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  description: D-GENIES – for Dot plot large Genomes in an Interactive, Efficient
    and Simple way – is an online tool designed to compare two genomes. It supports
    large genome and you can interact with the dot plot to improve the visualization.
  documentation:
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    - data:
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    note: null
    operation:
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    output:
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      format: []
    - data:
        term: Sequence similarity plot
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      format: []
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    input:
    - data:
        term: Nucleic acid sequence alignment
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    operation:
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    output:
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      format: []
  homepage: https://dgenies.toulouse.inrae.fr/
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  language:
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  - Shell
  lastUpdate: '2025-12-18T10:02:18.098079Z'
  license: GPL-3.0
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  maturity: Mature
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  owner: d.gabrielaitis
  publication:
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    metadata:
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      journal: PeerJ
      title: 'D-GENIES: Dot plot large genomes in an interactive, efficient and simple
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    note: null
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    pmid: '29888139'
    type:
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  toolType:
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  - Command-line tool
  topic:
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    uri: http://edamontology.org/topic_0622
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    uri: http://edamontology.org/topic_0092
  - term: Sequence analysis
    uri: http://edamontology.org/topic_0080
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- accessibility: Open access
  additionDate: '2025-12-15T11:29:08.759624Z'
  biotoolsCURIE: biotools:mitsorter
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  description: Stand-alone tool for methylation-based discrimination of mitochondrial
    DNA ONT reads
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    type:
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  publication:
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    metadata:
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      journal: Bioinformatics Advances
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    note: null
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- accessibility: null
  additionDate: '2025-04-18T15:04:18.411979Z'
  biotoolsCURIE: biotools:dicom_tags_extractor
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  description: Scans the DICOM files of a defined directory at the series level, and
    produces as output either 1/one single csv file containing all preselected DICOM
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    note: null
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  topic:
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  - term: Medical imaging
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  validated: 0
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- accessibility: Open access
  additionDate: '2022-04-19T09:32:41.303637Z'
  biotoolsCURIE: biotools:metagwgs
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  description: metagWGS is a workflow dedicated to the analysis of metagenomic data.
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    is included. It has been developed in collaboration with several CATI BIOS4biol
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    Futur elevage) and SeqOccIn project (CPER - Occitanie Toulouse / FEDER), ATB_Biofilm
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    url: https://genotoul-bioinfo.pages-forge.inrae.fr/metagwgs/master/index.html
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    operation:
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    note: null
    operation:
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    note: null
    operation:
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  homepage: https://forgemia.inra.fr/genotoul-bioinfo/metagwgs
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  language:
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  lastUpdate: '2025-12-11T14:51:44.804907Z'
  license: GPL-3.0
  link:
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    type:
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  name: metagWGS
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  version:
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  additionDate: '2019-02-13T17:01:40Z'
  biotoolsCURIE: biotools:Jalview
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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: Hands-on exercises, Training courses and Training videos
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    type: Icon
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  - note: Executable JAR file
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    note: 'Other Input formats:

      AMSA (.amsa);

      JnetFile (.concise, .jnet);

      PFAM (.pfam);

      Substitution matrix (.matrix);

      Jalview Project File (.jvp);

      Jalview Feature File (.features, .jvfeatures);

      Jalview Annotations File (.annotations, .jvannotations);

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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: ClustalW format
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      - term: GCG MSF
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    - data:
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      - term: Format
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      - term: HTML
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      - term: SVG
        uri: http://edamontology.org/format_3604
      - term: PNG
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  license: GPL-3.0
  link:
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  - note: null
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  - note: Latest development version
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  - note: null
    type:
    - Repository
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  - note: Twitter feed
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  - note: YouTube training videos
    type:
    - Social media
    url: https://www.youtube.com/channel/UCIjpnvZB770yz7ftbrJ0tfw
  - note: null
    type:
    - Social media
    url: https://www.linkedin.com/company/104771886/
  maturity: Mature
  name: Jalview
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  otherID: []
  owner: ben_s
  publication:
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    metadata:
      abstract: ''
      authors: []
      citationCount: 7717
      date: '2009-05-07T00:00:00Z'
      journal: Bioinformatics
      title: Jalview Version 2-A multiple sequence alignment editor and analysis workbench
    note: null
    pmcid: PMC2672624
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    type: []
    version: null
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  toolType:
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  topic:
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  - term: Data visualisation
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  validated: 1
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- accessibility: null
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  biotoolsCURIE: biotools:prolipipe
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  description: Large-scale assessment of metabolic profiles on bacteria focusing on
    specific pathways.
  documentation: []
  download:
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  description: D-GENIES – for Dot plot large Genomes in an Interactive, Efficient
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  toolType:
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  topic:
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  - term: Comparative genomics
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  validated: 0
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  description: XNAT for Preclinical Imaging Centers (XNAT-PIC) is a free and open-source
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  topic:
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  - term: Preclinical and clinical studies
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  - term: FAIR data
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  description: Open RGB Imaging Workflow for Morphological and Morphometric Analysis
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  topic:
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  biotoolsCURIE: biotools:placeback
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  description: This tool enables in silico design of synthetic promoters in yeast
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        biomarker identification through the combination of multiple metabolomic datasets
        and (4) a Network Explorer module for integrative analysis of metabolomics,
        metagenomics, and/or transcriptomics data. The user interface of MetaboAnalyst
        4.0 has been reengineered to provide a more modern look and feel, as well
        as to give more space and flexibility to introduce new functions. The underlying
        knowledgebases (compound libraries, metabolite sets, and metabolic pathways)
        have also been updated based on the latest data from the Human Metabolome
        Database (HMDB). A Docker image of MetaboAnalyst is also available to facilitate
        download and local installation of Metabo-Analyst.'
      authors:
      - name: Chong J.
      - name: Soufan O.
      - name: Li C.
      - name: Caraus I.
      - name: Li S.
      - name: Bourque G.
      - name: Wishart D.S.
      - name: Xia J.
      citationCount: 2833
      date: '2018-07-02T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'MetaboAnalyst 4.0: Towards more transparent and integrative metabolomics
        analysis'
    note: null
    pmcid: PMC6030889
    pmid: '29762782'
    type: []
    version: null
  - doi: 10.1038/s41596-022-00710-w
    metadata:
      abstract: 'Liquid chromatography coupled with high-resolution mass spectrometry
        (LC–HRMS) has become a workhorse in global metabolomics studies with growing
        applications across biomedical and environmental sciences. However, outstanding
        bioinformatics challenges in terms of data processing, statistical analysis
        and functional interpretation remain critical barriers to the wider adoption
        of this technology. To help the user community overcome these barriers, we
        have made major updates to the well-established MetaboAnalyst platform (www.metaboanalyst.ca).
        This protocol extends the previous 2011 Nature Protocol by providing stepwise
        instructions on how to use MetaboAnalyst 5.0 to: optimize parameters for LC–HRMS
        spectra processing; obtain functional insights from peak list data; integrate
        metabolomics data with transcriptomics data or combine multiple metabolomics
        datasets; conduct exploratory statistical analysis with complex metadata.
        Parameter optimization may take ~2 h to complete depending on the server load,
        and the remaining three stages may be executed in ~60 min.'
      authors:
      - name: Pang Z.
      - name: Zhou G.
      - name: Ewald J.
      - name: Chang L.
      - name: Hacariz O.
      - name: Basu N.
      - name: Xia J.
      citationCount: 730
      date: '2022-08-01T00:00:00Z'
      journal: Nature Protocols
      title: Using MetaboAnalyst 5.0 for LC–HRMS spectra processing, multi-omics integration
        and covariate adjustment of global metabolomics data
    note: null
    pmcid: null
    pmid: '35715522'
    type: []
    version: null
  relation: []
  toolType:
  - Web application
  topic:
  - term: Metabolomics
    uri: http://edamontology.org/topic_3172
  - term: Metagenomics
    uri: http://edamontology.org/topic_3174
  - term: Small molecules
    uri: http://edamontology.org/topic_0154
  validated: 1
  version:
  - '4.0'
  - '5.0'
- accessibility: Open access
  additionDate: '2019-07-04T14:05:39Z'
  biotoolsCURIE: biotools:CliqueMS
  biotoolsID: CliqueMS
  collectionID: []
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: oriol.senan@urv.cat
    fundrefid: null
    gridid: null
    name: Oriol Senan
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  description: Computational tool for annotating in-source metabolite ions from LC-MS
    untargeted metabolomics data based on a coelution similarity network.
  documentation:
  - note: Tutorial material
    type:
    - Training material
    url: https://github.com/osenan/cliqueMS/blob/master/vignettes/annotate_features.Rmd
  download:
  - note: null
    type: Source code
    url: https://cran.r-project.org/src/contrib/Archive/cliqueMS/
    version: null
  editPermission:
    authors:
    - recetox-specdatri
    type: group
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Read binning
      uri: http://edamontology.org/operation_3798
    - term: Natural product identification
      uri: http://edamontology.org/operation_3803
    output: []
  homepage: https://github.com/osenan/cliqueMS
  homepage_status: 0
  language:
  - R
  - C++
  lastUpdate: '2025-11-03T16:44:03.166147Z'
  license: GPL-3.0
  link:
  - note: null
    type:
    - Issue tracker
    url: https://github.com/osenan/cliqueMS/issues
  maturity: Mature
  name: CliqueMS
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: Ruta
  publication:
  - doi: 10.1093/bioinformatics/btz207
    metadata:
      abstract: 'The analysis of biological samples in untargeted metabolomic studies
        using LC-MS yields tens of thousands of ion signals. Annotating these features
        is of the utmost importance for answering questions as fundamental as, e.g.
        how many metabolites are there in a given sample.Results: Here, we introduce
        CliqueMS, a new algorithm for annotating in-source LC-MS1 data. CliqueMS is
        based on the similarity between coelution profiles and therefore, as opposed
        to most methods, allows for the annotation of a single spectrum. Furthermore,
        CliqueMS improves upon the state of the art in several dimensions: (i) it
        uses a more discriminatory feature similarity metric; (ii) it treats the similarities
        between features in a transparent way by means of a simple generativemodel;
        (iii) it uses a well-grounded maximum likelihood inference approach to group
        features; (iv) it uses empirical adduct frequencies to identify the parental
        mass and (v) it deals more flexibly with the identification of the parental
        mass by proposing and ranking alternative annotations. We validate our approach
        with simple mixtures of standards and with real complex biological samples.
        CliqueMS reduces the thousands of features typically obtained in complex samples
        to hundreds of metabolites, and it is able to correctly annotate more metabolites
        and adducts from a single spectrum than available tools.'
      authors:
      - name: Senan O.
      - name: Aguilar-Mogas A.
      - name: Navarro M.
      - name: Capellades J.
      - name: Noon L.
      - name: Burks D.
      - name: Yanes O.
      - name: Guimera R.
      - name: Sales-Pardo M.
      citationCount: 48
      date: '2019-10-15T00:00:00Z'
      journal: Bioinformatics
      title: 'CliqueMS: A computational tool for annotating in-source metabolite ions
        from LC-MS untargeted metabolomics data based on a coelution similarity network'
    note: null
    pmcid: PMC6792096
    pmid: '30903689'
    type:
    - Primary
    version: null
  relation: []
  toolType:
  - Library
  topic:
  - term: Small molecules
    uri: http://edamontology.org/topic_0154
  - term: Metabolomics
    uri: http://edamontology.org/topic_3172
  - term: Proteomics experiment
    uri: http://edamontology.org/topic_3520
  validated: 1
  version:
  - 0.3.2
- accessibility: Open access
  additionDate: '2020-01-21T09:25:21Z'
  biotoolsCURIE: biotools:IsoCor
  biotoolsID: IsoCor
  collectionID: []
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: millard@insa-toulouse.fr
    fundrefid: null
    gridid: null
    name: Pierre Millard
    note: null
    orcidid: https://orcid.org/0000-0002-8136-9963
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  - email: guionnet@insa-toulouse.fr
    fundrefid: null
    gridid: null
    name: Matthieu Guionnet
    note: null
    orcidid: https://orcid.org/0000-0001-5326-0357
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Baudoin Delépine
    note: null
    orcidid: https://orcid.org/0000-0001-6288-425X
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  description: IsoCor is a scientific software dedicated to the correction of low-
    and high-resolution mass spectrometry (MS) data for naturally occuring isotopes.
