data. The challenge is to integrate this information
        with other publicly available data. Nucleotide sequencing throughput has been
        improved with new technologies; this increases the need for powerful information
        systems able to store, manage and explore data. GnpIS is a multispecies integrative
        information system dedicated to plant and fungi pests. It bridges genetic
        and genomic data, allowing researchers access to both genetic information
        (e.g. genetic maps, quantitative trait loci, markers, single nucleotide polymorphisms,
        germplasms and genotypes) and genomic data (e.g. genomic sequences, physical
        maps, genome annotation and expression data) for species of agronomical interest.
        GnpIS is used by both large international projects and plant science departments
        at the French National Institute for Agricultural Research. Here, we illustrate
        its use. © The Author(s) 2013. Published by Oxford University Press.
      authors:
      - name: Steinbach D.
      - name: Alaux M.
      - name: Amselem J.
      - name: Choisne N.
      - name: Durand S.
      - name: Flores R.
      - name: Keliet A.-O.
      - name: Kimmel E.
      - name: Lapalu N.
      - name: Luyten I.
      - name: Michotey C.
      - name: Mohellibi N.
      - name: Pommier C.
      - name: Reboux S.
      - name: Valdenaire D.
      - name: Verdelet D.
      - name: Quesneville H.
      citationCount: 42
      date: '2013-12-01T00:00:00Z'
      journal: Database
      title: 'GnpIS: An information system to integrate genetic and genomic data from
        plants and fungi'
    note: null
    pmcid: PMC3746681
    pmid: '23959375'
    type:
    - Primary
    version: null
  - doi: 10.1007/978-1-4939-6658-5_5
    metadata:
      abstract: GnpIS is an information system designed to help scientists working
        on plants and fungi to decipher the molecular and genetic architecture of
        trait variations by facilitating the navigation through genetic, genomic,
        and phenotypic information. The purpose of the present chapter is to illustrate
        how users can (1) explore datasets from phenotyping experiments in order to
        build new datasets for studying genotype × environment interactions in traits,
        (2) browse into the results of other genetic analysis data such as GWAS to
        generate or check working hypothesis about candidate genes or to identify
        important alleles and germplasms for breeding programs, and (3) explore the
        polymorphism in specific area of the genome using InterMine, JBrowse tools
        embedded in the GnpIS information system.
      authors:
      - name: Adam-Blondon A.-F.
      - name: Alaux M.
      - name: Durand S.
      - name: Letellier T.
      - name: Merceron G.
      - name: Mohellibi N.
      - name: Pommier C.
      - name: Steinbach D.
      - name: Alfama F.
      - name: Amselem J.
      - name: Charruaud D.
      - name: Choisne N.
      - name: Flores R.
      - name: Guerche C.
      - name: Jamilloux V.
      - name: Kimmel E.
      - name: Lapalu N.
      - name: Loaec M.
      - name: Michotey C.
      - name: Quesneville H.
      citationCount: 1
      date: '2017-01-01T00:00:00Z'
      journal: Methods in Molecular Biology
      title: Mining plant genomic and genetic data using the gnpis information system
    note: null
    pmcid: null
    pmid: '27987166'
    type:
    - Primary
    version: null
  - doi: 10.1038/hortres.2016.56
    metadata:
      abstract: Viticulture, like other fields of agriculture, is currently facing
        important challenges that will be addressed only through sustained, dedicated
        and coordinated research. Although the methods used in biology have evolved
        tremendously in recent years and now involve the routine production of large
        data sets of varied nature, in many domains of study, including grapevine
        research, there is a need to improve the findability, accessibility, interoperability
        and reusability (FAIR-ness) of these data. Considering the heterogeneous nature
        of the data produced, the transnational nature of the scientific community
        and the experience gained elsewhere, we have formed an open working group,
        in the framework of the International Grapevine Genome Program (www.vitaceae.org),
        to construct a coordinated federation of information systems holding grapevine
        data distributed around the world, providing an integrated set of interfaces
        supporting advanced data modeling, rich semantic integration and the next
        generation of data mining tools. To achieve this goal, it will be critical
        to develop, implement and adopt appropriate standards for data annotation
        and formatting. The development of this system, the GrapeIS, linking genotypes
        to phenotypes, and scientific research to agronomical and oeneological data,
        should provide new insights into grape biology, and allow the development
        of new varieties to meet the challenges of biotic and abiotic stress, environmental
        change, and consumer demand.
      authors:
      - name: Adam-Blondon A.-F.
      - name: Alaux M.
      - name: Pommier C.
      - name: Cantu D.
      - name: Cheng Z.-M.
      - name: Cramer G.
      - name: Davies C.
      - name: Delrot S.
      - name: Deluc L.
      - name: Di Gaspero G.
      - name: Grimplet J.
      - name: Fennell A.
      - name: Londo J.
      - name: Kersey P.
      - name: Mattivi F.
      - name: Naithani S.
      - name: Neveu P.
      - name: Nikolski M.
      - name: Pezzotti M.
      - name: Reisch B.
      - name: Topfer R.
      - name: Vivier M.
      - name: Ware D.
      - name: Quesneville H.
      citationCount: 37
      date: '2016-11-23T00:00:00Z'
      journal: Horticulture Research
      title: Towards an open grapevine information system
    note: null
    pmcid: PMC5120350
    pmid: '27917288'
    type:
    - Other
    version: null
  - doi: 10.3835/plantgenome2015.06.0038
    metadata:
      abstract: The genome sequences of many important Triticeae species, including
        bread wheat (Triticum aestivum L.) and barley (Hordeum vulgare L.), remained
        uncharacterized for a long time because their high repeat content, large sizes,
        and polyploidy. As a result of improvements in sequencing technologies and
        novel analyses strategies, several of these have recently been deciphered.
        These efforts have generated new insights into Triticeae biology and genome
        organization and have important implications for downstream usage by breeders,
        experimental biologists, and comparative genomicists. transPLANT (http://www.transplantdb.eu)
        is an EU-funded project aimed at constructing hardware, software, and data
        infrastructure for genome-scale research in the life sciences. Since the Triticeae
        data are intrinsically complex, heterogenous, and distributed, the transPLANT
        consortium has undertaken efforts to develop common data formats and tools
        that enable the exchange and integration of data from distributed resources.
        Here we present an overview of the individual Triticeae genome resources hosted
        by transPLANT partners, introduce the objectives of transPLANT, and outline
        common developments and interfaces supporting integrated data access.
      authors:
      - name: Spannagl M.
      - name: Alaux M.
      - name: Lange M.
      - name: Bolser D.M.
      - name: Bader K.C.
      - name: Letellier T.
      - name: Kimmel E.
      - name: Flores R.
      - name: Pommier C.
      - name: Kerhornou A.
      - name: Walts B.
      - name: Nussbaumer T.
      - name: Grabmuller C.
      - name: Chen J.
      - name: Colmsee C.
      - name: Beier S.
      - name: Mascher M.
      - name: Schmutzer T.
      - name: Arend D.
      - name: Thanki A.
      - name: Ramirez-Gonzalez R.
      - name: Ayling M.
      - name: Ayling S.
      - name: Caccamo M.
      - name: Mayer K.F.X.
      - name: Scholz U.
      - name: Steinbach D.
      - name: Quesneville H.
