count: 30401
list:
- accessibility: null
  additionDate: '2025-05-09T13:44:22.905859Z'
  biotoolsCURIE: biotools:buffercalc
  biotoolsID: buffercalc
  collectionID: []
  confidence_flag: tool
  cost: Free of charge
  credit: []
  description: Web application for designing thermodynamically corrected monoprotic
    buffers used in biological systems, with corrections for the temperature and ionic
    strength.
  documentation: []
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  editPermission:
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  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Calculation
      uri: http://edamontology.org/operation_3438
    output:
    - data:
        term: Protocol
        uri: http://edamontology.org/data_2531
      format:
      - term: HTML
        uri: http://edamontology.org/format_2331
  homepage: http://phbuffers.org/BuffferCalc/Buffer.html
  homepage_status: 0
  language:
  - Other
  lastUpdate: '2025-05-09T13:48:04.641670Z'
  license: null
  link: []
  maturity: Mature
  name: BufferCalc
  operatingSystem: []
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  owner: n.m.palmblad@lumc.nl
  publication:
  - doi: 10.1093/bioinformatics/4.4.487
    metadata:
      abstract: This paper describes a stack for the Apple MacintoshlTM, HypercardTM
        environment that facilitates the calculation of a set of thermodynamically-corrected
        pH buffers. Presented in the familiar Macintosh mouse-based environment, the
        program allows comprehensive buffer design and gives the user full control
        of buffer species, temperature, ionic strength, pH and choice of counter-ion
        to maintain the ionic strength at a fixed value. Addition of new buffers to
        the stack is straightforward and the recipes that are generated, including
        the weights of the various components, can be displayed on the screen or saved
        to a disk file for subsequent printing. © 1988 IRL Press Limited.
      authors:
      - name: Beynon R.J.
      citationCount: 7
      date: '1988-11-01T00:00:00Z'
      journal: Bioinformatics
      title: A Macintosh hypercard stack for calculation of thermodynamically-corrected
        buffer recipes
    note: null
    pmcid: null
    pmid: '3208185'
    type:
    - Primary
    version: null
  relation: []
  toolType:
  - Web application
  topic:
  - term: Chemistry
    uri: http://edamontology.org/topic_3314
  validated: 0
  version: []
- accessibility: null
  additionDate: '2025-05-08T16:21:08.567634Z'
  biotoolsCURIE: biotools:hymet
  biotoolsID: hymet
  collectionID: []
  confidence_flag: null
  cost: null
  credit: []
  description: Hybrid Metagenomic Tool
  documentation: []
  download: []
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  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Taxonomic classification
      uri: http://edamontology.org/operation_3460
    output: []
  homepage: https://github.com/inesbmartins02/HYMET
  homepage_status: 0
  language: []
  lastUpdate: '2025-05-08T16:21:08.570771Z'
  license: null
  link: []
  maturity: null
  name: HYMET
  operatingSystem: []
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  owner: inesbrancomartins
  publication: []
  relation: []
  toolType: []
  topic: []
  validated: 0
  version:
  - 1.0.0
- accessibility: null
  additionDate: '2025-04-24T13:00:12.867477Z'
  biotoolsCURIE: biotools:eetl_toolset
  biotoolsID: eetl_toolset
  collectionID:
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  confidence_flag: null
  cost: null
  credit: []
  description: 'Modular toolchain for an extensible and customizable ETL pipeline
    that extracts, transforms, and loads clinical data and medical imaging metadata,
    applying dataset-specific mappings to generate outputs compatible with the EUCAIM
    Common Data Model (CDM). Its design aims to minimize manual data preparation efforts
    and facilitate customization and integration with other components, such as data
    quality assurance tools.

    Containerized, currently supports input datasets in CSV, JSON, XLSX.'
  documentation: []
  download: []
  editPermission:
    authors: []
    type: private
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  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Data formatting
      uri: http://edamontology.org/operation_0335
    output: []
  - cmd: null
    input: []
    note: null
    operation:
    - term: Data deposition
      uri: http://edamontology.org/operation_3431
    output: []
  - cmd: null
    input: []
    note: null
    operation:
    - term: Format validation
      uri: http://edamontology.org/operation_0336
    output: []
  homepage: https://bahiasoftware.es/home
  homepage_status: 0
  language:
  - Java
  - Python
  lastUpdate: '2025-05-08T09:29:42.363560Z'
  license: Apache-2.0
  link: []
  maturity: Emerging
  name: EUCAIM ETL toolset
  operatingSystem:
  - Linux
  - Windows
  otherID: []
  owner: victorsp
  publication: []
  relation: []
  toolType:
  - Workflow
  - Library
  topic:
  - term: Data identity and mapping
    uri: http://edamontology.org/topic_3345
  - term: Workflows
    uri: http://edamontology.org/topic_0769
  validated: 0
  version:
  - 0.9.1
- accessibility: null
  additionDate: '2025-05-08T09:17:49.360624Z'
  biotoolsCURIE: biotools:hyperparameter_scoring_hi-c
  biotoolsID: hyperparameter_scoring_hi-c
  collectionID: []
  confidence_flag: null
  cost: null
  credit: []
  description: Regression-based scoring functions for predicted Hi-C matrices to enhance
    hyperparameter optimization.