    IsoCor corrects raw MS data (mass fractions) for naturally-occurring isotopes
    of all elements and purity of the isotopic tracer. The output of IsoCor is the
    isotopologue distribution of the molecule (i.e. the relative fractions of molecular
    entities differing only in the number of isotopic substitutions of the tracer).
    IsoCor also calculates the mean enrichment (i.e. the mean isotopic content in
    the molecule) in metabolites.
  documentation:
  - note: null
    type:
    - API documentation
    - Command-line options
    - FAQ
    - Installation instructions
    - User manual
    url: https://isocor.readthedocs.io/en/latest/
  download:
  - note: null
    type: Source code
    url: https://github.com/MetaSys-LISBP/IsoCor
    version: '2'
  editPermission:
    authors:
    - recetox-specdatri
    type: group
  elixirCommunity: []
  elixirNode:
  - France
  elixirPlatform:
  - Tools
  - Compute
  elixir_badge: 0
  function: []
  homepage: https://github.com/MetaSys-LISBP/IsoCor
  homepage_status: 0
  language:
  - Python
  lastUpdate: '2025-11-03T16:16:25.029297Z'
  license: GPL-3.0
  link:
  - note: GitHub repository
    type:
    - Repository
    url: https://github.com/MetaSys-LISBP/IsoCor
  - note: Documentation
    type:
    - Helpdesk
    url: https://isocor.readthedocs.io/en/latest/
  - note: Galaxy tool shed
    type:
    - Galaxy service
    url: https://toolshed.g2.bx.psu.edu/view/gmat/isocor/96f7617b4848
  - note: PyPi repository
    type:
    - Repository
    url: https://pypi.org/project/IsoCor/
  - note: Bioconda repository
    type:
    - Repository
    url: https://anaconda.org/bioconda/isocor
  maturity: Mature
  name: IsoCor
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: millard
  publication:
  - doi: 10.1093/bioinformatics/btz209
    metadata:
      abstract: '© 2019 The Author(s) 2019. Published by Oxford University Press.
        All rights reserved.Summary: Mass spectrometry (MS) is widely used for isotopic
        studies of metabolism and other (bio)chemical processes. Quantitative applications
        in systems and synthetic biology require to correct the raw MS data for the
        contribution of naturally occurring isotopes. Several tools are available
        to correct low-resolution MS data, and recent developments made substantial
        improvements by introducing resolution-dependent correction methods, hence
        opening the way to the correction of high-resolution MS (HRMS) data. Nevertheless,
        current HRMS correction methods partly fail to determine which isotopic species
        are resolved from the tracer isotopologues and should thus be corrected. We
        present an updated version of our isotope correction software (IsoCor) with
        a novel correction algorithm which ensures to accurately exploit any chemical
        species with any isotopic tracer, at any MS resolution. IsoCor v2 also includes
        a novel graphical user interface for intuitive use by end-users and a command-line
        interface to streamline integration into existing pipelines. Availability
        and implementation: IsoCor v2 is implemented in Python 3 and was tested on
        Windows, Unix and MacOS platforms. The source code and the documentation are
        freely distributed under GPL3 license at https://github.com/MetaSys-LISBP/IsoCor/
        and https://isocor.readthedocs.io/.'
      authors:
      - name: Millard P.
      - name: Delepine B.
      - name: Guionnet M.
      - name: Heuillet M.
      - name: Bellvert F.
      - name: Letisse F.
      citationCount: 21
      date: '2019-11-01T00:00:00Z'
      journal: Bioinformatics
      title: 'IsoCor: Isotope correction for high-resolution MS labeling experiments'
    note: null
    pmcid: null
    pmid: '30903185'
    type:
    - Method
    version: '2'
  relation: []
  toolType:
  - Command-line tool
  - Library
  - Desktop application
  topic:
  - term: Fluxomics
    uri: http://edamontology.org/topic_3955
  - term: Metabolomics
    uri: http://edamontology.org/topic_3172
  - term: Systems biology
    uri: http://edamontology.org/topic_2259
  validated: 1
  version: []
- accessibility: null
  additionDate: '2025-10-27T16:45:48.395441Z'
  biotoolsCURIE: biotools:tetranscripts
  biotoolsID: tetranscripts
  collectionID: []
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: null
    fundrefid: null
    gridid: null
    name: Molly Gale Hammell
    note: null
    orcidid: https://orcid.org/0000-0003-0405-8392
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: null
  description: TEtranscripts is a software package for including transposable elements
    in differential expression analysis of RNA-seq datasets. It assigns reads to genes
    and transposable elements, performs differential expression testing, and provides
    statistical analysis for transposable element expression.
  documentation:
  - note: null
    type:
    - Installation instructions
    - User manual
    url: https://github.com/mhammell-laboratory/TEtranscripts
  download:
  - note: null
    type: Source code
    url: https://github.com/mhammell-laboratory/TEtranscripts
    version: null
  editPermission:
    authors: []
    type: private
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: TEtranscripts --mode TE --input <input_file> --output <output_file>
    input:
    - data:
        term: RNA sequence
        uri: http://edamontology.org/data_3495
      format:
      - term: FASTQ
        uri: http://edamontology.org/format_1930
    note: null
    operation:
    - term: Differential gene expression analysis
      uri: http://edamontology.org/operation_3223
    output:
    - data:
        term: Gene expression data
        uri: http://edamontology.org/data_2603
      format:
      - term: TSV
        uri: http://edamontology.org/format_3475
  homepage: https://hammelllab.labsites.cshl.edu/software/#TEtranscripts
  homepage_status: 0
  language:
  - Python
  lastUpdate: '2025-10-27T16:50:09.756484Z'
  license: GPL-3.0
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/mhammell-laboratory/TEtranscripts
  - note: null
    type:
    - Service
    url: https://www.mghlab.org/software/tetranscripts
  maturity: Mature
  name: TEtranscripts
  operatingSystem:
  - Mac
  - Linux
  otherID: []
  owner: samuelruizperez
  publication:
  - doi: 10.1093/bioinformatics/btv422
    metadata:
      abstract: ''
      authors: []
      citationCount: 419
      date: '2015-05-25T00:00:00Z'
      journal: Bioinformatics
      title: 'TEtranscripts: A package for including transposable elements in differential
        expression analysis of RNA-seq datasets'
    note: null
    pmcid: null
    pmid: null
    type:
    - Primary
    version: null
  relation: []
  toolType:
  - Command-line tool
  - Script
  topic:
  - term: Transcriptomics
    uri: http://edamontology.org/topic_3308
  - term: RNA-Seq
    uri: http://edamontology.org/topic_3170
  validated: 0
  version: []
- accessibility: null
  additionDate: '2016-11-28T10:07:16Z'
  biotoolsCURIE: biotools:shaman
  biotoolsID: shaman
  collectionID: []
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: null
    fundrefid: null
    gridid: null
    name: Stevenn Volant
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: https://research.pasteur.fr/en/member/stevenn-volant/
  - email: null
    fundrefid: null
    gridid: null
    name: Hugo Varet
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: https://research.pasteur.fr/en/member/hugo-varet/
  - email: null
    fundrefid: null
    gridid: null
    name: Pierre Lechat
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: https://research.pasteur.fr/en/member/pierre-lechat/
  - email: null
    fundrefid: null
    gridid: null
    name: Amine Ghozlane
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: https://research.pasteur.fr/en/member/amine-ghozlane/
  - email: null
    fundrefid: null
    gridid: null
    name: Institut Pasteur
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
    - Provider
    url: https://research.pasteur.fr
  - email: null
    fundrefid: null
    gridid: null
    name: C3BI
    note: null
    orcidid: null
    rorid: null
    typeEntity: Division
    typeRole: []
    url: https://research.pasteur.fr/en/center/c3bi/
  - email: null
    fundrefid: null
    gridid: null
    name: Bioinformatics and Biostatistics Hub
    note: null
    orcidid: null
    rorid: null
    typeEntity: Division
    typeRole:
    - Provider
    url: https://research.pasteur.fr/en/team/bioinformatics-and-biostatistics-hub/
  - email: shaman@pasteur.fr
    fundrefid: null
    gridid: null
    name: SHAMAN team
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: https://research.pasteur.fr/en/software/shaman-shiny-application-for-metagenomic-analysis/
  description: SHiny application for Metagenomic ANalysis including the normalization,
    the differential analysis and mutiple visualization. It is based on DESeq2 R package
    [Anders and Huber 2010] for the analysis of metagenomic data, as suggested in
    [McMurdie and Holmes 2014, Jonsson2016]. It robustly identifies the differential
    abundant genera with the Generalized Linear Model implemented in DESeq2 [Love
    2014].
  documentation:
  - note: null
    type:
    - General
    url: http://shaman.c3bi.pasteur.fr/
  download: []
  editPermission:
    authors:
    - hmenager
    - khillion
    - vashokan
    type: group
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Report
        uri: http://edamontology.org/data_2048
      format:
      - term: TSV
        uri: http://edamontology.org/format_3475
    note: Quantitative metagenomics Count table & taxonomy Diversity, barplot, boxplot,
      scatterplot, rarefaction curves, heatmap
    operation:
    - term: Visualisation
      uri: http://edamontology.org/operation_0337
    - term: Standardisation and normalisation
      uri: http://edamontology.org/operation_3435
    - term: Differential gene expression analysis
      uri: http://edamontology.org/operation_3223
    - term: Species frequency estimation
      uri: http://edamontology.org/operation_3221
    output:
    - data:
        term: Plot
        uri: http://edamontology.org/data_2884
      format: []
  homepage: http://shaman.c3bi.pasteur.fr/
  homepage_status: 0
  language:
  - R
  lastUpdate: '2025-10-23T10:46:59.953305Z'
  license: GPL-3.0
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/aghozlane/shaman
  maturity: Mature
  name: SHAMAN
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: aghozlane
  publication:
  - doi: 10.1073/pnas.1523899113
    metadata:
      abstract: Listeria monocytogenes is responsible for gastroenteritis in healthy
        individuals and for a severe invasive disease in immunocompromised patients.
        Among the three identified L. monocytogenes evolutionary lineages, lineage
        I strains are overrepresented in epidemic listeriosis outbreaks, but the mechanisms
        underlying the higher virulence potential of strains of this lineage remain
        elusive. Here, we demonstrate that Listeriolysin S (LLS), a virulence factor
        only present in a subset of lineage I strains, is a bacteriocin highly expressed
        in the intestine of orally infected mice that alters the host intestinal microbiota
        and promotes intestinal colonization by L. monocytogenes, as well as deeper
        organ infection. To our knowledge, these results therefore identify LLS as
        the first bacteriocin described in L. monocytogenes and associate modulation
        of host microbiota by L. monocytogenes epidemic strains to increased virulence.
      authors:
      - name: Quereda J.J.
      - name: Dussurget O.
      - name: Nahori M.-A.
      - name: Ghozlane A.
      - name: Volant S.
      - name: Dillies M.-A.
      - name: Regnault B.
      - name: Kennedy S.
      - name: Mondot S.
      - name: Villoing B.
      - name: Cossart P.