      - name: Kersey P.J.
      citationCount: 6
      date: '2016-03-01T00:00:00Z'
      journal: Plant Genome
      title: TransPLANT resources for triticeae genomic data
    note: null
    pmcid: null
    pmid: '27898761'
    type:
    - Primary
    version: null
  relation: []
  toolType:
  - Web application
  - Database portal
  topic:
  - term: Genomics
    uri: http://edamontology.org/topic_0622
  - term: Plant biology
    uri: http://edamontology.org/topic_0780
  - term: Genetics
    uri: http://edamontology.org/topic_3053
  - term: Genotype and phenotype
    uri: http://edamontology.org/topic_0625
  validated: 1
  version:
  - '18.2'
- accessibility: null
  additionDate: '2019-11-27T10:47:08Z'
  biotoolsCURIE: biotools:OakMine
  biotoolsID: OakMine
  collectionID: []
  confidence_flag: null
  cost: Free of charge
  credit: []
  description: Quercus robur annotation database
  documentation:
  - note: null
    type:
    - API documentation
    url: http://intermine.readthedocs.org/en/latest/web-services/
  - note: null
    type:
    - User manual
    url: https://flymine.readthedocs.io/en/latest/
  download: []
  editPermission:
    authors:
    - cmichotey
    type: group
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Sequence features
        uri: http://edamontology.org/data_1255
      format: []
    - data:
        term: Ontology data
        uri: http://edamontology.org/data_2353
      format: []
    note: null
    operation:
    - term: Data retrieval
      uri: http://edamontology.org/operation_2422
    - term: Visualisation
      uri: http://edamontology.org/operation_0337
    - term: Gene-set enrichment analysis
      uri: http://edamontology.org/operation_2436
    - term: Query and retrieval
      uri: http://edamontology.org/operation_0224
    output:
    - data:
        term: Over-representation data
        uri: http://edamontology.org/data_3753
      format: []
    - data:
        term: Query script
        uri: http://edamontology.org/data_3786
      format: []
    - data:
        term: Sequence features
        uri: http://edamontology.org/data_1255
      format: []
  homepage: https://urgi.versailles.inra.fr/OakMine_PM1N
  homepage_status: 0
  language:
  - R
  - Ruby
  - Java
  - Python
  - JavaScript
  - Perl
  lastUpdate: '2025-07-29T13:42:35.424110Z'
  license: LGPL-2.1
  link:
  - note: null
    type:
    - Software catalogue
    url: https://registry.intermine.org
  - note: null
    type:
    - Other
    url: http://intermine.org
  maturity: Mature
  name: OakMine
  operatingSystem:
  - Linux
  - Mac
  otherID: []
  owner: InterMine
  publication:
  - doi: 10.1093/bioinformatics/bts577
    metadata:
      abstract: InterMine is an open-source data warehouse system that facilitates
        the building of databases with complex data integration requirements and a
        need for a fast customizable query facility. Using InterMine, large biological
        databases can be created from a range of heterogeneous data sources, and the
        extensible data model allows for easy integration of new data types. The analysis
        tools include a flexible query builder, genomic region search and a library
        of 'widgets' performing various statistical analyses. The results can be exported
        in many commonly used formats. InterMine is a fully extensible framework where
        developers can add new tools and functionality. Additionally, there is a comprehensive
        set of web services, for which client libraries are provided in five commonly
        used programming languages. © The Author 2012. Published by Oxford University
        Press. All rights reserved.
      authors:
      - name: Smith R.N.
      - name: Aleksic J.
      - name: Butano D.
      - name: Carr A.
      - name: Contrino S.
      - name: Hu F.
      - name: Lyne M.
      - name: Lyne R.
      - name: Kalderimis A.
      - name: Rutherford K.
      - name: Stepan R.
      - name: Sullivan J.
      - name: Wakeling M.
      - name: Watkins X.
      - name: Micklem G.
      citationCount: 202
      date: '2012-12-01T00:00:00Z'
      journal: Bioinformatics
      title: 'InterMine: A flexible data warehouse system for the integration and
        analysis of heterogeneous biological data'
    note: null
    pmcid: PMC3516146
    pmid: '23023984'
    type:
    - Other
    version: null
  relation: []
  toolType:
  - Web application
  - Web service
  - Database portal
  topic:
  - term: Data management
    uri: http://edamontology.org/topic_3071
  - term: Genomics
    uri: http://edamontology.org/topic_0622
  - term: Proteomics
    uri: http://edamontology.org/topic_0121
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  description: An integrated database for grapevine data
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  language:
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  - Java
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    metadata:
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        need for a fast customizable query facility. Using InterMine, large biological
        databases can be created from a range of heterogeneous data sources, and the
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        set of web services, for which client libraries are provided in five commonly
        used programming languages. © The Author 2012. Published by Oxford University
        Press. All rights reserved.
      authors:
      - name: Smith R.N.
      - name: Aleksic J.
      - name: Butano D.
      - name: Carr A.
      - name: Contrino S.
      - name: Hu F.
      - name: Lyne M.
      - name: Lyne R.
      - name: Kalderimis A.
      - name: Rutherford K.
      - name: Stepan R.
      - name: Sullivan J.
      - name: Wakeling M.
      - name: Watkins X.
      - name: Micklem G.
      citationCount: 202
      date: '2012-12-01T00:00:00Z'
      journal: Bioinformatics
      title: 'InterMine: A flexible data warehouse system for the integration and
        analysis of heterogeneous biological data'
    note: null
    pmcid: PMC3516146
    pmid: '23023984'
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  toolType:
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  topic:
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  - term: Genomics
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  - term: Proteomics
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  validated: 1
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  additionDate: '2019-11-27T10:47:40Z'
  biotoolsCURIE: biotools:WheatMine
  biotoolsID: WheatMine
  collectionID: []
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  cost: Free of charge
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  description: Wheat IWGSC RefSeq v1.0
  documentation:
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    type:
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  - note: null
    type:
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  homepage: https://urgi.versailles.inra.fr/WheatMine
  homepage_status: 0
  language:
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  - JavaScript
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  lastUpdate: '2025-07-29T13:42:33.209390Z'
  license: LGPL-2.1
  link:
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  maturity: Mature
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  publication:
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    metadata:
      abstract: InterMine is an open-source data warehouse system that facilitates
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        need for a fast customizable query facility. Using InterMine, large biological
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        extensible data model allows for easy integration of new data types. The analysis
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        set of web services, for which client libraries are provided in five commonly
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        Press. All rights reserved.
      authors:
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      - name: Aleksic J.
      - name: Butano D.
      - name: Carr A.
      - name: Contrino S.
      - name: Hu F.
      - name: Lyne M.
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      - name: Stepan R.
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      - name: Micklem G.