  documentation: []
  download: []
  editPermission:
    authors: []
    type: private
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function: []
  homepage: https://github.com/joachimwolff/hyperparameterScoringHiC
  homepage_status: 0
  language: []
  lastUpdate: '2025-05-08T09:17:49.363010Z'
  license: null
  link: []
  maturity: null
  name: Hyperparameter Scoring Hi-C
  operatingSystem: []
  otherID: []
  owner: joachimwolff
  publication: []
  relation: []
  toolType: []
  topic: []
  validated: 0
  version: []
- accessibility: Open access
  additionDate: '2019-09-28T12:06:10Z'
  biotoolsCURIE: biotools:AMICI
  biotoolsID: AMICI
  collectionID: []
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: fabian_froehlich@hms.harvard.edu
    fundrefid: null
    gridid: null
    name: Fabian Fröhlich
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    - Maintainer
    - Developer
    url: null
  - email: jan.hasenauer@uni-bonn.de
    fundrefid: null
    gridid: null
    name: Jan Hasenauer
    note: null
    orcidid: https://orcid.org/0000-0002-4935-3312
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  - email: daniel.weindl@uni-bonn.de
    fundrefid: null
    gridid: null
    name: Daniel Weindl
    note: null
    orcidid: https://orcid.org/0000-0001-9963-6057
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    - Maintainer
    - Developer
    url: null
  description: 'AMICI provides a multi-language (Python, C++, Matlab) interface for
    the SUNDIALS solvers CVODES (for ordinary differential equations) and IDAS (for
    algebraic differential equations). AMICI allows the user to read differential
    equation models specified as SBML or PySB and automatically compiles such models
    into .mex simulation files (Matlab), C++ executables or Python modules.


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


    The interface was designed to provide routines for efficient gradient computation
    in parameter estimation of biochemical reaction models but it is also applicable
    to a wider range of differential equation constrained optimization problems.'
  documentation:
  - note: null
    type:
    - User manual
    url: https://amici.readthedocs.io/en/latest/
  download: []
  editPermission:
    authors: []
    type: private
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Pathway or network
        uri: http://edamontology.org/data_2600
      format:
      - term: SBML
        uri: http://edamontology.org/format_2585
      - term: PEtab
        uri: http://edamontology.org/format_4015
    note: null
    operation:
    - term: Network simulation
      uri: http://edamontology.org/operation_3562
    - term: Modelling and simulation
      uri: http://edamontology.org/operation_2426
    output:
    - data:
        term: Trajectory data
        uri: http://edamontology.org/data_3870
      format:
      - term: Textual format
        uri: http://edamontology.org/format_2330
  homepage: https://github.com/AMICI-dev/AMICI
  homepage_status: 0
  language:
  - MATLAB
  - C++
  - Python
  lastUpdate: '2025-05-08T07:28:52.817175Z'
  license: BSD-3-Clause
  link:
  - note: null
    type:
    - Issue tracker
    url: https://github.com/AMICI-dev/AMICI/issues
  maturity: Mature
  name: AMICI
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: dweindl
  publication:
  - doi: 10.1093/bioinformatics/btab227
    metadata:
      abstract: Ordinary differential equation models facilitate the understanding
        of cellular signal transduction and other biological processes. However, for
        large and comprehensive models, the computational cost of simulating or calibrating
        can be limiting. AMICI is a modular toolbox implemented in C++/Python/MATLAB
        that provides efficient simulation and sensitivity analysis routines tailored
        for scalable, gradient-based parameter estimation and uncertainty quantification.
      authors:
      - name: Frohlich F.
      - name: Weindl D.
      - name: Schalte Y.
      - name: Pathirana D.
      - name: Paszkowski L.
      - name: Lines G.T.
      - name: Stapor P.