      - name: Pizarro-Cerda J.
      citationCount: 87
      date: '2016-05-17T00:00:00Z'
      journal: Proceedings of the National Academy of Sciences of the United States
        of America
      title: Bacteriocin from epidemic Listeria strains alters the host intestinal
        microbiota to favor infection
    note: null
    pmcid: PMC4878514
    pmid: '27140611'
    type:
    - Primary
    version: null
  relation: []
  toolType:
  - Web application
  topic:
  - term: Metagenomics
    uri: http://edamontology.org/topic_3174
  validated: 1
  version: []
- accessibility: Open access
  additionDate: '2025-10-14T12:23:40.079667Z'
  biotoolsCURIE: biotools:dynamont
  biotoolsID: dynamont
  collectionID: []
  confidence_flag: null
  cost: Free of charge
  credit: []
  description: A Dynamic Programming Approach to Segment ONT Signals. Dynamont is
    a segmentation/resquiggling tool for ONT signals.
  documentation: []
  download: []
  editPermission:
    authors: []
    type: private
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function: []
  homepage: https://github.com/rnajena/dynamont
  homepage_status: 0
  language:
  - Python
  - C++
  lastUpdate: '2025-10-14T12:27:29.187590Z'
  license: GPL-3.0
  link: []
  maturity: Mature
  name: Dynamont
  operatingSystem:
  - Linux
  otherID: []
  owner: Jannes
  publication: []
  relation: []
  toolType:
  - Command-line tool
  topic:
  - term: Bioinformatics
    uri: http://edamontology.org/topic_0091
  validated: 0
  version:
  - 0.7.2
- accessibility: Open access
  additionDate: '2024-03-07T20:51:08.529472Z'
  biotoolsCURIE: biotools:oncoanalyser
  biotoolsID: oncoanalyser
  collectionID: []
  confidence_flag: tool
  cost: Free of charge
  credit: []
  description: Oncoanalyser is an nf-core Nextflow implementation of the tools developed
    by Hartwig Medical Foundation. The workflow is designed to comprehensively detect
    all variant types (SNV. MNV, InDel, SV, CNV, Fusions, Viral insertions, Telomere
    length, Genetic Immune Escape, mutational processes) as well as key tumor characteristics
    (purity, ploidy, TMB, MSI) from data derived from different short read platforms.
    The tooling is optimised for paired whole genome samples (90x tumor, 30x normal)
    but can be run on exome or panel (targeted) data. There is support for GRCh37
    and GRCh38 human reference genome builds.
  documentation: []
  download: []
  editPermission:
    authors:
    - jdeligt
    - VKasalica
    type: group
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function: []
  homepage: https://github.com/nf-core/oncoanalyser/tree/dev
  homepage_status: 0
  language:
  - Java
  lastUpdate: '2025-10-09T07:39:49.943872Z'
  license: GPL-3.0
  link:
  - note: GitHub page for issue tracking of Nextflow workflow implementation
    type:
    - Issue tracker
    - Repository
    url: https://github.com/nf-core/oncoanalyser/tree/dev
  - note: GitHub repository of underlying tools with issue tracking
    type:
    - Repository
    - Issue tracker
    url: https://github.com/hartwigmedical/hmftools
  maturity: Mature
  name: oncoanalyser
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: jdeligt
  publication: []
  relation: []
  toolType:
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  topic:
  - term: Oncology
    uri: http://edamontology.org/topic_2640
  - term: Whole genome sequencing
    uri: http://edamontology.org/topic_3673
  - term: RNA-Seq
    uri: http://edamontology.org/topic_3170
  validated: 0
  version:
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- accessibility: null
  additionDate: '2025-09-25T09:40:57.232559Z'
  biotoolsCURIE: biotools:napy
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  cost: null
  credit: []
  description: An efficient Python tool providing statistical tests for large-scale
    heterogeneous data with enhanced support for missing data
  documentation:
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    type:
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    - Citation instructions
    - User manual
    url: https://github.com/DyHealthNet/NApy
  download: []
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  function:
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    input:
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        term: Matrix
        uri: http://edamontology.org/data_2082
      format: []
    note: null
    operation:
    - term: Statistical inference
      uri: http://edamontology.org/operation_3658
    output:
    - data:
        term: Matrix
        uri: http://edamontology.org/data_2082
      format: []
  homepage: https://github.com/DyHealthNet/NApy
  homepage_status: 0
  language: []
  lastUpdate: '2025-09-25T09:48:41.530316Z'
  license: GPL-3.0
  link: []
  maturity: null
  name: NApy
  operatingSystem:
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  - Linux
  otherID: []
  owner: fabianwoller
  publication:
  - doi: 10.48550/arXiv.2505.00448
    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_2269
  validated: 0
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- accessibility: null
  additionDate: '2025-09-23T08:54:29.614497Z'
  biotoolsCURIE: biotools:constava
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  collectionID: []
  confidence_flag: null
  cost: Free of charge
  credit:
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    fundrefid: null
    gridid: null
    name: Wim Vranken
    note: W.V., D.R. and G.O. conceptualised the study. W.V., D.R., G.O. and D.B.
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    orcidid: https://orcid.org/0000-0001-7470-4324
    rorid: null
    typeEntity: Person
    typeRole:
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    url: https://bio2byte.be/people/31
  - email: null
    fundrefid: null
    gridid: null
    name: José Gavalda-Garcia
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    orcidid: https://orcid.org/0000-0001-6431-3442
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: https://bio2byte.be/people/38
  - email: null
    fundrefid: null
    gridid: null
    name: David Bickel
    note: W.V., D.R., G.O. and D.B. provided supervision. J.G.-G. and D.B. developed,
      implemented and validated the method.
    orcidid: https://orcid.org/0000-0003-0332-8338
    rorid: null
    typeEntity: Person
    typeRole:
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    url: https://bio2byte.be/people/47
  - email: adrian.diaz@vub.be
    fundrefid: null
    gridid: null
    name: Adrián Díaz
    note: A.D. contributed in the distribution of this software.
    orcidid: https://orcid.org/0000-0003-0165-1318
    rorid: null
    typeEntity: Person
    typeRole:
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    url: https://bio2byte.be/people/48
  - email: null
    fundrefid: null
    gridid: null
    name: Daniele Raimondi
    note: W.V., D.R. and G.O. conceptualised the study. W.V., D.R., G.O. and D.B.
      provided supervision.
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    rorid: null
    typeEntity: Person
    typeRole:
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    url: https://orcid.org/0000-0003-1157-1899
  - email: null
    fundrefid: null
    gridid: null
    name: Gabriele Orlando
    note: W.V., D.R. and G.O. conceptualised the study. G.O. developed the initial
      methodology. W.V., D.R., G.O. and D.B. provided supervision.
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    rorid: null
    typeEntity: Person
    typeRole:
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    url: https://orcid.org/0000-0002-5935-5258
  - email: bio2byte@vub.be
    fundrefid: null
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    name: Bio2Byte
    note: null
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    typeRole: []
    url: https://bio2byte.be
  - email: null
    fundrefid: null
    gridid: null
    name: Joel Roca-Martinez
    note: J.R.-M. performed the MD simulations.
    orcidid: https://orcid.org/0000-0002-4313-3845
    rorid: null
    typeEntity: Person
    typeRole:
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    url: https://orcid.org/0000-0002-4313-3845
  description: Constava calculates conformational states probability and conformational
    state variability from protein structure ensembles.
  documentation:
  - note: "Table of content: \nDescription\nInstallation\nPrerequisites\nInstallation\
      \ through PyPI\nInstallation from the source\nUsage\nExecution from the command\
      \ line\nExtracting backbone dihedrals from a trajectory\nAnalyzing a conformational\
      \ ensemble\nGenerating custom conformational state models\nExecution as a python\
      \ library\nExtracting backbone dihedrals as a DataFrame\nSetting parameters\
      \ and analyzing a conformational ensemble\nGenerating and loading conformational\
      \ state models\nConstava-class parameters vs. command line arguments\nLicense\n\
      Authors\nAcknowledgements\nContact"
    type:
    - Command-line options
    url: https://pypi.org/project/constava/
  download:
  - note: Source code in tar.gz or zip formats.
    type: Source code
    url: https://github.com/Bio2Byte/constava/releases/tag/v1.1.0
    version: 1.1.0
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    type: group
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  elixir_badge: 0
  function:
  - cmd: constava analyze
    input:
    - data:
        term: Protein geometry data
        uri: http://edamontology.org/data_2991
      format: []
    note: This command analyzes the provided backbone dihedral angles and infers the
      propensities for each residue to reside in a given conformational state.
    operation:
    - term: Protein geometry calculation
      uri: http://edamontology.org/operation_0249
    output:
    - data:
        term: Amino acid property
        uri: http://edamontology.org/data_2016
      format: []
  homepage: https://pypi.org/project/constava/
  homepage_status: 0
  language:
  - Python
  lastUpdate: '2025-09-23T08:54:29.626822Z'
  license: GPL-3.0
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/bio2byte/constava
  maturity: Emerging
  name: Constava
  operatingSystem: []
  otherID: []
  owner: adrian.diaz
  publication:
  - doi: 10.1093/nargab/lqae082
    metadata:
      abstract: ''
      authors: []
      citationCount: 2
      date: '2024-09-01T00:00:00Z'
      journal: NAR Genomics and Bioinformatics
      title: Data-driven probabilistic definition of the low energy conformational
        states of protein residues
    note: null
    pmcid: null
    pmid: null
    type:
    - Primary
    version: null
  - doi: 10.1016/j.jmb.2024.168900
    metadata:
      abstract: ''
      authors: []
      citationCount: 3
      date: '2025-01-15T00:00:00Z'
      journal: Journal of Molecular Biology
      title: Gradations in protein dynamics captured by experimental NMR are not well
        represented by AlphaFold2 models and other computational metrics
    note: null
    pmcid: null
    pmid: null
    type:
    - Usage
    version: null
  relation: []
  toolType:
  - Command-line tool
  topic:
  - term: Protein folding, stability and design
    uri: http://edamontology.org/topic_0130
  validated: 0
  version:
  - 1.1.0
- accessibility: Open access
  additionDate: '2023-09-15T19:04:20.592395Z'
  biotoolsCURIE: biotools:methylr
  biotoolsID: methylr
  collectionID: []
  confidence_flag: tool
  cost: Free of charge
  credit:
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    fundrefid: null
    gridid: null
    name: Jyotirmoy Das
    note: null
    orcidid: https://orcid.org/0000-0002-5649-4658
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  description: Graphical interface for comprehensive DNA methylation array data analysis.
  documentation:
  - note: null
    type:
    - User manual
    url: https://methylr.netlify.app/methylysis
  download:
  - note: null
    type: Container file
    url: https://hub.docker.com/r/jd21/methylr
    version: null
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  function:
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    input:
    - data:
        term: Raw microarray data
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      format: []
    note: null
    operation:
    - term: Methylation analysis
      uri: http://edamontology.org/operation_3204
    - term: Essential dynamics
      uri: http://edamontology.org/operation_3891
    - term: Gene-set enrichment analysis
      uri: http://edamontology.org/operation_2436
    - term: Pathway analysis
      uri: http://edamontology.org/operation_3928
    - term: Principal component visualisation
      uri: http://edamontology.org/operation_2939
    output:
    - data:
        term: Gene report
        uri: http://edamontology.org/data_0916
      format: []
    - data:
        term: Heat map
        uri: http://edamontology.org/data_1636
      format: []
    - data:
        term: GO-term enrichment data
        uri: http://edamontology.org/data_3754
      format: []
    - data:
        term: Pathway overrepresentation data
        uri: http://edamontology.org/data_3953
      format: []
  homepage: https://methylr.research.liu.se
  homepage_status: 0
  language:
  - JavaScript
  - R
  lastUpdate: '2025-09-22T16:50:36.936901Z'
  license: GPL-3.0
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/JD2112/methylr
  - note: null
    type:
    - Discussion forum
    url: https://groups.google.com/g/methylr
  - note: null
    type:
    - Repository
    url: https://sourceforge.net/projects/methylr/
  - note: null
    type:
    - Other
    url: http://methylr.netlify.app
  maturity: null
  name: methylR
  operatingSystem:
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  - Linux
  - Windows
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  owner: jd21
  publication:
  - doi: 10.1093/bioinformatics/btad184
    metadata:
      abstract: 'Motivation: DNA methylation analysis using arrays is a widely used
        method in research and clinical studies to study Epigenetics. Although several
        packages have been published to incur the results, most of them require a
        deep computational knowledge to perform the analysis. To resolve the limitation
        and to offer an easily accessible solution for researchers, we developed methylR
        a graphical tool that can analyze not only the raw data but also performs
        different downstream analyses with a few mouse clicks. Results: We used standard
        and established open-source published packages or pipelines in methylR. We
        evaluated a publicly available dataset and compared the published results
        with those obtained with our tool. We implemented eight downstream analysis
        modules that can perform multidimensional analyses to pathway enrichment.
        Although the main application is designed for Illumina DNA methylation array
        data analysis, we made the accessory modules suitable for other kinds of data
        analysis as well. Availability and implementation: Freely available at Github:
        https://github.com/JD2112/methylr; Webserver: https://methylr.research.liu.se.'
      authors:
      - name: Volpe M.