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      date: '2012-12-01T00:00:00Z'
      journal: Bioinformatics
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    note: null
    pmcid: PMC3516146
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  - term: Genomics
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  - term: Proteomics
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  validated: 1
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  additionDate: '2025-07-23T10:24:09.622930Z'
  biotoolsCURIE: biotools:xnatpy
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  confidence_flag: tool
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  description: Python package to interact with the XNAT REST API in a python data-science
    way
  documentation:
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    type:
    - General
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  download:
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    type: Software package
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    version: null
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    input: []
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    operation:
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  language:
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  lastUpdate: '2025-07-24T08:55:06.000976Z'
  license: Apache-2.0
  link:
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    url: https://gitlab.com/radiology/infrastructure/xnatpy/
  - note: null
    type:
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  - note: null
    type:
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    url: https://pypi.org/project/xnat/
  - note: null
    type:
    - Software catalogue
    url: https://anaconda.org/conda-forge/xnat
  maturity: Mature
  name: XNATpy
  operatingSystem:
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  - Linux
  - Mac
  otherID: []
  owner: hachterberg
  publication: []
  relation:
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    type: usedBy
  - biotoolsID: xnat
    type: uses
  toolType:
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  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
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- accessibility: Open access
  additionDate: '2025-07-24T08:48:17.637773Z'
  biotoolsCURIE: biotools:xnat
  biotoolsID: xnat
  collectionID:
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  confidence_flag: tool
  cost: Free of charge
  credit:
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    fundrefid: null
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    name: Daniel Marcus
    note: null
    orcidid: https://orcid.org/0000-0001-5662-5358
    rorid: null
    typeEntity: Person
    typeRole:
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    url: https://profiles.wustl.edu/en/persons/daniel-marcus
  description: XNAT is an open source imaging informatics platform developed by the
    Neuroinformatics Research Group at Washington University. XNAT was originally
    developed at Washington University in the Buckner Lab, which is now located at
    Harvard University. It facilitates common management, productivity, and quality
    assurance tasks for imaging and associated data. Thanks to its extensibility,
    XNAT can be used to support a wide range of imaging-based projects.
  documentation:
  - note: null
    type:
    - User manual
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  - note: null
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  language:
  - Java
  lastUpdate: '2025-07-24T08:53:51.609723Z'
  license: BSD-2-Clause
  link:
  - note: null
    type:
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  - note: null
    type:
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  - Windows
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  otherID: []
  owner: hachterberg
  publication:
  - doi: 10.1385/ni:5:1:11
    metadata:
      abstract: The Extensible Neuroimaging Archive Toolkit (XNAT) is a software platform
        designed to facilitate common management and productivity tasks for neuroimaging
        and associated data. In particular, XNAT enables qualitycontrol procedures
        and provides secure access to and storage of data. XNAT follows a threetiered
        architecture that includes a data archive, user interface, and middleware
        engine. Data can be entered into the archive as XML or through data entry
        forms. Newly added data are stored in a virtual quarantine until an authorized
        user has validated it. XNAT subsequently maintains a history profile to track
        all changes made to the managed data. User access to the archive is provided
        by a secure web application. The web application provides a number of quality
        control and productivity features, including data entry forms, data-type-specific
        searches, searches that combine across data types, detailed reports, and listings
        of experimental data, upload/download tools, access to standard laboratory
        workflows, and administration and security tools. XNAT also includes an online
        image viewer that supports a number of common neuroimaging formats, including
        DICOM and Analyze. The viewer can be extended to support additional formats
        and to generate custom displays. By managing data with XNAT, laboratories
        are prepared to better maintain the long-term integrity of their data, to
        explore emergent relations across data types, and to share their data with
        the broader neuroimaging community. © Copyright 2007 by Humana Press Inc.
        All rights of any nature whatsoever are reserved.
      authors:
      - name: Marcus D.S.
      - name: Olsen T.R.
      - name: Ramaratnam M.
      - name: Buckner R.L.
      citationCount: 378
      date: '2007-03-01T00:00:00Z'
      journal: Neuroinformatics
      title: 'The extensible neuroimaging archive toolkit: An informatics platform
        for managing, exploring, and sharing neuroimaging data'
    note: null
    pmcid: null
    pmid: '17426351'
    type:
    - Primary
    version: null
  - doi: 10.1162/jocn.2009.21407
    metadata:
      abstract: The Open Access Series of Imaging Studies is a series of neuroimaging
        data sets that are publicly available for study and analysis. The present
        MRI data set consists of a longitudinal collection of 150 subjects aged 60
        to 96 years all acquired on the same scanner using identical sequences. Each
        subject was scanned on two or more visits, separated by at least 1 year for
        a total of 373 imaging sessions. Subjects were characterized using the Clinical
        Dementia Rating (CDR) as either nondemented or with very mild tomild Alzheimer's
        disease. Seventy-two of the subjects were characterized as nondemented throughout
        the study. Sixty-four of the included subjects were characterized as demented
        at the time of their initial visits and remained so for subsequent scans,
        including 51 individuals with CDR 0.5 similar level of impairment to individuals
        elsewhere considered to have "mild cognitive impairment." Another 14 subjects
        were characterized as nondemented at the time of their initial visit (CDR
        0) and were subsequently characterized as demented at a later visit (CDR >
        0). The subjects were all right-handed and include bothmen (n=62) and women
        (n = 88). For each scanning session, three or four individual T1-weighted
        MRI scans were obtained. Multiple withinsession acquisitions provide extremely
        high contrast to noise, making the data amenable to a wide range of analytic
        approaches including automated computational analysis. Automated calculation
        of whole-brain volume is presented to demonstrate use of the data for measuring
        differences associated with normal aging and Alzheimer's disease. © 2010 Massachusetts
        Institute of Technology.
      authors:
      - name: Marcus D.S.
      - name: Fotenos A.F.
      - name: Csernansky J.G.
      - name: Morris J.C.
      - name: Buckner R.L.
      citationCount: 461
      date: '2010-12-01T00:00:00Z'
      journal: Journal of Cognitive Neuroscience
      title: 'Open access series of imaging studies: Longitudinal MRI data in nondemented
        and demented older adults'
    note: null
    pmcid: PMC2895005
    pmid: '19929323'
    type:
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    type: usedBy
  toolType:
  - Web application
  - Web API
  topic:
  - term: Medical imaging
    uri: http://edamontology.org/topic_3384
  - term: MRI
    uri: http://edamontology.org/topic_3444
  - term: Bioimaging
    uri: http://edamontology.org/topic_3383
  - term: Tomography
    uri: http://edamontology.org/topic_3452
  - term: Data management
    uri: http://edamontology.org/topic_3071
  validated: 0
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- accessibility: Open access
  additionDate: '2025-07-15T16:04:03.513732Z'
  biotoolsCURIE: biotools:GevaertLab_DUNE
  biotoolsID: GevaertLab_DUNE
  collectionID: []
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: thomas.barba@inserm.fr
    fundrefid: null
    gridid: null
    name: Thomas Barba
    note: null
    orcidid: null
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    typeEntity: null
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    url: null
  description: A versatile neuroimaging encoder for extracting deep features from
    multisequence brain MRIs
  documentation:
  - note: null
    type:
    - Quick start guide
    url: https://github.com/gevaertlab/DUNE/blob/main/README.md
  download:
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    type: Source code
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  function:
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    note: Extracts features from
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      uri: http://edamontology.org/operation_3937
    output: []
  homepage: https://github.com/gevaertlab/DUNE
  homepage_status: 0
  language:
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  lastUpdate: '2025-07-15T16:04:03.516083Z'
  license: Apache-2.0
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  name: DUNE
  operatingSystem:
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  otherID: []
  owner: tbarba
  publication:
  - doi: 10.1101/2025.02.24.25322787
    metadata: null
    note: null
    pmcid: null
    pmid: null
    type: []
    version: null
  relation: []
  toolType:
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  topic:
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    uri: http://edamontology.org/topic_3384
  validated: 0
  version: []
- accessibility: Open access
  additionDate: '2025-06-30T08:52:48.500476Z'
  biotoolsCURIE: biotools:fair_eva_4_eucaim
  biotoolsID: fair_eva_4_eucaim
  collectionID:
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  confidence_flag: null
  cost: Free of charge
  credit:
  - email: null
    fundrefid: null
    gridid: null
    name: Fernando Aguilar
    note: This software started to be developed within IFCA-Advanced-Computing receives
      funding from the European Union’s Horizon 2020 research and innovation programme
      under grant agreement No 857647.
    orcidid: https://orcid.org/0000-0001-9462-4831
    rorid: null
    typeEntity: Person
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    url: null
  description: 'FAIR EVA: Evaluator, Validator & Advisor has been developed to check
    the FAIRness level of digital objects from different repositories or data portals.