      - name: Hasenauer J.
      citationCount: 37
      date: '2021-10-15T00:00:00Z'
      journal: Bioinformatics
      title: 'AMICI: high-performance sensitivity analysis for large ordinary differential
        equation models'
    note: null
    pmcid: PMC8545331
    pmid: '33821950'
    type:
    - Primary
    version: null
  relation: []
  toolType:
  - Library
  topic:
  - term: Systems biology
    uri: http://edamontology.org/topic_2259
  validated: 1
  version: []
- accessibility: Open access
  additionDate: '2025-05-07T12:50:07.458170Z'
  biotoolsCURIE: biotools:galaxy_ecology
  biotoolsID: galaxy_ecology
  collectionID: []
  confidence_flag: null
  cost: null
  credit:
  - email: yvan.le-bras@mnhn.fr
    fundrefid: null
    gridid: null
    name: Yvan Le Bras
    note: null
    orcidid: https://orcid.org/0000-0002-8504-068X
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  - email: null
    fundrefid: null
    gridid: grid.410350.3
    name: Muséum national d'Histoire naturelle
    note: null
    orcidid: null
    rorid: 03wkt5x30
    typeEntity: Institute
    typeRole: []
    url: null
  description: Galaxy Ecology is mainly developed by the French Data Terra research
    infrastructure Biodiversity data hub (PNDB). Its dedication is to provide tools
    for biodiversity data management and analysis for the Galaxy platform. Tools are
    useable through dedicated Galaxy instances hosted by Galaxy Europe (ecology.usegalaxy.eu)
    and Galaxy France (ecology.usegalaxy.fr).
  documentation: []
  download: []
  editPermission:
    authors: []
    type: public
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function: []
  homepage: https://github.com/galaxyecology/tools-ecology
  homepage_status: 0
  language: []
  lastUpdate: '2025-05-07T12:50:07.461506Z'
  license: MIT
  link:
  - note: European Galaxy Ecology instance
    type:
    - Galaxy service
    url: https://ecology.usegalaxy.eu
  - note: French Galaxy Ecology instance
    type:
    - Galaxy service
    url: https://ecology.usegalaxy.fr
  maturity: Mature
  name: Galaxy Ecology
  operatingSystem: []
  otherID: []
  owner: ylebras
  publication:
  - doi: 10.1093/gigascience/giae122
    metadata:
      abstract: Numerous conceptual frameworks exist for best practices in research
        data and analysis (e.g., Open Science and FAIR principles). In practice, there
        is a need for further progress to improve transparency, reproducibility, and
        confidence in ecology. Here, we propose a practical and operational framework
        for researchers and experts in ecology to achieve best practices for building
        analytical procedures from individual research projects to production-level
        analytical pipelines. We introduce the concept of atomization to identify
        analytical steps that support generalization by allowing us to go beyond single
        analyses. The term atomization is employed to convey the idea of single analytical
        steps as "atoms"composing an analytical procedure. When generalized, "atoms"can
        be used in more than a single case analysis. These guidelines were established
        during the development of the Galaxy-Ecology initiative, a web platform dedicated
        to data analysis in ecology. Galaxy-Ecology allows us to demonstrate a way
        to reach higher levels of reproducibility in ecological sciences by increasing
        the accessibility and reusability of analytical workflows once atomized and
        generalized.
      authors:
      - name: Royaux C.
      - name: Mihoub J.-B.
      - name: Josse M.
      - name: Pelletier D.
      - name: Norvez O.
      - name: Reecht Y.
      - name: Fouilloux A.
      - name: Rasche H.
      - name: Hiltemann S.
      - name: Batut B.
      - name: Marc E.
      - name: Seguineau P.
      - name: Masse G.
      - name: Amosse A.
      - name: Bissery C.
      - name: Lorrilliere R.
      - name: Martin A.
      - name: Bas Y.
      - name: Virgoulay T.
      - name: Chambon V.
      - name: Arnaud E.
      - name: Michon E.
      - name: Urfer C.
      - name: Trigodet E.
      - name: Delannoy M.
      - name: Lois G.
      - name: Julliard R.
      - name: Gruning B.