      - name: Das J.
      citationCount: 0
      date: '2023-04-01T00:00:00Z'
      journal: Bioinformatics
      title: 'methylR: a graphical interface for comprehensive DNA methylation array
        data analysis'
    note: null
    pmcid: PMC10125902
    pmid: '37039839'
    type:
    - Primary
    version: null
  relation: []
  toolType:
  - Web application
  - Desktop application
  topic:
  - term: Epigenetics
    uri: http://edamontology.org/topic_3295
  - term: Microarray experiment
    uri: http://edamontology.org/topic_3518
  - term: DNA
    uri: http://edamontology.org/topic_0654
  - term: Molecular interactions, pathways and networks
    uri: http://edamontology.org/topic_0602
  - term: RNA-Seq
    uri: http://edamontology.org/topic_3170
  validated: 0
  version: []
- accessibility: Open access
  additionDate: '2025-09-22T12:18:43.568886Z'
  biotoolsCURIE: biotools:twistmethylflow
  biotoolsID: twistmethylflow
  collectionID: []
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: jyotirmoy.das@liu.se
    fundrefid: null
    gridid: null
    name: Jyotirmoy Das
    note: null
    orcidid: https://orcid.org/0000-0002-5649-4658
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    - Developer
    - Maintainer
    - Documentor
    - Provider
    - Support
    url: https://liu.se/en/employee/jyoda68
  description: This Nextflow pipeline is designed for the analysis of Twist NGS Methylation
    data, including quality control, alignment, methylation calling, differential
    methylation analysis, and post-processing. It integrates various tools and custom
    scripts to provide a comprehensive analysis workflow.
  documentation:
  - note: null
    type:
    - User manual
    url: https://jd2112.github.io/TwistMethylFlow
  download:
  - note: null
    type: Source code
    url: https://github.com/JD2112/TwistMethylFlow
    version: 1.0.5
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  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Sequencing quality control
      uri: http://edamontology.org/operation_3218
    output: []
  homepage: https://github.com/JD2112/TwistMethylFlow/
  homepage_status: 0
  language:
  - R
  - Bash
  - Python
  - JavaScript
  - Other
  lastUpdate: '2025-09-22T12:35:30.590353Z'
  license: GPL-3.0
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/JD2112/TwistMethylFlow
  maturity: Emerging
  name: TwistMethylFlow
  operatingSystem:
  - Linux
  - Mac
  - Windows
  otherID: []
  owner: jd21
  publication: []
  relation:
  - biotoolsID: bismark
    type: uses
  - biotoolsID: methylkit
    type: uses
  - biotoolsID: edger
    type: uses
  - biotoolsID: samtools
    type: uses
  - biotoolsID: fastqc
    type: uses
  - biotoolsID: multiqc
    type: uses
  - biotoolsID: qualimap
    type: uses
  - biotoolsID: clusterprofiler
    type: uses
  toolType:
  - Command-line tool
  topic:
  - term: Bioinformatics
    uri: http://edamontology.org/topic_0091
  - term: Sequence analysis
    uri: http://edamontology.org/topic_0080
  validated: 0
  version:
  - 1.0.5
- accessibility: Open access
  additionDate: '2019-05-27T16:59:15Z'
  biotoolsCURIE: biotools:SLiM_software
  biotoolsID: SLiM_software
  collectionID: []
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: messer@cornell.edu
    fundrefid: null
    gridid: null
    name: Philipp Messer
    note: null
    orcidid: https://orcid.org/0000-0001-8453-9377
    rorid: null
    typeEntity: Person
    typeRole:
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    url: https://messerlab.org
  - email: bhaller@benhaller.com
    fundrefid: null
    gridid: null
    name: Benjamin C. Haller
    note: null
    orcidid: https://orcid.org/0000-0003-1874-8327
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: http://benhaller.com
  description: Evolutionary simulation framework that combines a powerful engine for
    population genetic simulations with the capability of modeling arbitrarily complex
    evolutionary scenarios.  Includes a graphical modeling environment.
  documentation:
  - note: The manual for SLiM itself
    type:
    - User manual
    url: http://benhaller.com/slim/SLiM_Manual.pdf
  - note: The manual for Eidos, the scripting language used by SLiM
    type:
    - User manual
    url: http://benhaller.com/slim/Eidos_Manual.pdf
  - note: Quick reference sheets for SLiM and Eidos
    type:
    - Quick start guide
    url: http://benhaller.com/slim/SLiMEidosRefSheets.zip
  download:
  - note: A source archive for the command-line `slim` tool only.  Complete source
      code is on GitHub, but most platforms have an installer anyway; see the manual,
      chapter 2, for installation instructions.
    type: Source code
    url: http://benhaller.com/slim/SLiM.zip
    version: null
  - note: The GitHub page for the current release version, to obtain full source code.
    type: Downloads page
    url: https://github.com/MesserLab/SLiM/releases/latest
    version: null
  editPermission:
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  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: Run individual-based eco-evolutionary simulations with explicit genetics
    operation:
    - term: DNA substitution modelling
      uri: http://edamontology.org/operation_0550
    - term: Sequence generation
      uri: http://edamontology.org/operation_0230
    - term: Ecological modelling
      uri: http://edamontology.org/operation_3946
    output: []
  homepage: https://messerlab.org/slim/
  homepage_status: 0
  language:
  - C++
  lastUpdate: '2025-09-13T19:34:39.164982Z'
  license: GPL-3.0
  link:
  - note: SLiM home page in the Messer Lab website
    type:
    - Software catalogue
    url: https://messerlab.org/slim/
  - note: GitHub repository for SLiM
    type:
    - Repository
    url: https://github.com/MesserLab/SLiM
  - note: Discussion forum for SLiM questions
    type:
    - Discussion forum
    url: https://groups.google.com/g/slim-discuss
  - note: Announcements mailing list
    type:
    - Mailing list
    url: https://groups.google.com/g/slim-announce
  maturity: Mature
  name: SLiM
  operatingSystem:
  - Linux
  - Mac
  - Windows
  otherID: []
  owner: bchaller
  publication:
  - doi: 10.1093/molbev/msy228
    metadata:
      abstract: ''
      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
      the Wright–Fisher Model. Molecular Biology and Evolution 36(3), 632–637.'
    pmcid: PMC6389312
    pmid: '30517680'
    type:
    - Primary
    version: '3.0'
  - 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
    note: B.C. Haller, P.W. Messer. (2019). Evolutionary modeling in SLiM 3 for beginners.
      Molecular Biology and Evolution 36(5), 1101–1109.
    pmcid: PMC6501880
    pmid: '30590560'
    type:
    - Method
    version: '3.0'
  - 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
      of whole genomes. Molecular Ecology Resources 19(2), 552–566.
    pmcid: PMC6393187
    pmid: '30565882'
    type:
    - Primary
    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
      across multiple chromosomes and full genomes. bioRxiv, 2025.08. 07.669155'
    pmcid: PMC12363870
    pmid: '40832315'
    type:
    - Primary
    version: '5.0'
  - doi: 10.1086/723601
    metadata:
      abstract: ''
      authors: []
      citationCount: 124
      date: '2023-05-01T00:00:00Z'
      journal: American Naturalist
      title: 'SLiM 4: Multispecies Eco-Evolutionary Modeling'
    note: 'B.C. Haller, P.W. Messer. (2023). SLiM 4: Multispecies eco-evolutionary
      modeling. The American Naturalist 201(5), E127–E139.'
    pmcid: PMC10793872
    pmid: '37130229'
    type:
    - Primary
    version: '4.0'
  relation: []
  toolType:
  - Command-line tool
  - Desktop application
  topic:
  - term: Ecology
    uri: http://edamontology.org/topic_0610
  - term: Molecular interactions, pathways and networks
    uri: http://edamontology.org/topic_0602
  - term: Genetic variation
    uri: http://edamontology.org/topic_0199
  - term: Evolutionary biology
    uri: http://edamontology.org/topic_3299
  validated: 0
  version:
  - '5.1'
- accessibility: Open access
  additionDate: '2021-05-08T17:25:21Z'
  biotoolsCURIE: biotools:bakta
  biotoolsID: bakta
  collectionID: []
  confidence_flag: tool
  cost: Free of charge
  credit:
  - email: oliver.schwengers@cb.jlug.de
    fundrefid: null
    gridid: null
    name: Oliver Schwengers
    note: null
    orcidid: https://orcid.org/0000-0003-4216-2721
    rorid: null
    typeEntity: Person
    typeRole:
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    - Developer
    - Maintainer
    url: https://github.com/oschwengers
  - email: null
    fundrefid: null
    gridid: null
    name: Justus Liebig University Giessen
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
    - Provider
    url: https://www.uni-giessen.de
  description: Rapid & standardized annotation of bacterial genomes, MAGs & plasmids
  documentation:
  - note: null
    type:
    - General
    url: https://github.com/oschwengers/bakta/blob/main/README.md
  - note: null
    type:
    - Contributions policy
    url: https://github.com/oschwengers/bakta/blob/main/CONTRIBUTION.md
  - note: null
    type:
    - Code of conduct
    url: https://github.com/oschwengers/bakta/blob/main/CODE_OF_CONDUCT.md
  - note: null
    type:
    - User manual
    url: https://bakta.readthedocs.io/
  download:
  - note: Mandatory annotation database
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        term: Sequence assembly
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        term: Hidden Markov model
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      format:
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    note: null
    operation:
    - term: Genome annotation
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    output:
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      format:
      - term: GenBank format
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      - term: EMBL format
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      format:
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      - term: SVG
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    - data:
        term: Score
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      format:
      - term: TSV
        uri: http://edamontology.org/format_3475
  homepage: https://github.com/oschwengers/bakta
  homepage_status: 0
  language:
  - Python
  lastUpdate: '2025-09-01T07:59:35.735958Z'
  license: GPL-3.0
  link:
  - note: null
    type:
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  - note: null
    type:
    - Issue tracker
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  - note: null
    type:
    - Other
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  - note: null
    type:
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  otherID: []
  owner: oschwengers
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    metadata:
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      authors: []
      citationCount: 582
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      journal: Microbial Genomics
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    note: null
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    pmid: '34739369'
    type:
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    type: uses
  - biotoolsID: blast
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  - biotoolsID: aragorn
    type: uses
  - biotoolsID: pilercr
    type: uses
  - biotoolsID: deepsig
    type: uses
  toolType:
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  - Web application
  topic:
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    uri: http://edamontology.org/topic_0622
  - term: Sequence analysis
    uri: http://edamontology.org/topic_0080
  - term: Bioinformatics
    uri: http://edamontology.org/topic_0091
  validated: 0
  version:
  - v1.11.4
- accessibility: null
  additionDate: '2020-04-23T07:50:13Z'
  biotoolsCURIE: biotools:metabolicatlas
  biotoolsID: metabolicatlas
  collectionID: []
  confidence_flag: null
  cost: null
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    fundrefid: null
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    name: Mihail Anton
    note: null
    orcidid: https://orcid.org/0000-0002-7753-9042
    rorid: null
    typeEntity: null
    typeRole:
    - Primary contact
    url: null
  description: Metabolic Atlas is a web platform integrating open-source genome scale
    metabolic models (GEMs) for easy browsing and analysis. The goal is to collect
    curated GEMs, and to bring these models closer to FAIR principles. The website
    provides visualisations and comparisons of the GEMs, and links to resources, algorithms,
    other databases, and more general software applications. Metabolic Atlas is intended
    to be used for applications in metabolomics, clinical chemistry, biomarker discovery
    and general education. In short, the vision is to create a one-stop-shop for everything
    metabolism related.