    It requires the object identifier (preferably persistent and unique identifier)
    and the repository to check. It also provides a generic and agnostic way to check
    digital objects.'
  documentation:
  - note: Documentation for the main package, EUCAIM plugin specific documentation
      not included.
    type:
    - Quick start guide
    url: https://github.com/IFCA-Advanced-Computing/FAIR_eva/blob/main/docs/index.md
  download: []
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  license: Apache-2.0
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  maturity: Mature
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  operatingSystem:
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  otherID: []
  owner: davrodgon
  publication:
  - doi: 10.1038/s41597-023-02652-8
    metadata:
      abstract: The FAIR Principles are a set of good practices to improve the reproducibility
        and quality of data in an Open Science context. Different sets of indicators
        have been proposed to evaluate the FAIRness of digital objects, including
        datasets that are usually stored in repositories or data portals. However,
        indicators like those proposed by the Research Data Alliance are provided
        from a high-level perspective that can be interpreted and they are not always
        realistic to particular environments like multidisciplinary repositories.
        This paper describes FAIR EVA, a new tool developed within the European Open
        Science Cloud context that is oriented to particular data management systems
        like open repositories, which can be customized to a specific case in a scalable
        and automatic environment. It aims to be adaptive enough to work for different
        environments, repository software and disciplines, taking into account the
        flexibility of the FAIR Principles. As an example, we present DIGITAL.CSIC
        repository as the first target of the tool, gathering the particular needs
        of a multidisciplinary institution as well as its institutional repository.
      authors:
      - name: Aguilar Gomez F.
      - name: Bernal I.
      citationCount: 6
      date: '2023-12-01T00:00:00Z'
      journal: Scientific Data
      title: 'FAIR EVA: Bringing institutional multidisciplinary repositories into
        the FAIR picture'
    note: null
    pmcid: null
    pmid: null
    type: []
    version: null
  relation: []
  toolType:
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  topic:
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    uri: http://edamontology.org/topic_4012
  validated: 0
  version:
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- 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
  elixirCommunity: []
  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
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  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: '2025-02-26T14:07:27.855714Z'
  biotoolsCURIE: biotools:basico
  biotoolsID: basico
  collectionID:
  - de.NBI
  confidence_flag: null
  cost: Free of charge
  credit:
  - 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
    - Developer
    url: null
  description: "BASICO, a simplified Python interface to COPASI. It provides a set\
    \ of functions\n that allow to create, edit, simulate and analyze models in an\
    \ automated way"
  documentation: []
  download:
  - note: null
    type: Source code
    url: https://pypi.org/project/copasi-basico/
    version: null
  editPermission:
    authors: []
    type: private
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Kinetic model
        uri: http://edamontology.org/data_3241
      format:
      - term: CopasiML
        uri: http://edamontology.org/format_3239
      - term: SBML
        uri: http://edamontology.org/format_2585
      - term: SED-ML
        uri: http://edamontology.org/format_3685
      - term: COMBINE OMEX
        uri: http://edamontology.org/format_3686
    note: null
    operation:
    - term: Metabolic network modelling
      uri: http://edamontology.org/operation_3660
    - term: Pathway analysis
      uri: http://edamontology.org/operation_3928
    - term: Modelling and simulation
      uri: http://edamontology.org/operation_2426
    output:
    - data:
        term: Kinetic model
        uri: http://edamontology.org/data_3241
      format:
      - term: CopasiML
        uri: http://edamontology.org/format_3239
      - term: SBML
        uri: http://edamontology.org/format_2585
      - term: SED-ML
        uri: http://edamontology.org/format_3685
      - term: COMBINE OMEX
        uri: http://edamontology.org/format_3686
  homepage: https://basico.readthedocs.io/en/latest/
  homepage_status: 0
  language:
  - Python
  lastUpdate: '2025-07-07T11:16:29.397538Z'
  license: Artistic-2.0
  link: []
  maturity: Mature
  name: basico
  operatingSystem:
  - Mac
  - Linux
  - Windows
  otherID: []
  owner: frankbergmann
  publication:
  - doi: 10.21105/joss.05553
    metadata: null
    note: null
    pmcid: null
    pmid: null
    type: []
    version: null
  relation:
  - biotoolsID: copasi
    type: uses
  toolType:
  - Library
  - Script
  topic:
  - term: Systems biology
    uri: http://edamontology.org/topic_2259
  validated: 0
  version: []
- accessibility: null
  additionDate: '2025-07-07T09:04:03.787249Z'
  biotoolsCURIE: biotools:sqanti3
  biotoolsID: sqanti3
  collectionID: []
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: ana.conesa@csic.es
    fundrefid: null
    gridid: null
    name: Ana Conesa
    note: null
    orcidid: https://orcid.org/0000-0001-9597-311X
    rorid: null
    typeEntity: null
    typeRole: []
    url: null
  - email: pablo.atienza@csic.es
    fundrefid: null
    gridid: null
    name: Pablo Atienza
    note: Maintainer of SQANTI3
    orcidid: https://orcid.org/0009-0002-1093-693X
    rorid: null
    typeEntity: Person
    typeRole:
    - Maintainer
    url: null
  - email: fabian.robledo@csic.es
    fundrefid: null
    gridid: null
    name: Fabián Robledo
    note: Maintainer of SQANTI3 and ELIXIR-related contact
    orcidid: https://orcid.org/0009-0005-9047-3315
    rorid: null
    typeEntity: Person
    typeRole:
    - Maintainer
    url: null
  description: "SQANTI3 constitutes the first module of the Functional IsoTranscriptomics\
    \ (FIT) pipeline, which is an end-to-end strategy to perform isoform-level bioinformatics\
    \ analyses. \n\nThe SQANTI3 tool is designed to enable quality control and filtering\
    \ of long read-defined transcriptomes, which are often rich in artifacts and false-positive\
    \ isoforms. \n\nTherefore, a good curation of the transcriptome is indispensable\
    \ to proceed with FIT analysis and produce valid, biologically sound conclusions/hypothesis."