      - name: Le Bras Y.
      citationCount: 0
      date: '2025-01-01T00:00:00Z'
      journal: GigaScience
      title: 'Guidance framework to apply best practices in ecological data analysis:
        lessons learned from building Galaxy-Ecology'
    note: null
    pmcid: null
    pmid: null
    type:
    - Review
    version: null
  relation:
  - biotoolsID: galaxy
    type: uses
  - biotoolsID: tiaas
    type: uses
  - biotoolsID: Galaxy_Tools
    type: uses
  - biotoolsID: galaxy_france
    type: includedIn
  toolType: []
  topic:
  - term: Environmental sciences
    uri: http://edamontology.org/topic_3855
  - term: Ecology
    uri: http://edamontology.org/topic_0610
  validated: 0
  version:
  - 1.0.0
- accessibility: Open access
  additionDate: '2016-07-12T10:54:05Z'
  biotoolsCURIE: biotools:pia
  biotoolsID: pia
  collectionID:
  - KNIME
  - de.NBI
  - Proteomics
  - BioInfra.Prot
  - CUBiMed.RUB
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: julian.uszkoreit@rub.de
    fundrefid: null
    gridid: null
    name: Julian Uszkoreit
    note: null
    orcidid: http://orcid.org/0000-0001-7522-4007
    rorid: null
    typeEntity: Person
    typeRole:
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    - Developer
    - Maintainer
    url: null
  - email: cubimed@rub.de
    fundrefid: null
    gridid: null
    name: CUBiMed.RUB
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
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    url: null
  description: The main focus lays on the integrated inference algorithms, concluding
    the proteins from a set of identified spectra. But it also allows you to integrate
    results of various search engines, inspect your peptide spectrum matches, calculate
    FDR values across different results and visualize the correspondence between PSMs,
    peptides and proteins.
  documentation:
  - note: null
    type:
    - General
    url: https://github.com/medbioinf/pia/wiki
  download:
  - note: null
    type: Source code
    url: https://github.com/mpc-bioinformatics/pia
    version: null
  - note: null
    type: Software package
    url: http://bioconda.github.io/recipes/pia/README.html
    version: null
  - note: null
    type: Binaries
    url: https://github.com/mpc-bioinformatics/pia/releases
    version: null
  - note: null
    type: Container file
    url: https://hub.docker.com/r/julianusz/pia
    version: null
  editPermission:
    authors: []
    type: private
  elixirCommunity:
  - Proteomics
  elixirNode:
  - Germany
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Mass spectrometry spectra
        uri: http://edamontology.org/data_0943
      format:
      - term: Mascot .dat file
        uri: http://edamontology.org/format_3713
      - term: mzIdentML
        uri: http://edamontology.org/format_3247
      - term: TSV
        uri: http://edamontology.org/format_3475
      - term: PRIDE XML
        uri: http://edamontology.org/format_3684
      - term: X!Tandem XML
        uri: http://edamontology.org/format_3711
      - term: MSF
        uri: http://edamontology.org/format_3702
      - term: mzTab
        uri: http://edamontology.org/format_3681
    note: PIA allows you to inspect the results of common proteomics spectrum identification
      search engines, combine them seamlessly and conduct statistical analyses. The
      main focus of PIA lays on the integrated inference algorithms, i.e. concluding
      the proteins from a set of identified spectra. But it also allows you to inspect
      your peptide spectrum matches, calculate FDR values across different search
      engine results and visualize the correspondence between PSMs, peptides and proteins.
      Search engine results in several formats peptide spectrum matches (PSMs) and
      peptides Inferred Proteins
    operation:
    - term: Protein identification
      uri: http://edamontology.org/operation_3767
    - term: Target-Decoy
      uri: http://edamontology.org/operation_3649
    output:
    - data:
        term: Peptide identification
        uri: http://edamontology.org/data_0945
      format:
      - term: Sequence feature table format (text)
        uri: http://edamontology.org/format_2206
      - term: KNIME datatable format
        uri: http://edamontology.org/format_3765
      - term: idXML
        uri: http://edamontology.org/format_3764
      - term: TSV
        uri: http://edamontology.org/format_3475
      - term: mzTab
        uri: http://edamontology.org/format_3681
      - term: mzIdentML
        uri: http://edamontology.org/format_3247
    - data:
        term: Protein identifier
        uri: http://edamontology.org/data_0989
      format:
      - term: Sequence feature table format (text)
        uri: http://edamontology.org/format_2206
      - term: KNIME datatable format
        uri: http://edamontology.org/format_3765
      - term: idXML
        uri: http://edamontology.org/format_3764
      - term: TSV
        uri: http://edamontology.org/format_3475
      - term: mzTab
        uri: http://edamontology.org/format_3681
      - term: mzIdentML
        uri: http://edamontology.org/format_3247
  homepage: https://github.com/medbioinf/pia
  homepage_status: 0
  language:
  - Java
  lastUpdate: '2025-05-02T13:15:26.717477Z'
  license: BSD-3-Clause
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/medbioinf/pia
  maturity: Mature
  name: PIA - Protein Inference Algorithms
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: julianu
  publication:
  - doi: 10.1021/acs.jproteome.5b00121
    metadata:
      abstract: Protein inference connects the peptide spectrum matches (PSMs) obtained
        from database search engines back to proteins, which are typically at the
        heart of most proteomics studies. Different search engines yield different
        PSMs and thus different protein lists. Analysis of results from one or multiple
        search engines is often hampered by different data exchange formats and lack
        of convenient and intuitive user interfaces. We present PIA, a flexible software
        suite for combining PSMs from different search engine runs and turning these
        into consistent results. PIA can be integrated into proteomics data analysis
        workflows in several ways. A user-friendly graphical user interface can be
        run either locally or (e.g., for larger core facilities) from a central server.