  documentation:
  - note: null
    type:
    - User manual
    url: https://metabolicatlas.org/documentation
  - note: null
    type:
    - API documentation
    url: https://metabolicatlas.org/api
  download:
  - note: null
    type: Source code
    url: https://github.com/MetabolicAtlas/MetabolicAtlas
    version: null
  - note: null
    type: Icon
    url: https://github.com/MetabolicAtlas/MetabolicAtlas/blob/main/frontend/public/img/logo.png
    version: null
  - note: null
    type: API specification
    url: https://metabolicatlas.org/api/v2/
    version: null
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  function:
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    input: []
    note: null
    operation:
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    - term: Map drawing
      uri: http://edamontology.org/operation_0573
    - term: Expression profile pathway mapping
      uri: http://edamontology.org/operation_0533
    output: []
  homepage: https://metabolicatlas.org
  homepage_status: 0
  language: []
  lastUpdate: '2025-08-31T22:25:13.264963Z'
  license: GPL-3.0
  link: []
  maturity: Mature
  name: Metabolic Atlas
  operatingSystem:
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  - Windows
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  otherID:
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    value: DOI:10.1093/nar/gkac831
    version: '3.3'
  owner: M
  publication:
  - doi: 10.1126/scisignal.aaz1482
    metadata:
      abstract: ''
      authors: []
      citationCount: 253
      date: '2020-03-24T00:00:00Z'
      journal: Science Signaling
      title: An atlas of human metabolism
    note: null
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    pmid: '32209698'
    type: []
    version: '1'
  - doi: 10.1073/pnas.2102344118
    metadata:
      abstract: ''
      authors: []
      citationCount: 69
      date: '2021-07-27T00:00:00Z'
      journal: Proceedings of the National Academy of Sciences of the United States
        of America
      title: Genome-scale metabolic network reconstruction of model animals as a platform
        for translational research
    note: null
    pmcid: PMC8325244
    pmid: '34282017'
    type: []
    version: '2'
  - doi: 10.1093/nar/gkac831
    metadata:
      abstract: ''
      authors: []
      citationCount: 35
      date: '2023-01-06T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'GotEnzymes: an extensive database of enzyme parameter predictions'
    note: null
    pmcid: PMC9825421
    pmid: '36169223'
    type: []
    version: '3'
  - doi: 10.1093/database/bav068
    metadata:
      abstract: ''
      authors: []
      citationCount: 66
      date: '2015-01-01T00:00:00Z'
      journal: Database
      title: 'Human metabolic atlas: An online resource for human metabolism'
    note: null
    pmcid: PMC4513696
    pmid: '26209309'
    type: []
    version: '0'
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    type: uses
  - biotoolsID: metanetx
    type: usedBy
  - biotoolsID: identifiers.org
    type: usedBy
  - biotoolsID: chebi
    type: uses
  toolType:
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  topic:
  - term: Systems biology
    uri: http://edamontology.org/topic_2259
  validated: 0
  version:
  - 3.0 - 3.5+
  - 2.0 - 2.6
  - 1.0 - 1.7
- accessibility: null
  additionDate: '2020-01-14T09:34:01Z'
  biotoolsCURIE: biotools:vapor
  biotoolsID: vapor
  collectionID: []
  confidence_flag: tool
  cost: null
  credit: []
  description: VAPOR is a tool for classification of Influenza samples from raw short
    read sequence data for downstream bioinformatics analysis. VAPOR is provided with
    a fasta file of full-length sequences (> 20,000) for a given segment, a set of
    reads, and attempts to retrieve a reference that is closest to the sample strain.
  documentation: []
  download:
  - note: null
    type: Software package
    url: https://pypi.org/project/vaporup/#files
    version: null
  - note: A curated collection of reference sequences for each influenza A genome
      segment that can be used with the tool for classification of sequences from
      this virus
    type: Biological data
    url: https://doi.org/10.5281/zenodo.15364147
    version: null
  editPermission:
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  function:
  - cmd: null
    input: []
    note: null
    operation:
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      uri: http://edamontology.org/operation_2422
    - term: De-novo assembly
      uri: http://edamontology.org/operation_0524
    - term: Read mapping
      uri: http://edamontology.org/operation_3198
    output: []
  homepage: https://github.com/wm75/vaporup
  homepage_status: 0
  language:
  - Python
  lastUpdate: '2025-08-28T14:32:58.093703Z'
  license: GPL-3.0
  link:
  - note: Original VAPOR repository from which versions prior to 1.0.3 were released
    type:
    - Other
    url: https://github.com/connor-lab/vapor
  maturity: null
  name: VAPOR
  operatingSystem: []
  otherID: []
  owner: Kigaard
  publication:
  - doi: 10.1093/bioinformatics/btz814
    metadata:
      abstract: 'Motivation: Influenza viruses represent a global public health burden
        due to annual epidemics and pandemic potential. Due to a rapidly evolving
        RNA genome, inter-species transmission, intra-host variation, and noise in
        short-read data, reads can be lost during mapping, and de novo assembly can
        be time consuming and result in misassembly. We assessed read loss during
        mapping and designed a graph-based classifier, VAPOR, for selecting mapping
        references, assembly validation and detection of strains of non-human origin.
        Results: Standard human reference viruses were insufficient for mapping diverse
        influenza samples in simulation. VAPOR retrieved references for 257 real whole-genome
        sequencing samples with a mean of > 99:8% identity to assemblies, and increased
        the proportion of mapped reads by up to 13.3% compared to standard references.
        VAPOR has the potential to improve the robustness of bioinformatics pipelines
        for surveillance and could be adapted to other RNA viruses.'
      authors:
      - name: Southgate J.A.
      - name: Bull M.J.
      - name: Brown C.M.
      - name: Watkins J.
      - name: Corden S.
      - name: Southgate B.
      - name: Moore C.
      - name: Connor T.R.
      citationCount: 7
      date: '2020-01-01T00:00:00Z'
      journal: Bioinformatics
      title: Influenza classification from short reads with VAPOR facilitates robust
        mapping pipelines and zoonotic strain detection for routine surveillance applications
    note: null
    pmcid: PMC7703727
    pmid: '31693070'
    type: []
    version: null
  relation: []
  toolType:
  - Command-line tool
  topic:
  - term: Whole genome sequencing
    uri: http://edamontology.org/topic_3673
  - term: Mapping
    uri: http://edamontology.org/topic_0102
  - term: Sequence assembly
    uri: http://edamontology.org/topic_0196
  validated: 1
  version:
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- accessibility: Open access
  additionDate: '2025-08-20T17:28:51.309591Z'
  biotoolsCURIE: biotools:esssubgraph
  biotoolsID: esssubgraph
  collectionID: []
  confidence_flag: null
  cost: Free of charge
  credit:
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    fundrefid: null
    gridid: null
    name: haimei wen
    note: null
    orcidid: https://orcid.org/0009-0006-1600-1210
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Susan Carpenter
    note: null
    orcidid: https://orcid.org/0000-0002-5600-5404
    rorid: null
    typeEntity: null
    typeRole: []
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Karen McGinnis
    note: null
    orcidid: https://orcid.org/0000-0002-9564-8146
    rorid: null
    typeEntity: null
    typeRole: []
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Andrew Nelson
    note: null
    orcidid: https://orcid.org/0000-0001-9896-1739
    rorid: null
    typeEntity: null
    typeRole: []
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Keriayn Smith
    note: null
    orcidid: https://orcid.org/0000-0002-4351-2765
    rorid: null
    typeEntity: null
    typeRole: []
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Tian Hong
    note: null
    orcidid: https://orcid.org/0000-0002-8212-7050
    rorid: null
    typeEntity: null
    typeRole:
    - Primary contact
    url: null
  description: EssSubgraph is a model algorithm that integrates omics data and network
    data to predict essential genes.
  documentation:
  - note: null
    type:
    - Installation instructions
    url: https://github.com/wenmm/EssSubgraph/tree/main
  download:
  - note: null
    type: Source code
    url: https://github.com/wenmm/EssSubgraph/tree/main
    version: null
  editPermission:
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  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: python EssSubgraph.py --epochs 200 --device 0 --dataset ./data/esssubgraph_human_pc50_string.pkl
    input: []
    note: null
    operation:
    - term: Protein interaction network analysis
      uri: http://edamontology.org/operation_0276
    output: []
  - cmd: null
    input: []
    note: null
    operation:
    - term: Gene prediction
      uri: http://edamontology.org/operation_2454
    output: []
  - cmd: null
    input: []
    note: null
    operation:
    - term: Protein-protein interaction analysis
      uri: http://edamontology.org/operation_2949
    output: []
  homepage: https://github.com/wenmm/EssSubgraph/tree/main
  homepage_status: 0
  language:
  - Python
  lastUpdate: '2025-08-20T18:13:15.065957Z'
  license: GPL-3.0
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/wenmm/EssSubgraph/tree/main
  maturity: Mature
  name: EssSubgraph
  operatingSystem:
  - Linux
  - Mac
  - Windows
  otherID: []
  owner: haimei
  publication:
  - doi: 10.1101/2025.07.21.665218
    metadata: null
    note: https://www.biorxiv.org/content/10.1101/2025.07.21.665218v1.abstract
    pmcid: null
    pmid: null
    type:
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    version: null
  relation:
  - biotoolsID: MTGCN
    type: includes
  toolType:
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  topic:
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    uri: http://edamontology.org/topic_0091
  - term: Computational biology
    uri: http://edamontology.org/topic_3307
  - term: Machine learning
    uri: http://edamontology.org/topic_3474
  - term: Biomarkers
    uri: http://edamontology.org/topic_3360
  validated: 0
  version: []
- accessibility: Open access
  additionDate: '2025-08-07T10:25:22.118390Z'
  biotoolsCURIE: biotools:macsylib
  biotoolsID: macsylib
  collectionID:
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  confidence_flag: null
  cost: null
  credit:
  - email: null
    fundrefid: null
    gridid: null
    name: Institut Pasteur
    note: null
    orcidid: null
    rorid: 0495fxg12
    typeEntity: Institute
    typeRole: []
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Microbial Evolutionary Genomics Unit
    note: null
    orcidid: null
    rorid: null
    typeEntity: Division
    typeRole: []
    url: https://research.pasteur.fr/en/team/microbial-evolutionary-genomics/
  - email: null
    fundrefid: null
    gridid: null
    name: Bioinformatics and Biostatistics HUB
    note: null
    orcidid: null
    rorid: null
    typeEntity: Division
    typeRole: []
    url: https://research.pasteur.fr/en/team/bioinformatics-and-biostatistics-hub/
  - email: null
    fundrefid: null
    gridid: null
    name: Eduardo P.C. Rocha
    note: null
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    rorid: null
    typeEntity: Person
    typeRole:
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    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Sophie Abby
    note: null
    orcidid: https://orcid.org/0000-0002-5231-3346
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Bertrand Néron
    note: null
    orcidid: https://orcid.org/0000-0002-0220-0482
    rorid: null
    typeEntity: Person
    typeRole:
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    url: null
  description: a Python package library that allow to model and detect macromolecular
    systems, genetic pathways… by similarity search in prokaryotes datasets.
  documentation:
  - note: null
    type:
    - General
    url: https://macsylib.readthedocs.io/en/latest/
  download:
  - note: null
    type: Source code
    url: https://github.com/gem-pasteur/macsylib
    version: 1.0.1
  - note: null
    type: Software package
    url: https://pypi.org/project/MacSyLib/
    version: 1.0.1
  editPermission:
    authors: []
    type: private
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  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Protein sequence record
        uri: http://edamontology.org/data_2886
      format: []
    - data:
        term: Profile HMM
        uri: http://edamontology.org/data_3949
      format: []
    note: null
    operation:
    - term: Gene functional annotation
      uri: http://edamontology.org/operation_3672
    output:
    - data:
        term: Sequence cluster (protein)
        uri: http://edamontology.org/data_1245
      format: []
  homepage: https://github.com/gem-pasteur/macsylib
  homepage_status: 0
  language:
  - Python
  lastUpdate: '2025-08-11T12:14:42.322020Z'
  license: GPL-3.0
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/gem-pasteur/macsylib
  - note: null
    type:
    - Other
    url: https://pypi.org/project/MacSyLib/
  - note: null
    type:
    - Other
    url: https://macsylib.readthedocs.io/en/latest/
  maturity: Mature
  name: MacSyLib
  operatingSystem:
  - Linux
  - Mac
  otherID: []
  owner: bneron
  publication:
  - doi: 10.24072/pcjournal.250
    metadata:
      abstract: 'Complex cellular functions are usually encoded by a set of genes
        in one or a few orga-nized genetic loci in microbial genomes. Macromolecular
        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
        modelling of the systems. We introduce a more intuitive and comprehensive
        search engine to identify all the best candidate systems and sub-optimal ones
        that respect the models’ constraints. We also introduce the novel macsydata
        companion tool that enables the easy installation and broad distribution of
        the models developed for MacSyFinder (macsy-models) from GitHub repositories.