  documentation:
  - note: SQANTI3 main documentation resource
    type:
    - General
    url: https://github.com/ConesaLab/SQANTI3/wiki
  - note: null
    type:
    - Code of conduct
    url: https://github.com/ConesaLab/SQANTI3/blob/master/CODE_OF_CONDUCT.md
  - note: Command-line options and instructions for the QC submodule
    type:
    - Command-line options
    url: https://github.com/ConesaLab/SQANTI3/wiki/Running-SQANTI3-Quality-Control
  - note: Command-line options and instructions for the filter submodule
    type:
    - Command-line options
    url: https://github.com/ConesaLab/SQANTI3/wiki/Running-SQANTI3-filter
  - note: Command-line options and instructions for the rescue submodule
    type:
    - Command-line options
    url: https://github.com/ConesaLab/SQANTI3/wiki/Running-SQANTI3-rescue
  - note: Instructions to install and use sqanti, either in docker or apptainer containers
      or in a linux system
    type:
    - Installation instructions
    url: https://github.com/ConesaLab/SQANTI3/wiki/Dependencies-and-installation
  - note: Basic tutorial with examples to start using SQANTI3
    type:
    - Quick start guide
    url: https://github.com/ConesaLab/SQANTI3/wiki/Tutorial:-running-SQANTI3-on-an-example-dataset
  - note: Changelog and release notes for every version
    type:
    - Release notes
    url: https://github.com/ConesaLab/SQANTI3/releases
  - note: Citation instructions are on the end of the Github repository's main page
    type:
    - Citation instructions
    url: https://github.com/ConesaLab/SQANTI3?tab=readme-ov-file#how-to-cite-sqanti3
  - note: Benchmarking about the resources needed to run sqanti3 with multiple cores
    type:
    - Other
    url: https://github.com/ConesaLab/SQANTI3/wiki/SQANTI3-memory-requeriments-and-paralellization
  download:
  - note: null
    type: Downloads page
    url: https://github.com/ConesaLab/SQANTI3/releases
    version: null
  - note: Version 5.5 download link from github
    type: Binaries
    url: https://github.com/ConesaLab/SQANTI3/releases/download/v5.5/SQANTI3_v5.5.zip
    version: '5.5'
  editPermission:
    authors:
    - Fabian-RY
    type: group
  elixirCommunity: []
  elixirNode:
  - Spain
  elixirPlatform: []
  elixir_badge: 0
  function: []
  homepage: https://github.com/ConesaLab/SQANTI3
  homepage_status: 0
  language:
  - Python
  lastUpdate: '2025-07-07T09:35:33.280160Z'
  license: GPL-3.0
  link:
  - note: Github repository for source code access and download
    type:
    - Repository
    url: https://github.com/ConesaLab/SQANTI3
  maturity: Mature
  name: SQANTI3
  operatingSystem:
  - Linux
  otherID: []
  owner: Fabian-RY
  publication:
  - doi: 10.1038/s41592-024-02229-2
    metadata:
      abstract: SQANTI3 offers a flexible tool for quality control, curation and annotation
        of long-read RNA sequencing data. SQANTI3 is a tool designed for the quality
        control, curation and annotation of long-read transcript models obtained with
        third-generation sequencing technologies. Leveraging its annotation framework,
        SQANTI3 calculates quality descriptors of transcript models, junctions and
        transcript ends. With this information, potential artifacts can be identified
        and replaced with reliable sequences. Furthermore, the integrated functional
        annotation feature enables subsequent functional iso-transcriptomics analyses.
      authors:
      - name: Pardo-Palacios F.J.
      - name: Arzalluz-Luque A.
      - name: Kondratova L.
      - name: Salguero P.
      - name: Mestre-Tomas J.
      - name: Amorin R.
      - name: Estevan-Morio E.
      - name: Liu T.
      - name: Nanni A.
      - name: McIntyre L.
      - name: Tseng E.
      - name: Conesa A.
      citationCount: 41
      date: '2024-05-01T00:00:00Z'
      journal: Nature Methods
      title: 'SQANTI3: curation of long-read transcriptomes for accurate identification
        of known and novel isoforms'
    note: Publication of SQANTI3
    pmcid: null
    pmid: null
    type:
    - Primary
    version: '5.1'
  - doi: 10.1101/gr.222976.117
    metadata:
      abstract: High-throughput sequencing of full-length transcripts using long reads
        has paved the way for the discovery of thousands of novel transcripts, even
        in well-annotated mammalian species. The advances in sequencing technology
        have created a need for studies and tools that can characterize these novel
        variants. Here, we present SQANTI, an automated pipeline for the classification
        of long-read transcripts that can assess the quality of data and the preprocessing
        pipeline using 47 unique descriptors. We apply SQANTI to a neuronal mouse
        transcriptome using Pacific Biosciences (PacBio) long reads and illustrate
        how the tool is effective in characterizing and describing the composition
        of the full-length transcriptome. We perform extensive evaluation of ToFU
        PacBio transcripts by PCR to reveal that an important number of the novel
        transcripts are technical artifacts of the sequencing approach and that SQANTI
        quality descriptors can be used to engineer a filtering strategy to remove
        them. Most novel transcripts in this curated transcriptome are novel combinations
        of existing splice sites, resulting more frequently in novel ORFs than novel
        UTRs, and are enriched in both general metabolic and neural-specific functions.
        We show that these new transcripts have a major impact in the correct quantification
        of transcript levels by state-of-the-art short-read-based quantification algorithms.
        By comparing our iso-transcriptome with public proteomics databases, we find
        that alternative isoforms are elusive to proteogenomics detection. SQANTI
        allows the user to maximize the analytical outcome of long-read technologies
        by providing the tools to deliver quality-evaluated and curated full-length
        transcriptomes.
      authors:
      - name: Tardaguila M.
      - name: De La Fuente L.
      - name: Marti C.
      - name: Pereira C.
      - name: Pardo-Palacios F.J.
      - name: Del Risco H.
      - name: Ferrell M.
      - name: Mellado M.
      - name: Macchietto M.
      - name: Verheggen K.
      - name: Edelmann M.
      - name: Ezkurdia I.
      - name: Vazquez J.
      - name: Tress M.
      - name: Mortazavi A.
      - name: Martens L.
      - name: Rodriguez-Navarro S.
      - name: Moreno-Manzano V.
      - name: Conesa A.
      citationCount: 256
      date: '2018-03-01T00:00:00Z'
      journal: Genome Research
      title: 'SQANTI: Extensive characterization of long-read transcript sequences
        for quality control in full-length transcriptome identification and quantification'
    note: Original SQANTI publication
    pmcid: null
    pmid: null
    type:
    - Method
    version: null
  relation: []
  toolType:
  - Command-line tool
  topic:
  - term: Bioinformatics
    uri: http://edamontology.org/topic_0091
  - term: Gene transcripts
    uri: http://edamontology.org/topic_3512
  validated: 0
  version:
  - '5.5'
- accessibility: Open access
  additionDate: '2016-02-09T13:19:44Z'
  biotoolsCURIE: biotools:mirgen
  biotoolsID: mirgen
  collectionID:
  - UiO tools
  - ELIXIR-NO
  - ELIXIR-Norway
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: BastianFromm@gmail.com
    fundrefid: null
    gridid: null
    name: Bastian Fromm
    note: null
    orcidid: https://orcid.org/0000-0003-0352-3037
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    - Developer
    - Maintainer
    - Support
    url: null
  - email: kevin.j.peterson@dartmouth.edu
    fundrefid: null
    gridid: null
    name: Kevin J. Peterson
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    - Maintainer
    url: null
  - email: support@elixir.no
    fundrefid: null
    gridid: null
    name: The Norwegian Bioinformatics Platform (ELIXIR-Norway) Helpdesk
    note: null
    orcidid: null
    rorid: null
    typeEntity: Consortium
    typeRole:
    - Support
    url: https://elixir.no/helpdesk
  - email: null
    fundrefid: 10.13039/501100005366
    gridid: grid.5510.1
    name: University of Oslo
    note: null
    orcidid: null
    rorid: 01xtthb56
    typeEntity: Institute
    typeRole:
    - Provider
    url: https://www.uio.no/english/index.html
  description: MirGeneDB is a database of manually curated microRNA genes that have
    been validated and annotated as initially described in Fromm et al. 2015 , Fromm
    et al. 2020 and Fromm et al 2022. MirGeneDB 3.0 (Clarke and Hoye et al. 2024 )
    includes more than 21,000 microRNA gene entries representing more than 1,700 microRNA
    families from 114 metazoan species. All microRNAs can be browsed, searched and
    downloaded.