        For automated data processing, stand-alone tools are available. PIA implements
        several established protein inference algorithms and can combine results from
        different search engines seamlessly. On several benchmark data sets, we show
        that PIA can identify a larger number of proteins at the same protein FDR
        when compared to that using inference based on a single search engine. PIA
        supports the majority of established search engines and data in the mzIdentML
        standard format. It is implemented in Java and freely available at https://github.com/mpc-bioinformatics/pia.
      authors:
      - name: Uszkoreit J.
      - name: Maerkens A.
      - name: Perez-Riverol Y.
      - name: Meyer H.E.
      - name: Marcus K.
      - name: Stephan C.
      - name: Kohlbacher O.
      - name: Eisenacher M.
      citationCount: 57
      date: '2015-07-02T00:00:00Z'
      journal: Journal of Proteome Research
      title: 'PIA: An Intuitive Protein Inference Engine with a Web-Based User Interface'
    note: null
    pmcid: null
    pmid: '25938255'
    type:
    - Primary
    version: null
  - doi: 10.1021/acs.jproteome.8b00723
    metadata:
      abstract: Proteomics using LC-MS/MS has become one of the main methods to analyze
        the proteins in biological samples in high-throughput. But the existing mass-spectrometry
        instruments are still limited with respect to resolution and measurable mass
        ranges, which is one of the main reasons why shotgun proteomics is the major
        approach. Here proteins are digested, which leads to the identification and
        quantification of peptides instead. While often neglected, the important step
        of protein inference needs to be conducted to infer from the identified peptides
        to the actual proteins in the original sample. In this work, we highlight
        some of the previously published and newly added features of the tool PIA
        - Protein Inference Algorithms, which helps the user with the protein inference
        of measured samples. We also highlight the importance of the usage of PSI
        standard file formats, as PIA is the only current software supporting all
        available standards used for spectrum identification and protein inference.
        Additionally, we briefly describe the benefits of working with workflow environments
        for proteomics analyses and show the new features of the PIA nodes for the
        KNIME Analytics Platform. Finally, we benchmark PIA against a recently published
        data set for isoform detection. PIA is open source and available for download
        on GitHub (https://github.com/mpc-bioinformatics/pia) or directly via the
        community extensions inside the KNIME analytics platform.
      authors:
      - name: Uszkoreit J.
      - name: Perez-Riverol Y.
      - name: Eggers B.
      - name: Marcus K.
      - name: Eisenacher M.
      citationCount: 30
      date: '2019-02-01T00:00:00Z'
      journal: Journal of Proteome Research
      title: Protein Inference Using PIA Workflows and PSI Standard File Formats
    note: null
    pmcid: null
    pmid: '30474983'
    type: []
    version: null
  relation:
  - biotoolsID: knime
    type: uses
  toolType:
  - Command-line tool
  - Library
  - Desktop application
  - Workflow
  topic:
  - term: Proteomics
    uri: http://edamontology.org/topic_0121
  - term: Proteomics experiment
    uri: http://edamontology.org/topic_3520
  - term: Protein variants
    uri: http://edamontology.org/topic_3120
  validated: 1
  version:
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  description: The package includes some statistical outlier detection methods for
    epimutations detection in DNA methylation data. The methods included in the package
    are MANOVA, Multivariate linear models, isolation forest, robust mahalanobis distance,
    quantile and beta. The methods compare a case sample with a suspected disease
    against a reference panel (composed of healthy individuals) to identify epimutations
    in the given case sample. It also contains functions to annotate and visualize
    the identified epimutations.
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      abstract: 'Epimutations are rare alterations of the normal DNA methylation pattern
        at specific loci, which can lead to rare diseases. Methylation microarrays
        enable genome-wide epimutation detection, but technical limitations prevent
        their use in clinical settings: methods applied to rare diseases’ data cannot
        be easily incorporated to standard analyses pipelines, while epimutation methods
        implemented in R packages (ramr) have not been validated for rare diseases.