        Finally, we have updated and improved MacSyFinder popular mod-els: TXSScan
        to identify protein secretion systems, TFFscan to identify type IV filaments,
        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.'
      authors:
      - name: Neron B.
      - name: Denise R.
      - name: Coluzzi C.
      - name: Touchon M.
      - name: Rocha E.P.C.
      - name: Abby S.S.
      citationCount: 43
      date: '2023-01-01T00:00:00Z'
      journal: Peer Community Journal
      title: 'MacSyFinder v2: Improved modelling and search engine to identify molecular
        systems in genomes'
    note: null
    pmcid: null
    pmid: null
    type: []
    version: null
  relation:
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    type: usedBy
  toolType:
  - Library
  topic:
  - term: Functional genomics
    uri: http://edamontology.org/topic_0085
  validated: 0
  version:
  - 1.0.1
- accessibility: null
  additionDate: '2025-07-24T07:14:51.692628Z'
  biotoolsCURIE: biotools:eukcc
  biotoolsID: eukcc
  collectionID: []
  confidence_flag: null
  cost: null
  credit: []
  description: EukCC is a completeness and contamination estimator for metagenomic
    assembled microbial eukaryotic genomes.
  documentation: []
  download: []
  editPermission:
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  elixirNode: []
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  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: DNA sequence
        uri: http://edamontology.org/data_3494
      format: []
    - data:
        term: Protein sequence record
        uri: http://edamontology.org/data_2886
      format: []
    note: null
    operation:
    - term: Sequence assembly validation
      uri: http://edamontology.org/operation_3180
    output:
    - data:
        term: Sequence report
        uri: http://edamontology.org/data_2955
      format: []
  homepage: https://github.com/EBI-Metagenomics/EukCC
  homepage_status: 0
  language:
  - Python
  lastUpdate: '2025-07-24T07:14:51.694965Z'
  license: GPL-3.0
  link: []
  maturity: null
  name: EukCC
  operatingSystem: []
  otherID: []
  owner: m.bernt
  publication:
  - doi: 10.1186/s13059-020-02155-4
    metadata:
      abstract: Microbial eukaryotes constitute a significant fraction of biodiversity
        and have recently gained more attention, but the recovery of high-quality
        metagenomic assembled eukaryotic genomes is limited by the current availability
        of tools. To help address this, we have developed EukCC, a tool for estimating
        the quality of eukaryotic genomes based on the automated dynamic selection
        of single copy marker gene sets. We demonstrate that our method outperforms
        current genome quality estimators, particularly for estimating contamination,
        and have applied EukCC to datasets derived from two different environments
        to enable the identification of novel eukaryote genomes, including one from
        the human skin.
      authors:
      - name: Saary P.
      - name: Mitchell A.L.
      - name: Finn R.D.
      citationCount: 70
      date: '2020-09-10T00:00:00Z'
      journal: Genome Biology
      title: Estimating the quality of eukaryotic genomes recovered from metagenomic
        analysis with EukCC
    note: null
    pmcid: null
    pmid: null
    type: []
    version: null
  relation: []
  toolType:
  - Command-line tool
  topic:
  - term: Metagenomics
    uri: http://edamontology.org/topic_3174
  validated: 0
  version: []
- accessibility: Open access
  additionDate: '2025-07-23T10:27:57.572501Z'
  biotoolsCURIE: biotools:etenlnc
  biotoolsID: etenlnc
  collectionID: []
  confidence_flag: tool
  cost: Free of charge
  credit:
  - email: barah@tezu.ernet.in
    fundrefid: null
    gridid: null
    name: Pankaj Barah
    note: Assistant Professor at Department of Molecular Biology and Biotechnology,
      Tezpur University.
    orcidid: https://orcid.org/0000-0001-7039-7996
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    - Maintainer
    url: https://www.tezu.ernet.in/dmbbt/profile/34
  - email: prangannathofficial@gmai.com
    fundrefid: null
    gridid: null
    name: Prangan Nath
    note: null
    orcidid: https://orcid.org/0000-0002-9451-7822
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    - Maintainer
    url: null
  description: ETENLNC (End-To-End-Novel-NonCoding) is a lncRNA identification and
    analysis framework
  documentation:
  - note: A detailed guide on running ETENLNC using the demo data can be found in
      the ETENLNC manual (supplementary to our publication)
    type:
    - Command-line options
    url: https://github.com/EvolOMICS-TU/ETENLNC
  download:
  - note: Sample/demo data for ETENLNC. A detailed guide on running ETENLNC using
      the demo data can be found in the ETENLNC manual (supplementary to our publication).
    type: Biological data
    url: https://zenodo.org/records/14325721?token=eyJhbGciOiJIUzUxMiJ9.eyJpZCI6ImVmYTllNWJkLWE4ODUtNGM3OC05YTAxLWM4ZDk5YTljZDZjMCIsImRhdGEiOnt9LCJyYW5kb20iOiI4M2I1YjBlZDQ4MmUyZTIxNDg2YmI0YTFkMWE5MTI1OCJ9.HeB3WrsPduNzMyXjH4x5HfCgmIp4NzYv0P_11XU9lcXC_ZxEaVndP-kD0LDkxwufHVNlroeAhdK33PR51F6jnw
    version: '1.0'
  editPermission:
    authors: []
    type: private
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: bash ETENLNC_docker.sh
    input:
    - data:
        term: Expression data
        uri: http://edamontology.org/data_2603
      format:
      - term: FASTQ
        uri: http://edamontology.org/format_1930
    - data:
        term: Nucleic acid sequence
        uri: http://edamontology.org/data_2977
      format:
      - term: FASTA
        uri: http://edamontology.org/format_1929
    - data:
        term: Genome map
        uri: http://edamontology.org/data_1288
      format:
      - term: FASTA
        uri: http://edamontology.org/format_1929
    - data:
        term: Annotation track
        uri: http://edamontology.org/data_3002
      format:
      - term: GTF
        uri: http://edamontology.org/format_2306
      - term: GFF
        uri: http://edamontology.org/format_2305
    note: Run ETENLNC on paired-end raw RNA-Seq (.fastq) data
    operation:
    - term: Read pre-processing
      uri: http://edamontology.org/operation_3219
    - term: Sequencing quality control
      uri: http://edamontology.org/operation_3218
    - term: Transcriptome assembly
      uri: http://edamontology.org/operation_3258
    - term: Nucleic acid feature detection
      uri: http://edamontology.org/operation_0415
    - term: RNA-Seq quantification
      uri: http://edamontology.org/operation_3800
    - term: Differential gene expression profiling
      uri: http://edamontology.org/operation_3223
    - term: Heat map generation
      uri: http://edamontology.org/operation_0531
    - term: RNA secondary structure prediction
      uri: http://edamontology.org/operation_0278
    - term: k-mer counting
      uri: http://edamontology.org/operation_3472
    - term: Protein-nucleic acid interaction analysis
      uri: http://edamontology.org/operation_0389
    - term: RNA-binding protein prediction
      uri: http://edamontology.org/operation_3901
    - term: Gene regulatory network prediction
      uri: http://edamontology.org/operation_2437
    output:
    - data:
        term: Nucleic acid sequence record
        uri: http://edamontology.org/data_2887
      format:
      - term: FASTA
        uri: http://edamontology.org/format_1929
    - data:
        term: Gene expression matrix
        uri: http://edamontology.org/data_3112
      format:
      - term: CSV
        uri: http://edamontology.org/format_3752
    - data:
        term: Heat map
        uri: http://edamontology.org/data_1636
      format:
      - term: PDF
        uri: http://edamontology.org/format_3508
    - data:
        term: Protein interaction data
        uri: http://edamontology.org/data_0906
      format: []
  homepage: https://github.com/EvolOMICS-TU/ETENLNC
  homepage_status: 0
  language: []
  lastUpdate: '2025-07-23T10:27:57.574879Z'
  license: GPL-3.0
  link:
  - note: GitHub Repo
    type:
    - Repository
    url: https://github.com/EvolOMICS-TU/ETENLNC
  maturity: Emerging
  name: ETENLNC
  operatingSystem:
  - Linux
  - Mac
  - Windows
  otherID: []
  owner: prangannath
  publication:
  - doi: 10.1016/j.compbiolchem.2024.108140
    metadata:
      abstract: 'Long non-coding RNAs (lncRNAs) play crucial roles in the regulation
        of gene expression and maintenance of genomic integrity through various interactions
        with DNA, RNA, and proteins. The availability of large-scale sequence data
        from various high-throughput platforms has opened possibilities to identify,
        predict, and functionally annotate lncRNAs. As a result, there is a growing
        demand for an integrative computational framework capable of identifying known
        lncRNAs, predicting novel lncRNAs, and inferring the downstream regulatory
        interactions of lncRNAs at the genome-scale. We present ETENLNC (End-To-End-Novel-Long-NonCoding),
        a user-friendly, integrative, open-source, scalable, and modular computational
        framework for identifying and analyzing lncRNAs from raw RNA-Seq data. ETENLNC
        employs six stringent filtration steps to identify novel lncRNAs, performs
        differential expression analysis of mRNA and lncRNA transcripts, and predicts
        regulatory interactions between lncRNAs, mRNAs, miRNAs, and proteins. We benchmarked
        ETENLNC against six existing tools and optimized it for desktop workstations
        and high-performance computing environments using data from three different
        species. ETENLNC is freely available on GitHub: https://github.com/EvolOMICS-TU/ETENLNC.'
      authors:
      - name: Nath P.
      - name: Bhuyan K.
      - name: Bhattacharyya D.K.
      - name: Barah P.
      citationCount: 2
      date: '2024-10-01T00:00:00Z'
      journal: Computational Biology and Chemistry
      title: 'ETENLNC: An end to end lncRNA identification and analysis framework
        to facilitate construction of known and novel lncRNA regulatory networks'
    note: null
    pmcid: null
    pmid: '38996755'
    type:
    - Primary
    version: '.0'
  relation:
  - biotoolsID: hisat2
    type: uses
  - biotoolsID: salmon
    type: uses
  - biotoolsID: fastqc
    type: uses
  - biotoolsID: fastp
    type: uses
  - biotoolsID: stringtie
    type: uses
  - biotoolsID: gffcompare
    type: uses
  - biotoolsID: cpc2
    type: uses
  - biotoolsID: ncbi_blast_plus
    type: uses
  - biotoolsID: tximport
    type: uses
  - biotoolsID: deseq2
    type: uses
  - biotoolsID: lnctar
    type: uses
  - biotoolsID: capsule-lpi
    type: uses
  - biotoolsID: seekr
    type: uses
  toolType:
  - Command-line tool
  topic:
  - term: Functional, regulatory and non-coding RNA
    uri: http://edamontology.org/topic_0659
  validated: 0
  version:
  - '1.0'
- 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: 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: '2025-07-04T16:10:32.821423Z'
  biotoolsCURIE: biotools:16smicrobiomemlfs
  biotoolsID: 16smicrobiomemlfs
  collectionID: []
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: igarachv@ugr.es
    fundrefid: null
    gridid: null
    name: Ignacio Garach Vélez
    note: null
    orcidid: https://orcid.org/0009-0006-6618-7949
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: https://github.com/nach00gar/16SMicrobiomeMLFS
  description: 'Code and supporting data for the article: "Exploring the role of normalization
    and feature selection in microbiome disease classification pipelines."'