  documentation:
  - note: null
    type:
    - General
    url: https://www.mirgenedb.org/information
  download:
  - note: Sequence downloads for 75 species
    type: Biological data
    url: https://www.mirgenedb.org/download
    version: '3.0'
  editPermission:
    authors:
    - eca008
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  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Sequence accession (nucleic acid)
        uri: http://edamontology.org/data_1097
      format:
      - term: FASTA
        uri: http://edamontology.org/format_1929
    - data:
        term: Organism identifier
        uri: http://edamontology.org/data_1869
      format: []
    note: 'Data retrieval: curated miRNA. Organism identifier: a specific miRNA identifier
      or a species  for all miRNAs for that species. Gene transcript report: with
      metadata and visualization. RNA secondary structure: the hairpin loop of the
      miRNA with bases.'
    operation:
    - term: Data retrieval
      uri: http://edamontology.org/operation_2422
    - term: Sequence visualisation
      uri: http://edamontology.org/operation_0564
    output:
    - data:
        term: Gene transcript report
        uri: http://edamontology.org/data_3134
      format:
      - term: HTML
        uri: http://edamontology.org/format_2331
    - data:
        term: RNA secondary structure
        uri: http://edamontology.org/data_0880
      format:
      - term: HTML
        uri: http://edamontology.org/format_2331
  - cmd: null
    input:
    - data:
        term: Sequence accession (nucleic acid)
        uri: http://edamontology.org/data_1097
      format: []
    note: null
    operation:
    - term: Query and retrieval
      uri: http://edamontology.org/operation_0224
    output:
    - data:
        term: RNA sequence
        uri: http://edamontology.org/data_3495
      format:
      - term: FASTA
        uri: http://edamontology.org/format_1929
    - data:
        term: Sequence coordinates
        uri: http://edamontology.org/data_2012
      format:
      - term: GFF
        uri: http://edamontology.org/format_2305
      - term: BED
        uri: http://edamontology.org/format_3003
    - data:
        term: Count matrix
        uri: http://edamontology.org/data_3917
      format:
      - term: Textual format
        uri: http://edamontology.org/format_2330
  homepage: http://mirgenedb.org/
  homepage_status: 0
  language: []
  lastUpdate: '2025-07-05T22:33:30.082420Z'
  license: CC0-1.0
  link:
  - note: null
    type:
    - Helpdesk
    url: https://elixir.no/helpdesk
  maturity: Mature
  name: MirGeneDB
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID:
  - type: doi
    value: doi:10.25504/FAIRsharing.QXSgvF
    version: '2.0'
  owner: UiO
  publication:
  - doi: 10.1093/nar/gkab1101
    metadata:
      abstract: We describe an update of MirGeneDB, the manually curated microRNA
        gene database. Adhering to uniform and consistent criteria for microRNA annotation
        and nomenclature, we substantially expanded MirGeneDB with 30 additional species
        representing previously missing metazoan phyla such as sponges, jellyfish,
        rotifers and flatworms. MirGeneDB 2.1 now consists of 75 species spanning
        over ∼800 million years of animal evolution, and contains a total number of
        16 670 microRNAs from 1549 families. Over 6000 microRNAs were added in this
        update using ∼550 datasets with ∼7.5 billion sequencing reads. By adding new
        phylogenetically important species, especially those relevant for the study
        of whole genome duplication events, and through updating evolutionary nodes
        of origin for many families and genes, we were able to substantially refine
        our nomenclature system. All changes are traceable in the specifically developed
        MirGeneDB version tracker. The performance of read-pages is improved and microRNA
        expression matrices for all tissues and species are now also downloadable.
        Altogether, this update represents a significant step toward a complete sampling
        of all major metazoan phyla, and a widely needed foundation for comparative
        microRNA genomics and transcriptomics studies. MirGeneDB 2.1 is part of RNAcentral
        and Elixir Norway, publicly and freely available at http://www.mirgenedb.org/.
      authors:
      - name: Fromm B.
      - name: Hoye E.
      - name: Domanska D.
      - name: Zhong X.
      - name: Aparicio-Puerta E.
      - name: Ovchinnikov V.
      - name: Umu S.U.
      - name: Chabot P.J.
      - name: Kang W.
      - name: Aslanzadeh M.
      - name: Tarbier M.
      - name: Marmol-Sanchez E.
      - name: Urgese G.
      - name: Johansen M.
      - name: Hovig E.
      - name: Hackenberg M.
      - name: Friedlander M.R.
      - name: Peterson K.J.
      citationCount: 95
      date: '2022-01-07T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'MirGeneDB 2.1: Toward a complete sampling of all major animal phyla'
    note: null
    pmcid: PMC8728216
    pmid: '34850127'
    type:
    - Primary
    version: '2.1'
  - doi: 10.1093/nar/gkz885
    metadata:
      abstract: Small non-coding RNAs have gained substantial attention due to their
        roles in animal development and human disorders. Among them, microRNAs are
        special because individual gene sequences are conserved across the animal
        kingdom. In addition, unique and mechanistically well understood features
        can clearly distinguish bona fide miRNAs from the myriad other small RNAs
        generated by cells. However, making this distinction is not a common practice
        and, thus, not surprisingly, the heterogeneous quality of available miRNA
        complements has become a major concern in microRNA research. We addressed
        this by extensively expanding our curated microRNA gene database-MirGeneDB-to
        45 organisms, encompassing a wide phylogenetic swath of animal evolution.
        By consistently annotating and naming 10,899 microRNA genes in these organisms,
        we show that previous microRNA annotations contained not only many false positives,
        but surprisingly lacked >2000 bona fide microRNAs. Indeed, curated microRNA
        complements of closely related organisms are very similar and can be used
        to reconstruct ancestral miRNA repertoires. MirGeneDB represents a robust
        platform for microRNA-based research, providing deeper and more significant
        insights into the biology and evolution of miRNAs as well as biomedical and
        biomarker research. MirGeneDB is publicly and freely available at http://mirgenedb.org/.
      authors:
      - name: Fromm B.
      - name: Domanska D.
      - name: Hoye E.
      - name: Ovchinnikov V.
      - name: Kang W.
      - name: Aparicio-Puerta E.
      - name: Johansen M.
      - name: Flatmark K.
      - name: Mathelier A.
      - name: Hovig E.
      - name: Hackenberg M.
      - name: Friedlander M.R.
      - name: Peterson K.J.
      citationCount: 178
      date: '2020-01-01T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'MirGeneDB 2.0: The metazoan microRNA complement'
    note: null
    pmcid: PMC6943042
    pmid: '31598695'
    type:
    - Primary
    version: '2.0'
  - doi: 10.1146/annurev-genet-120213-092023
    metadata:
      abstract: Although microRNAs (miRNAs) are among the most intensively studied
        molecules of the past 20 years, determining what is and what is not a miRNA
        has not been straightforward. Here, we present a uniform system for the annotation
        and nomenclature of miRNA genes. We show that less than a third of the 1,881
        human miRBase entries, and only approximately 16% of the 7,095 metazoan miRBase
        entries, are robustly supported as miRNA genes. Furthermore, we show that
        the human repertoire of miRNAs has been shaped by periods of intense miRNA
        innovation and that mature gene products show a very different tempo and mode
        of sequence evolution than star products. We establish a new open access database-MirGeneDB
        (http://mirgenedb.org)-to catalog this set of miRNAs, which complements the
        efforts of miRBase but differs from it by annotating the mature versus star
        products and by imposing an evolutionary hierarchy upon this curated and consistently
        named repertoire.
      authors:
      - name: Fromm B.