        We have developed epimutacions, a Bioconductor package (https://bioconductor.org/packages/release/bioc/html/epimutacions.html).
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        epimutacions a new Bioconductor package for incorporating epimutations detection
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      journal: Epigenetics
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  description: Open source library and a collection of tools and interfaces for the
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    metadata:
      abstract: © 2016 Nature America, Inc. All rights reserved.High-resolution mass
        spectrometry (MS) has become an important tool in the life sciences, contributing
        to the diagnosis and understanding of human diseases, elucidating biomolecular
        structural information and characterizing cellular signaling networks. However,
        the rapid growth in the volume and complexity of MS data makes transparent,
        accurate and reproducible analysis difficult. We present OpenMS 2.0 (http://www.openms.de),
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        flexible and reproducible analysis of high-throughput MS data. The extensible
        OpenMS software implements common mass spectrometric data processing tasks
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        set of 185 tools and ready-made workflows for common mass spectrometric data
        processing tasks, which enable users to perform complex quantitative mass
        spectrometric analyses with ease.
      authors:
      - name: Rost H.L.
      - name: Sachsenberg T.
      - name: Aiche S.
      - name: Bielow C.
      - name: Weisser H.
      - name: Aicheler F.
      - name: Andreotti S.
      - name: Ehrlich H.-C.
      - name: Gutenbrunner P.
      - name: Kenar E.
      - name: Liang X.
      - name: Nahnsen S.
      - name: Nilse L.
      - name: Pfeuffer J.
      - name: Rosenberger G.
      - name: Rurik M.
      - name: Schmitt U.
      - name: Veit J.
      - name: Walzer M.
      - name: Wojnar D.
      - name: Wolski W.E.
      - name: Schilling O.
      - name: Choudhary J.S.
      - name: Malmstrom L.
      - name: Aebersold R.
      - name: Reinert K.
      - name: Kohlbacher O.
      citationCount: 246
      date: '2016-08-30T00:00:00Z'
      journal: Nature Methods
      title: 'OpenMS: A flexible open-source software platform for mass spectrometry
        data analysis'
    note: null
    pmcid: null
    pmid: '27575624'
    type:
    - Primary
    version: null
  - doi: 10.1007/978-1-60761-987-1_23
    metadata:
      abstract: Proteomics experiments based on state-of-the-art mass spectrometry
        produce vast amounts of data, which cannot be analyzed manually. Hence, software
        is needed which is able to analyze the data in an automated fashion. The need
        for robust and reusable software tools triggered the development of libraries
        implementing different algorithms for the various analysis steps. OpenMS is
        such a software library and provides a wealth of data structures and algorithms
        for the analysis of mass spectrometric data. For users unfamiliar with programming,
        TOPP ("The OpenMS Proteomics Pipeline") offers a wide range of already implemented
        tools sharing the same interface and designed for a specific analysis task
        each. TOPP thus makes the sophisticated algorithms of OpenMS accessible to
        nonprogrammers. The individual TOPP tools can be strung together into pipelines
        for analyzing mass spectrometry-based experiments starting from the raw output
        of the mass spectrometer. These analysis pipelines can be constructed using
        a graphical editor. Even complex analytical workflows can thus be analyzed
        with ease.
      authors:
      - name: Bertsch A.
      - name: Gropl C.
      - name: Reinert K.
      - name: Kohlbacher O.
      citationCount: 65
      date: '2011-01-01T00:00:00Z'
      journal: Methods in molecular biology (Clifton, N.J.)
      title: 'OpenMS and TOPP: open source software for LC-MS data analysis.'
    note: null
    pmcid: null
    pmid: null
    type:
    - Other
    version: null
  relation: []
  toolType:
  - Library
  - Workbench
  topic:
  - term: Proteomics experiment
    uri: http://edamontology.org/topic_3520
  - term: Proteomics
    uri: http://edamontology.org/topic_0121
  - term: Metabolomics
    uri: http://edamontology.org/topic_3172
  validated: 1
  version:
  - 2.0.0
- accessibility: Open access
  additionDate: '2019-08-09T13:16:33Z'
  biotoolsCURIE: biotools:pyOpenMS
  biotoolsID: pyOpenMS
  collectionID: []
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: hannes.rost@utoronto.ca
    fundrefid: null
    gridid: null
    name: Hannes L. Rost
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  description: Python library for mass spectrometry, specifically for the analysis
    of proteomics and metabolomics data.