  documentation: []
  download: []
  editPermission:
    authors: []
    type: private
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function: []
  homepage: https://github.com/nach00gar/16SMicrobiomeMLFS
  homepage_status: 0
  language:
  - Python
  lastUpdate: '2025-07-04T16:10:32.823947Z'
  license: GPL-3.0
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/nach00gar/16SMicrobiomeMLFS
  maturity: Emerging
  name: 16SMicrobiomeMLFS
  operatingSystem:
  - Windows
  - Linux
  - Mac
  otherID: []
  owner: igarachv
  publication: []
  relation: []
  toolType:
  - Script
  topic:
  - term: Machine learning
    uri: http://edamontology.org/topic_3474
  validated: 0
  version: []
- accessibility: Open access
  additionDate: '2018-05-28T14:50:09Z'
  biotoolsCURIE: biotools:deepsig
  biotoolsID: deepsig
  collectionID:
  - Bologna Biocomputing Group
  confidence_flag: tool
  cost: Free of charge
  credit:
  - email: null
    fundrefid: null
    gridid: null
    name: ELIXIR-ITA-BOLOGNA
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
    - Provider
    url: http://biocomp.unibo.it
  - email: castrense.savojardo2@unibo.it
    fundrefid: null
    gridid: null
    name: Castrense Savojardo
    note: null
    orcidid: https://orcid.org/0000-0002-7359-0633
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    - Primary contact
    url: null
  - email: pierluigi.martelli@unibo.it
    fundrefid: null
    gridid: null
    name: Pier Luigi Martelli
    note: null
    orcidid: https://orcid.org/0000-0002-0274-5669
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: http://biocomp.unibo.it
  description: Prediction of secretory signal peptides in protein sequences
  documentation:
  - note: null
    type:
    - Command-line options
    url: https://github.com/BolognaBiocomp/deepsig
  download:
  - note: null
    type: Source code
    url: https://github.com/BolognaBiocomp/deepsig
    version: 1.2.5
  - note: null
    type: Container file
    url: https://hub.docker.com/r/bolognabiocomp/deepsig
    version: 1.2.5
  editPermission:
    authors:
    - savo
    - ELIXIR-ITA-BOLOGNA
    type: group
  elixirCommunity: []
  elixirNode:
  - Italy
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Protein sequence (raw)
        uri: http://edamontology.org/data_2974
      format:
      - term: FASTA
        uri: http://edamontology.org/format_1929
    - data:
        term: Taxonomy
        uri: http://edamontology.org/data_3028
      format:
      - term: Textual format
        uri: http://edamontology.org/format_2330
    note: null
    operation:
    - term: Protein signal peptide detection
      uri: http://edamontology.org/operation_0418
    output:
    - data:
        term: Protein report
        uri: http://edamontology.org/data_0896
      format:
      - term: HTML
        uri: http://edamontology.org/format_2331
  homepage: https://busca.biocomp.unibo.it/deepsig/
  homepage_status: 0
  language:
  - Python
  - C++
  lastUpdate: '2025-06-19T11:55:09.017105Z'
  license: GPL-3.0
  link: []
  maturity: Mature
  name: DeepSig
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: ELIXIR-ITA-BOLOGNA
  publication:
  - doi: 10.1093/bioinformatics/btx818
    metadata:
      abstract: Motivation The identification of signal peptides in protein sequences
        is an important step toward protein localization and function characterization.
        Results Here, we present DeepSig, an improved approach for signal peptide
        detection and cleavage-site prediction based on deep learning methods. Comparative
        benchmarks performed on an updated independent dataset of proteins show that
        DeepSig is the current best performing method, scoring better than other available
        state-of-the-art approaches on both signal peptide detection and precise cleavage-site
        identification. Availability and implementation DeepSig is available as both
        standalone program and web server at https://deepsig.biocomp.unibo.it. All
        datasets used in this study can be obtained from the same website.
      authors:
      - name: Savojardo C.
      - name: Martelli P.L.
      - name: Fariselli P.
      - name: Casadio R.
      citationCount: 96
      date: '2018-05-15T00:00:00Z'
      journal: Bioinformatics
      title: 'DeepSig: Deep learning improves signal peptide detection in proteins'
    note: null
    pmcid: PMC5946842
    pmid: '29280997'
    type:
    - Primary
    version: '1.0'
  relation: []
  toolType:
  - Web application
  - Command-line tool
  topic:
  - term: Computational biology
    uri: http://edamontology.org/topic_3307
  - term: Protein sites, features and motifs
    uri: http://edamontology.org/topic_3510
  - term: Protein properties
    uri: http://edamontology.org/topic_0123
  validated: 1
  version:
  - 1.2.5
- accessibility: Open access (with restrictions)
  additionDate: '2021-07-06T20:27:27Z'
  biotoolsCURIE: biotools:nanoplot
  biotoolsID: nanoplot
  collectionID:
  - ONTeater
  confidence_flag: null
  cost: Free of charge (with restrictions)
  credit:
  - email: null
    fundrefid: null
    gridid: null
    name: Wouter De Coster
    note: null
    orcidid: https://orcid.org/0000-0002-5248-8197
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: https://gigabaseorgigabyte.wordpress.com/
  description: NanoPlot is a tool with various visualizations of sequencing data in
    bam, cram, fastq, fasta or platform-specific TSV summaries, mainly intended for
    long-read sequencing from Oxford Nanopore Technologies and Pacific Biosciences
  documentation:
  - note: null
    type:
    - Command-line options
    url: https://github.com/wdecoster/NanoPlot
  download:
  - note: null
    type: Command-line specification
    url: https://anaconda.org/bioconda/nanoplot
    version: null
  - note: null
    type: Command-line specification
    url: https://pypi.org/project/NanoPlot/
    version: null
  editPermission:
    authors: []
    type: public
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: DNA sequence
        uri: http://edamontology.org/data_3494
      format:
      - term: FASTA-like
        uri: http://edamontology.org/format_2546
      - term: nucleotide
        uri: http://edamontology.org/format_1207
    note: null
    operation:
    - term: Scatter plot plotting
      uri: http://edamontology.org/operation_2940
    - term: Box-Whisker plot plotting
      uri: http://edamontology.org/operation_2943
    output: []
  homepage: https://github.com/wdecoster/NanoPlot
  homepage_status: 0
  language:
  - Python
  lastUpdate: '2025-06-18T12:31:48.762608Z'
  license: GPL-3.0
  link:
  - note: Issue tracker and most up to date software version
    type:
    - Repository
    url: https://github.com/wdecoster/NanoPlot
  - note: Web service with more limited options compared to the command line tool
    type:
    - Service
    url: http://nanoplot.bioinf.be/
  maturity: Mature
  name: NanoPlot
  operatingSystem:
  - Mac
  - Linux
  - Windows
  otherID: []
  owner: wdecoster
  publication:
  - doi: 10.1093/bioinformatics/bty149
    metadata:
      abstract: 'Summary: Here we describe NanoPack, a set of tools developed for
        visualization and processing of long-read sequencing data from Oxford Nanopore
        Technologies and Pacific Biosciences. Availability and implementation: The
        NanoPack tools are written in Python3 and released under the GNU GPL3.0 License.
        The source code can be found at https://github.com/wdecoster/nanopack, together
        with links to separate scripts and their documentation. The scripts are compatible
        with Linux, Mac OS and the MS Windows 10 subsystem for Linux and are available
        as a graphical user interface, a web service at http://nanoplot.bioinf.be
        and command line tools.'
      authors:
      - name: De Coster W.
      - name: D'Hert S.
      - name: Schultz D.T.
      - name: Cruts M.
      - name: Van Broeckhoven C.
      citationCount: 1840
      date: '2018-08-01T00:00:00Z'
      journal: Bioinformatics
      title: 'NanoPack: Visualizing and processing long-read sequencing data'
    note: null
    pmcid: PMC6061794
    pmid: '29547981'
    type:
    - Method
    version: null
  relation:
  - biotoolsID: nanopack
    type: includedIn
  toolType:
  - Command-line tool
  - Web application
  topic:
  - term: Genomics
    uri: http://edamontology.org/topic_0622
  validated: 0
  version:
  - v.1.42.0
- accessibility: Open access
  additionDate: '2021-05-26T21:13:32Z'
  biotoolsCURIE: biotools:nextdenovo
  biotoolsID: nextdenovo
  collectionID:
  - ONTeater
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: support@nextomics.org
    fundrefid: null
    gridid: null
    name: Nextomics
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
    - Primary contact
    url: null
  description: NextDenovo is a string graph-based de novo assembler for long reads
    (CLR, HiFi and ONT). It uses a "correct-then-assemble" strategy similar to canu
    (no correction step for PacBio Hifi reads), but requires significantly less computing
    resources and storages.
  documentation:
  - note: null
    type:
    - User manual
    url: https://nextdenovo.readthedocs.io/en/latest/
  download:
  - note: null
    type: Source code
    url: https://github.com/Nextomics/NextDenovo/releases/tag/2.5.2
    version: null
  editPermission:
    authors:
    - jw
    - ELIXIR-CZ
    - Keiler_Collier
    type: group
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Sequence trace
        uri: http://edamontology.org/data_0924
      format:
      - term: FASTA
        uri: http://edamontology.org/format_1929
      - term: FASTQ
        uri: http://edamontology.org/format_1930
    note: null
    operation:
    - term: De-novo assembly
      uri: http://edamontology.org/operation_0524
    - term: Genome assembly
      uri: http://edamontology.org/operation_0525
    output:
    - data:
        term: Sequence assembly
        uri: http://edamontology.org/data_0925
      format:
      - term: Sequence assembly format (text)
        uri: http://edamontology.org/format_2561
      - term: FASTA
        uri: http://edamontology.org/format_1929
  homepage: https://github.com/Nextomics/NextDenovo
  homepage_status: 0
  language:
  - Python
  - C
  lastUpdate: '2025-06-18T12:20:23.607241Z'
  license: GPL-3.0
  link:
  - note: null
    type:
    - Issue tracker
    url: https://github.com/Nextomics/NextDenovo/issues
  maturity: Mature
  name: NextDenovo
  operatingSystem: []
  otherID: []
  owner: Kigaard
  publication:
  - doi: 10.1101/2023.03.09.531669.
    metadata: null
    note: null
    pmcid: null
    pmid: null
    type: []
    version: null
  relation: []
  toolType:
  - Command-line tool
  topic:
  - term: Sequencing
    uri: http://edamontology.org/topic_3168
  - term: Sequence assembly
    uri: http://edamontology.org/topic_0196
  validated: 0
  version:
  - v.2.5.2
- accessibility: Open access
  additionDate: '2021-05-27T09:04:45Z'
  biotoolsCURIE: biotools:quickmerge
  biotoolsID: quickmerge
  collectionID:
  - ONTeater
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: null
    fundrefid: null
    gridid: null
    name: Mahul Chakraborty
    note: null
    orcidid: https://orcid.org/0000-0003-2414-9187
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: https://mahulchakraborty.wordpress.com/
  description: Quickmerge is a program that uses complementary information from genomes
    assembled with long reads in order to improve contiguity, and works with assemblies
    derived from both Pacific Biosciences or Oxford Nanopore. Quickmerge will even
    work with hybrid assemblies made by combining long reads and Illumina short reads.
  documentation: []
  download: []
  editPermission:
    authors:
    - ELIXIR-CZ
    - Keiler_Collier
    type: group
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: merge_wrapper.py -pre output_prefix assembly_1.fa assembly_2.fa
    input:
    - data:
        term: Sequence set (nucleic acid)
        uri: http://edamontology.org/data_1234
      format:
      - term: FASTA
        uri: http://edamontology.org/format_1929
    note: 'Runs whole merge process on an input assembly.

      Assembly 2 will be used to fill gaps in assembly 1.'
    operation:
    - term: Genome assembly
      uri: http://edamontology.org/operation_0525
    - term: Scaffolding
      uri: http://edamontology.org/operation_3216
    - term: De-novo assembly
      uri: http://edamontology.org/operation_0524
    - term: Genotyping
      uri: http://edamontology.org/operation_3196
    output:
    - data:
        term: Sequence set (nucleic acid)
        uri: http://edamontology.org/data_1234
      format:
      - term: FASTA
        uri: http://edamontology.org/format_1929
  homepage: https://github.com/mahulchak/quickmerge
  homepage_status: 0
  language:
  - C++
  - C
  lastUpdate: '2025-06-18T12:17:20.983962Z'
  license: GPL-3.0
  link:
  - note: null
    type:
    - Issue tracker
    url: https://github.com/mahulchak/quickmerge/issues
  - note: null
    type:
    - Repository
    url: https://github.com/mahulchak/quickmerge
  maturity: null
  name: quickmerge
  operatingSystem:
  - Mac
  - Linux
  otherID: []
  owner: Kigaard
  publication:
  - doi: 10.1534/g3.118.200162
    metadata:
      abstract: Accurate and comprehensive characterization of genetic variation is
        essential for deciphering the genetic basis of diseases and other phenotypes.