      - name: Billipp T.
      - name: Peck L.E.
      - name: Johansen M.
      - name: Tarver J.E.
      - name: King B.L.
      - name: Newcomb J.M.
      - name: Sempere L.F.
      - name: Flatmark K.
      - name: Hovig E.
      - name: Peterson K.J.
      citationCount: 435
      date: '2015-11-23T00:00:00Z'
      journal: Annual Review of Genetics
      title: A Uniform System for the Annotation of Vertebrate microRNA Genes and
        the Evolution of the Human microRNAome
    note: null
    pmcid: PMC4743252
    pmid: '26473382'
    type:
    - Primary
    version: '1.0'
  - doi: 10.1093/nar/gkae1094
    metadata:
      abstract: We present a major update of MirGeneDB (3.0), the manually curated
        animal microRNA gene database. Beyond moving to a new server and the creation
        of a computational mirror, we have expanded the database with the addition
        of 33 invertebrate species, including representatives of 5 previously unsampled
        phyla, and 6 mammal species. MirGeneDB now contains entries for 21 822 microRNA
        genes (5160 of these from the new species) belonging to 1743 microRNA families.
        The inclusion of these new species allowed us to refine both the evolutionary
        node of appearance of a number of microRNA genes/families, as well as MirGeneDB's
        phylogenetically informed nomenclature system. Updated covariance models of
        all microRNA families, along with all smallRNA read data are now downloadable.
        These enhanced annotations will allow researchers to analyze microRNA properties
        such as secondary structure and features of their biogenesis within a robust
        phylogenetic context and without the database plagued with numerous false
        positives and false negatives. In light of these improvements, MirGeneDB 3.0
        will assume the responsibility for naming conserved novel metazoan microRNAs.
        MirGeneDB is part of RNAcentral and Elixir Norway and is publicly and freely
        available at mirgenedb.org.
      authors:
      - name: Clarke A.W.
      - name: Hoye E.
      - name: Hembrom A.A.
      - name: Paynter V.M.
      - name: Vinther J.
      - name: Wyrozemski L.
      - name: Biryukova I.
      - name: Formaggioni A.
      - name: Ovchinnikov V.
      - name: Herlyn H.
      - name: Pierce A.
      - name: Wu C.
      - name: Aslanzadeh M.
      - name: Cheneby J.
      - name: Martinez P.
      - name: Friedlander M.R.
      - name: Hovig E.
      - name: Hackenberg M.
      - name: Umu S.U.
      - name: Johansen M.
      - name: Peterson K.J.
      - name: Fromm B.
      citationCount: 6
      date: '2025-01-06T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'MirGeneDB 3.0: Improved taxonomic sampling, uniform nomenclature of
        novel conserved microRNA families and updated covariance models'
    note: null
    pmcid: PMC11701709
    pmid: '39673268'
    type:
    - Primary
    version: '3.0'
  relation: []
  toolType:
  - Database portal
  topic:
  - term: Functional, regulatory and non-coding RNA
    uri: http://edamontology.org/topic_0659
  - term: Gene regulation
    uri: http://edamontology.org/topic_0204
  - term: Evolutionary biology
    uri: http://edamontology.org/topic_3299
  - term: Zoology
    uri: http://edamontology.org/topic_3500
  - term: Human biology
    uri: http://edamontology.org/topic_2815
  validated: 1
  version:
  - '3.0'
- accessibility: Open access
  additionDate: '2025-07-02T09:38:59.620332Z'
  biotoolsCURIE: biotools:OmicsQ
  biotoolsID: OmicsQ
  collectionID:
  - Proteomics
  confidence_flag: null
  cost: Free of charge
  credit: []
  description: OmicsQ is a Shiny-based web application designed for preprocessing
    and quantitative analysis of Omics data. It streamlines the preparation of data
    for subsequent analysis using specialized tools such as PolySTest for statistical
    testing and VSClust for clustering analysis.
  documentation:
  - note: null
    type:
    - User manual
    url: https://github.com/computproteomics/OmicsQ/blob/main/www/tutorial/Tutorial.pdf
  download: []
  editPermission:
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    input:
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        term: Expression data
        uri: http://edamontology.org/data_2603
      format:
      - term: DSV
        uri: http://edamontology.org/format_3751
      - term: xlsx
        uri: http://edamontology.org/format_3620
    note: null
    operation:
    - term: Quantification
      uri: http://edamontology.org/operation_3799
    - term: Standardisation and normalisation
      uri: http://edamontology.org/operation_3435
    - term: Principal component visualisation
      uri: http://edamontology.org/operation_2939
    - term: Correlation
      uri: http://edamontology.org/operation_3465
    - term: Multiple testing correction
      uri: http://edamontology.org/operation_4034
    - term: Expression profile clustering
      uri: http://edamontology.org/operation_0313
    - term: Statistical calculation
      uri: http://edamontology.org/operation_2238
    output:
    - data:
        term: Expression data
        uri: http://edamontology.org/data_2603
      format:
      - term: CSV
        uri: http://edamontology.org/format_3752
    - data:
        term: Statistical estimate score
        uri: http://edamontology.org/data_0951
      format:
      - term: CSV
        uri: http://edamontology.org/format_3752
    - data:
        term: Over-representation data
        uri: http://edamontology.org/data_3753
      format:
      - term: CSV
        uri: http://edamontology.org/format_3752
    - data:
        term: Plot
        uri: http://edamontology.org/data_2884
      format:
      - term: PDF
        uri: http://edamontology.org/format_3508
  homepage: https://computproteomics.bmb.sdu.dk/app_direct/OmicsQ/
  homepage_status: 0
  language:
  - R
  - JavaScript
  lastUpdate: '2025-07-02T09:38:59.624571Z'
  license: Apache-2.0
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/computproteomics/OmicsQ
  maturity: Mature
  name: OmicsQ
  operatingSystem: []
  otherID: []
  owner: veitveit11
  publication:
  - doi: 10.48550/ARXIV.2504.19813
    metadata: null
    note: null
    pmcid: null
    pmid: null
    type: []
    version: null
  relation: []
  toolType: []
  topic:
  - term: Proteomics
    uri: http://edamontology.org/topic_0121
  - term: Workflows
    uri: http://edamontology.org/topic_0769
  - term: Statistics and probability
    uri: http://edamontology.org/topic_2269
  - term: Molecular interactions, pathways and networks
    uri: http://edamontology.org/topic_0602
  - term: Omics
    uri: http://edamontology.org/topic_3391
  validated: 0
  version: []
- accessibility: Open access (with restrictions)
  additionDate: '2025-07-02T06:56:17.541425Z'
  biotoolsCURIE: biotools:uk_butterfly_monitoring_scheme
  biotoolsID: uk_butterfly_monitoring_scheme
  collectionID:
  - Biodiversity
  confidence_flag: null
  cost: Free of charge (with restrictions)
  credit:
  - email: info@butterfly-conservation.org
    fundrefid: null
    gridid: null
    name: Butterfly Conservation
    note: null
    orcidid: null
    rorid: null
    typeEntity: Project
    typeRole:
    - Contributor
    url: https://butterfly-conservation.org
  - email: null
    fundrefid: null
    gridid: null
    name: UK Centre for Ecology & Hydrology
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole: []
    url: https://www.ceh.ac.uk
  - email: info@bto.org
    fundrefid: null
    gridid: null
    name: BTO
    note: null
    orcidid: null
    rorid: null
    typeEntity: Project
    typeRole:
    - Contributor
    url: https://www.bto.org
  - email: null
    fundrefid: null
    gridid: null
    name: JNCC
    note: null
    orcidid: null
    rorid: null
    typeEntity: Project
    typeRole:
    - Contributor
    url: https://jncc.gov.uk
  description: Long-time series database of of butterfly observations with across
    the UK with rich metadata.