  documentation:
  - note: null
    type:
    - User manual
    url: https://pyopenms.readthedocs.io
  download: []
  editPermission:
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  homepage: https://github.com/OpenMS/pyopenms-extra/blob/master/docs/source/index.rst
  homepage_status: 0
  language:
  - Python
  lastUpdate: '2025-04-30T11:39:29.549782Z'
  license: BSD-3-Clause
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/OpenMS/pyopenms-extra
  - note: null
    type:
    - Issue tracker
    url: https://github.com/OpenMS/pyopenms-extra/issues
  maturity: Mature
  name: pyOpenMS
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: samwein
  publication:
  - doi: 10.7287/PEERJ.PREPRINTS.27736
    metadata: null
    note: null
    pmcid: null
    pmid: null
    type:
    - Primary
    version: null
  relation: []
  toolType:
  - Library
  topic:
  - term: Proteomics
    uri: http://edamontology.org/topic_0121
  - term: Proteomics experiment
    uri: http://edamontology.org/topic_3520
  - term: Protein modifications
    uri: http://edamontology.org/topic_0601
  validated: 1
  version: []
- accessibility: Open access
  additionDate: '2019-06-18T11:06:01Z'
  biotoolsCURIE: biotools:OpenSWATH
  biotoolsID: OpenSWATH
  collectionID:
  - ms-utils
  - Proteomics
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: hroest@stanford.edu
    fundrefid: null
    gridid: null
    name: Hannes Röst
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  - email: gr2578@cumc.columbia.edu
    fundrefid: null
    gridid: null
    name: George Rosenberger
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  description: OpenSWATH is a proteomics software that allows analysis of LC-MS/MS
    DIA (data independent acquisition) and implemented as part of OpenMS.
  documentation:
  - note: null
    type:
    - User manual
    url: https://buildmedia.readthedocs.org/media/pdf/openswath/latest/openswath.pdf
  download:
  - note: null
    type: Software package
    url: http://www.openswath.org/en/latest/docs/binaries.html
    version: null
  - note: null
    type: Source code
    url: http://www.openswath.org/en/latest/docs/sources.html
    version: null
  editPermission:
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  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Experimental measurement
        uri: http://edamontology.org/data_3108
      format:
      - term: WIFF format
        uri: http://edamontology.org/format_3710
      - term: Mass spectrometry data format
        uri: http://edamontology.org/format_3245
    note: null
    operation:
    - term: Formatting
      uri: http://edamontology.org/operation_0335
    output:
    - data:
        term: Mass spectrometry data
        uri: http://edamontology.org/data_2536
      format:
      - term: mzML
        uri: http://edamontology.org/format_3244
      - term: SQLite format
        uri: http://edamontology.org/format_3621
      - term: mzXML
        uri: http://edamontology.org/format_3654
  - cmd: null
    input:
    - data:
        term: Mass spectrometry data
        uri: http://edamontology.org/data_2536
      format:
      - term: mzML
        uri: http://edamontology.org/format_3244
      - term: SQLite format
        uri: http://edamontology.org/format_3621
      - term: mzXML
        uri: http://edamontology.org/format_3654
    - data:
        term: Mass spectrometry spectra
        uri: http://edamontology.org/data_0943
      format:
      - term: TSV
        uri: http://edamontology.org/format_3475
      - term: TraML
        uri: http://edamontology.org/format_3246
    note: null
    operation:
    - term: Peak detection
      uri: http://edamontology.org/operation_3215
    - term: Chromatographic alignment
      uri: http://edamontology.org/operation_3628
    - term: Chromatogram visualisation
      uri: http://edamontology.org/operation_3203
    - term: Target-Decoy
      uri: http://edamontology.org/operation_3649
    output:
    - data:
        term: Peptide mass fingerprint
        uri: http://edamontology.org/data_0944
      format:
      - term: featureXML
        uri: http://edamontology.org/format_3833
      - term: TSV
        uri: http://edamontology.org/format_3475
      - term: SQLite format
        uri: http://edamontology.org/format_3621
  homepage: http://www.openswath.org
  homepage_status: 0
  language:
  - C++
  lastUpdate: '2025-04-30T11:39:29.102190Z'
  license: BSD-3-Clause
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/OpenSWATH/docker
  - note: null
    type:
    - Repository
    url: https://github.com/OpenMS/OpenMS
  - note: null
    type:
    - Mailing list
    url: https://sourceforge.net/projects/open-ms/lists/open-ms-general
  maturity: null
  name: OpenSWATH
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: samwein
  publication:
  - doi: null
    metadata:
      abstract: ''
      authors:
      - name: Rost H.L.