        A vast amount of genetic variation stems from largescale sequence changes
        arising from the duplication, deletion, inversion, and translocation of sequences.
        In the past 10 years, high-throughput short reads have greatly expanded our
        ability to assay sequence variation due to single nucleotide polymorphisms.
        However, a recent de novo assembly of a second Drosophila melanogaster reference
        genome has revealed that short read genotyping methods miss hundreds of structural
        variants, including those affecting phenotypes. While genomes assembled using
        highcoverage long reads can achieve high levels of contiguity and completeness,
        concerns about cost, errors, and low yield have limited widespread adoption
        of such sequencing approaches. Here we resequenced the reference strain of
        D. melanogaster (ISO1) on a single Oxford Nanopore MinION flow cell run for
        24 hr. Using only reads longer than 1 kb or with at least 30x coverage, we
        assembled a highly contiguous de novo genome. The addition of inexpensive
        paired reads and subsequent scaffolding using an optical map technology achieved
        an assembly with completeness and contiguity comparable to the D. melanogaster
        reference assembly. Comparison of our assembly to the reference assembly of
        ISO1 uncovered a number of structural variants (SVs), including novel LTR
        transposable element insertions and duplications affecting genes with developmental,
        behavioral, and metabolic functions. Collectively, these SVs provide a snapshot
        of the dynamics of genome evolution. Furthermore, our assembly and comparison
        to the D. melanogaster reference genome demonstrates that high-quality de
        novo assembly of reference genomes and comprehensive variant discovery using
        such assemblies are now possible by a single lab for under $1,000 (USD).
      authors:
      - name: Solares E.A.
      - name: Chakraborty M.
      - name: Miller D.E.
      - name: Kalsow S.
      - name: Hall K.
      - name: Perera A.G.
      - name: Emerson J.J.
      - name: Scott Hawley R.
      citationCount: 70
      date: '2018-10-01T00:00:00Z'
      journal: 'G3: Genes, Genomes, Genetics'
      title: Rapid low-cost assembly of the drosophila melanogaster reference genome
        using low-coverage, long-read sequencing
    note: null
    pmcid: PMC6169397
    pmid: '30018084'
    type:
    - Primary
    version: null
  relation: []
  toolType:
  - Command-line tool
  topic:
  - term: Structural variation
    uri: http://edamontology.org/topic_3175
  - term: Sequence assembly
    uri: http://edamontology.org/topic_0196
  - term: DNA polymorphism
    uri: http://edamontology.org/topic_2885
  - term: Whole genome sequencing
    uri: http://edamontology.org/topic_3673
  - term: Genotype and phenotype
    uri: http://edamontology.org/topic_0625
  validated: 0
  version:
  - v.0.3
- accessibility: Open access
  additionDate: '2017-08-20T16:34:27Z'
  biotoolsCURIE: biotools:pavian
  biotoolsID: pavian
  collectionID:
  - Animal and Crop Genomics
  - Biodiversity
  - microbiome
  confidence_flag: null
  cost: null
  credit:
  - email: fbreitw1@jhmi.edu
    fundrefid: null
    gridid: null
    name: null
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  description: Web application for exploring metagenomics classification results,
    with a special focus on infectious disease diagnosis. Pinpointing pathogens in
    metagenomics classification results is often complicated by host and laboratory
    contaminants as well as many non-pathogenic microbiota. Researchers can analyze,
    display and transform results from the Kraken and Centrifuge classifiers using
    interactive tables, heatmaps and flow diagrams.
  documentation:
  - note: null
    type:
    - User manual
    url: https://ccb.jhu.edu/software/pavian/index.shtml?t=manual
  download: []
  editPermission:
    authors: []
    type: public
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Taxonomy
        uri: http://edamontology.org/data_3028
      format:
      - term: TSV
        uri: http://edamontology.org/format_3475
    note: null
    operation:
    - term: Annotation
      uri: http://edamontology.org/operation_0226
    - term: Taxonomic classification
      uri: http://edamontology.org/operation_3460
    output:
    - data:
        term: Plot
        uri: http://edamontology.org/data_2884
      format: []
  homepage: https://ccb.jhu.edu/software/pavian/
  homepage_status: 0
  language:
  - R
  lastUpdate: '2025-06-17T15:12:54.095225Z'
  license: GPL-3.0
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/fbreitwieser/pavian/tree/master
  maturity: null
  name: Pavian
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: admin
  publication:
  - doi: 10.1101/084715
    metadata: null
    note: null
    pmcid: null
    pmid: null
    type:
    - Primary
    version: null
  relation: []
  toolType:
  - Web application
  - Command-line tool
  topic:
  - term: Metagenomics
    uri: http://edamontology.org/topic_3174
  - term: Model organisms
    uri: http://edamontology.org/topic_0621
  validated: 1
  version: []
- accessibility: null
  additionDate: '2025-06-02T12:24:30.535794Z'
  biotoolsCURIE: biotools:wtv
  biotoolsID: wtv
  collectionID: []
  confidence_flag: null
  cost: null
  credit: []
  description: "A CLI/python library that selects characteristic qualitative ions\
    \ based on \nhttps://github.com/yuanhonglun/WTV_2.0"
  documentation:
  - note: null
    type:
    - User manual
    url: https://recetox.github.io/wtv/
  download:
  - note: null
    type: Source code
    url: https://github.com/RECETOX/wtv
    version: null
  - note: null
    type: Software package
    url: https://pypi.org/project/wtv/
    version: null
  - note: null
    type: Tool wrapper (Galaxy)
    url: https://github.com/RECETOX/galaxytools/tree/master/tools/wtv
    version: null
  editPermission:
    authors:
    - recetox-specdatri
    type: group
  elixirCommunity:
  - Metabolomics
  elixirNode:
  - Czech Republic
  elixirPlatform:
  - Tools
  elixir_badge: 0
  function:
  - cmd: wtv-cli --msp_path input.msp --outpath output --mz_min 35 --mz_max 400 ...
    input:
    - data:
        term: Mass spectrum
        uri: http://edamontology.org/data_0943
      format:
      - term: MSP
        uri: http://edamontology.org/format_4039
    note: null
    operation:
    - term: Feature selection
      uri: http://edamontology.org/operation_3936
    output:
    - data:
        term: Mass spectrum
        uri: http://edamontology.org/data_0943
      format:
      - term: MSP
        uri: http://edamontology.org/format_4039
  homepage: https://recetox.github.io/wtv/
  homepage_status: 0
  language:
  - Python
  lastUpdate: '2025-06-12T09:26:29.793603Z'
  license: GPL-3.0
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/RECETOX/wtv
  maturity: Emerging
  name: wtv
  operatingSystem: []
  otherID: []
  owner: acquayefrank
  publication:
  - doi: 10.1016/j.molp.2024.04.012
    metadata:
      abstract: Volatilomics is essential for understanding the biological functions
        and fragrance contributions of plant volatiles. However, the annotation coverage
        achieved using current untargeted and widely targeted volatomics (WTV) methods
        has been limited by low sensitivity and/or low acquisition coverage. Here,
        we introduce WTV 2.0, which enabled the construction of a high-coverage library
        containing 2111 plant volatiles, and report the development of a comprehensive
        selective ion monitoring (cSIM) acquisition method, including the selection
        of characteristic qualitative ions with the minimal ion number for each compound
        and an optimized segmentation method, that can acquire the smallest but sufficient
        number of ions for most plant volatiles, as well as the automatic qualitative
        and semi-quantitative analysis of cSIM data. Importantly, the library and
        acquisition method we developed can be self-expanded by incorporating compounds
        not present in the library, utilizing the obtained cSIM data. We showed that
        WTV 2.0 increases the median signal-to-noise ratio by 7.6-fold compared with
        the untargeted method, doubled the annotation coverage compared with the untargeted
        and WTV 1.0 methods in tomato fruit, and led to the discovery of menthofuran
        as a novel flavor compound in passion fruit. WTV 2.0 is a Python library with
        a user-friendly interface and is applicable to profiling of volatiles and
        primary metabolites in any species.
      authors:
      - name: Yuan H.
      - name: Jiangfang Y.
      - name: Liu Z.
      - name: Su R.
      - name: Li Q.
      - name: Fang C.
      - name: Huang S.
      - name: Liu X.
      - name: Fernie A.R.
      - name: Luo J.
      citationCount: 12
      date: '2024-06-03T00:00:00Z'
      journal: Molecular Plant
      title: 'WTV2.0: A high-coverage plant volatilomics method with a comprehensive
        selective ion monitoring acquisition mode'
    note: null
    pmcid: null
    pmid: null
    type:
    - Primary
    version: null
  relation: []
  toolType:
  - Command-line tool
  topic:
  - term: Metabolomics
    uri: http://edamontology.org/topic_3172
  validated: 0
  version:
  - 0.0.2
- accessibility: null
  additionDate: '2017-08-20T15:17:20Z'
  biotoolsCURIE: biotools:bracken
  biotoolsID: bracken
  collectionID:
  - Animal and Crop Genomics
  confidence_flag: null
  cost: null
  credit:
  - email: jlu26@jhmi.edu
    fundrefid: null
    gridid: null
    name: null
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  description: Bracken is a companion program to Kraken 1, KrakenUniq, or Kraken 2
    While Kraken classifies reads to multiple levels in the taxonomic tree, Bracken
    allows estimation of abundance at a single level using those classifications (e.g.
    Bracken can estimate abundance of species within a sample).
  documentation:
  - note: null
    type:
    - User manual
    url: https://ccb.jhu.edu/software/bracken/index.shtml?t=manual
  download: []
  editPermission:
    authors:
    - animalandcropgenomics
    - ELIXIR-CZ
    - bebatut
    - vashokan
    type: group
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Statistical calculation
      uri: http://edamontology.org/operation_2238
    output: []
  homepage: https://ccb.jhu.edu/software/bracken/
  homepage_status: 0
  language:
  - Perl
  - Python
  lastUpdate: '2025-06-11T12:25:29.118910Z'
  license: GPL-3.0
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/jenniferlu717/Bracken
  - note: null
    type:
    - Issue tracker
    url: https://github.com/jenniferlu717/Bracken/issues
  maturity: null
  name: Bracken
  operatingSystem:
  - Linux
  otherID: []
  owner: admin
  publication:
  - doi: 10.7717/peerj-cs.104
    metadata:
      abstract: Metagenomic experiments attempt to characterize microbial communities
        using high-throughput DNA sequencing. Identification of the microorganisms
        in a sample provides information about the genetic profile, population structure,
        and role of microorganisms within an environment. Until recently, most metagenomics
        studies focused on high-level characterization at the level of phyla, or alternatively
        sequenced the 16S ribosomalRNAgene that is present in bacterial species. As
        the cost of sequencing has fallen, though, metagenomics experiments have increasingly
        used unbiased shotgun sequencing to capture all the organisms in a sample.
        This approach requires a method for estimating abundance directly from the
        raw read data. Here we describe a fast, accurate new method that computes
        the abundance at the species level using the reads collected in a metagenomics
        experiment. Bracken (Bayesian Reestimation of Abundance after Classification
        with KrakEN) uses the taxonomic assignments made by Kraken, a very fast read-level
        classifier, along with information about the genomes themselves to estimate
        abundance at the species level, the genus level, or above. We demonstrate
        that Bracken can produce accurate species- and genus-level abundance estimates
        even when a sample contains multiple near-identical species.
      authors:
      - name: Lu J.
      - name: Breitwieser F.P.
      - name: Thielen P.
      - name: Salzberg S.L.
      citationCount: 1084
      date: '2017-01-01T00:00:00Z'
      journal: PeerJ Computer Science
      title: 'Bracken: Estimating species abundance in metagenomics data'
    note: null
    pmcid: null
    pmid: null
    type:
    - Primary
    version: null
  relation:
  - biotoolsID: kraken2
    type: uses
  toolType:
  - Command-line tool
  topic:
  - term: Metagenomics
    uri: http://edamontology.org/topic_3174
  - term: Microbial ecology
    uri: http://edamontology.org/topic_3697
  validated: 1
  version: []
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