  documentation: []
  download: []
  editPermission:
    authors: []
    type: private
  elixirCommunity: []
  elixirNode: []
  elixirPlatform:
  - Tools
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Organism identifier
        uri: http://edamontology.org/data_1869
      format: []
    - data:
        term: Species name
        uri: http://edamontology.org/data_1045
      format: []
    note: null
    operation:
    - term: Data retrieval
      uri: http://edamontology.org/operation_2422
    output:
    - data:
        term: Database entry metadata
        uri: http://edamontology.org/data_2193
      format: []
  homepage: https://ukbms.org
  homepage_status: 0
  language: []
  lastUpdate: '2025-07-02T06:56:17.543937Z'
  license: OGTSL
  link:
  - note: Link to data request form.
    type:
    - Service
    url: https://ukbms.org/request-data
  - note: Summary statistics.
    type:
    - Other
    url: https://ukbms.org/official-statistics
  maturity: Mature
  name: UK Butterfly Monitoring Scheme
  operatingSystem: []
  otherID: []
  owner: Keiler_Collier
  publication: []
  relation: []
  toolType:
  - Database portal
  topic:
  - term: Biodiversity
    uri: http://edamontology.org/topic_3050
  - term: Ecology
    uri: http://edamontology.org/topic_0610
  validated: 0
  version: []
- accessibility: null
  additionDate: '2020-01-14T08:51:14Z'
  biotoolsCURIE: biotools:RepeatModeler2
  biotoolsID: RepeatModeler2
  collectionID: []
  confidence_flag: tool
  cost: Free of charge
  credit: []
  description: RepeatModeler is a de novo transposable element (TE) family identification
    and modeling package. At the heart of RepeatModeler are three de-novo repeat finding
    programs ( RECON, RepeatScout and LtrHarvest/Ltr_retriever ) which employ complementary
    computational methods for identifying repeat element boundaries and family relationships
    from sequence data.
  documentation: []
  download: []
  editPermission:
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    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
        uri: http://edamontology.org/format_1929
    note: null
    operation:
    - term: Genome assembly
      uri: http://edamontology.org/operation_0525
    - term: de Novo sequencing
      uri: http://edamontology.org/operation_3644
    - term: Genome annotation
      uri: http://edamontology.org/operation_0362
    output: []
  homepage: https://github.com/Dfam-consortium/RepeatModeler
  homepage_status: 0
  language:
  - Perl
  lastUpdate: '2025-07-01T04:28:03.302129Z'
  license: OSL-2.0
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/Dfam-consortium/RepeatModeler/blob/master/LICENSE
  maturity: Mature
  name: RepeatModeler2
  operatingSystem:
  - Mac
  - Linux
  otherID: []
  owner: Pub2Tools
  publication:
  - doi: 10.1101/856591
    metadata: null
    note: null
    pmcid: null
    pmid: null
    type: []
    version: null
  relation:
  - biotoolsID: repeatmodeler
    type: isNewVersionOf
  toolType:
  - Command-line tool
  topic:
  - term: Model organisms
    uri: http://edamontology.org/topic_0621
  - term: Sequence composition, complexity and repeats
    uri: http://edamontology.org/topic_0157
  - term: Whole genome sequencing
    uri: http://edamontology.org/topic_3673
  - term: Sequence assembly
    uri: http://edamontology.org/topic_0196
  - term: Mobile genetic elements
    uri: http://edamontology.org/topic_0798
  validated: 1
  version:
  - 2.0.7
- accessibility: Open access
  additionDate: '2025-06-18T09:20:19.874306Z'
  biotoolsCURIE: biotools:chopper
  biotoolsID: chopper
  collectionID:
  - ONTeater
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: decosterwouter@gmail.com
    fundrefid: null
    gridid: null
    name: Wouter de Coster
    note: null
    orcidid: https://orcid.org/0000-0002-5248-8197
    rorid: null
    typeEntity: Person
    typeRole:
    - Contributor
    url: https://gigabaseorgigabyte.wordpress.com
  description: Rust implementation of NanoFilt+NanoLyse, both originally written in
    Python. This tool, intended for long read sequencing such as PacBio or ONT, filters
    and trims a fastq file.
  documentation: []
  download: []
  editPermission:
    authors: []
    type: private
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: 'gunzip -c reads.fastq.gz | chopper -q 10 -l 500 | gzip > filtered_reads.fastq.gz

      chopper -q 10 -l 500 -i reads.fastq > filtered_reads.fastq

      chopper -q 10 -l 500 -i reads.fastq.gz | gzip > filtered_reads.fastq.gz'
    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: Data filtering
      uri: http://edamontology.org/operation_3695
    - term: Sequence trimming
      uri: http://edamontology.org/operation_3192
    output:
    - data:
        term: Sequence set (nucleic acid)
        uri: http://edamontology.org/data_1234
      format:
      - term: FASTQ
        uri: http://edamontology.org/format_1930
  - 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: Scatter plot plotting
      uri: http://edamontology.org/operation_2940
    - term: Box-Whisker plot plotting
      uri: http://edamontology.org/operation_2943
    output:
    - data:
        term: Plot
        uri: http://edamontology.org/data_2884
      format:
      - term: JPG
        uri: http://edamontology.org/format_3579
  homepage: https://github.com/wdecoster/chopper
  homepage_status: 0
  language: []
  lastUpdate: '2025-06-30T15:46:01.095401Z'
  license: MIT
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/wdecoster/chopper
  maturity: Mature
  name: Chopper
  operatingSystem:
  - Mac
  - Linux
  otherID: []
  owner: Keiler_Collier
  publication:
  - doi: 10.1093/bioinformatics/btad311
    metadata:
      abstract: 'Increases in the cohort size in long-read sequencing projects necessitate
        more efficient software for quality assessment and processing of sequencing
        data from Oxford Nanopore Technologies and Pacific Biosciences. Here, we describe
        novel tools for summarizing experiments, filtering datasets, visualizing phased
        alignments results, and updates to the NanoPack software suite. Availability
        and implementation: The cramino, chopper, kyber, and phasius tools are written
        in Rust and available as executable binaries without requiring installation
        or managing dependencies. Binaries build on musl are available for broad compatibility.
        NanoPlot and NanoComp are written in Python3. Links to the separate tools
        and their documentation can be found at https://github.com/wdecoster/nanopack.
        All tools are compatible with Linux, Mac OS, and the MS Windows Subsystem
        for Linux and are released under the MIT license. The repositories include
        test data, and the tools are continuously tested using GitHub Actions and
        can be installed with the conda dependency manager.'
      authors:
      - name: De Coster W.
      - name: Rademakers R.
      citationCount: 211
      date: '2023-05-01T00:00:00Z'
      journal: Bioinformatics
      title: 'NanoPack2: population-scale evaluation of long-read sequencing data'
    note: null
    pmcid: null
    pmid: null
    type:
    - Primary
    version: null
  relation:
  - biotoolsID: nanopack
    type: isNewVersionOf
  toolType:
  - Command-line tool
  topic:
  - term: Sequencing
    uri: http://edamontology.org/topic_3168
  - term: Genomics
    uri: http://edamontology.org/topic_0622
  validated: 0
  version:
  - v0.10.0b
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