      - name: Rosenberger G.
      - name: Navarro P.
      - name: Gillet L.
      - name: Miladinovia S.M.
      - name: Schubert O.T.
      - name: Wolski W.
      - name: Collins B.C.
      - name: Malmstrom J.
      - name: Malmstrom L.
      - name: Aebersold R.
      citationCount: 409
      date: '2014-01-01T00:00:00Z'
      journal: Nature Biotechnology
      title: OpenSWATH enables automated, targeted analysis of data-independent acquisition
        MS data
    note: null
    pmcid: null
    pmid: '24727770'
    type: []
    version: null
  relation: []
  toolType:
  - Command-line tool
  topic:
  - term: Proteomics
    uri: http://edamontology.org/topic_0121
  - term: Proteomics experiment
    uri: http://edamontology.org/topic_3520
  validated: 1
  version:
  - OpenMS 2.4.0
- accessibility: null
  additionDate: '2021-01-18T11:10:26Z'
  biotoolsCURIE: biotools:openpepxl
  biotoolsID: openpepxl
  collectionID: []
  confidence_flag: tool
  cost: null
  credit:
  - email: eugen.netz@tuebingen.mpg.de
    fundrefid: null
    gridid: null
    name: Eugen Netz
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  - email: oliver.kohlbacher@uni-tuebingen.de
    fundrefid: null
    gridid: null
    name: Oliver Kohlbacher
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  description: 'An Open-Source Tool for Sensitive Identification of Cross-Linked Peptides
    in XL-MS.


    Protein-Protein Cross-Linking (OpenPepXL) – OpenMS.


    OpenPepXL is a protein-protein cross-link identification tool implemented in C++
    as part of OpenMS. It works with all uncleavable labeled and label-free cross-linkers
    but not (yet) with cleavable ones.'
  documentation: []
  download: []
  editPermission:
    authors: []
    type: private
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Peptide identification
      uri: http://edamontology.org/operation_3631
    - term: Deisotoping
      uri: http://edamontology.org/operation_3629
    - term: Protein identification
      uri: http://edamontology.org/operation_3767
    - term: Deposition
      uri: http://edamontology.org/operation_3431
    output: []
  homepage: https://openms.org/openpepxl
  homepage_status: 0
  language: []
  lastUpdate: '2025-04-30T11:39:28.349250Z'
  license: BSD-3-Clause
  link:
  - note: null
    type:
    - Other
    url: https://www.openms.de/openpepxl
  maturity: null
  name: OpenPepXL
  operatingSystem: []
  otherID: []
  owner: samwein
  publication:
  - doi: 10.1074/MCP.TIR120.002186
    metadata:
      abstract: © 2020 Netz et al. Published under exclusive license by The American
        Society for Biochemistry and Molecular Biology, Inc.Cross-linking MS (XL-MS)
        has been recognized as an effective source of information about protein structures
        and interactions. In contrast to regular peptide identification, XL-MS has
        to deal with a quadratic search space, where peptides from every protein could
        potentially be cross-linked to any other protein. To cope with this search
        space, most tools apply different heuristics for search space reduction. We
        introduce a new open-source XL-MS database search algorithm, OpenPepXL, which
        offers increased sensitivity compared with other tools. OpenPepXL searches
        the full search space of an XL-MS experiment without using heuristics to reduce
        it. Because of efficient data structures and built-in parallelization OpenPepXL
        achieves excellent runtimes and can also be deployed on large compute clusters
        and cloud services while maintaining a slim memory footprint. We compared
        OpenPepXL to several other commonly used tools for identification of noncleavable
        labeled and label-free cross-linkers on a diverse set of XL-MS experiments.
        In our first comparison, we used a data set from a fraction of a cell lysate
        with a protein database of 128 targets and 128 decoys. At 5% FDR, OpenPepXL
        finds from 7% to over 50% more unique residue pairs (URPs) than other tools.
        On data sets with available high-resolution structures for cross-link validation
        OpenPepXL reports from 7% to over 40% more structurally validated URPs than
        other tools. Additionally, we used a synthetic peptide data set that allows
        objective validation of cross-links without relying on structural information
        and found that OpenPepXL reports at least 12% more validated URPs than other
        tools. It has been built as part of the OpenMS suite of tools and supports
        Windows, macOS, and Linux operating systems. OpenPepXL also supports the MzIdentML
        1.2 format for XL-MS identification results. It is freely available under
        a three-clause BSD license at https://openms.org/openpepxl.
      authors:
      - name: Netz E.
      - name: Dijkstra T.M.H.
      - name: Sachsenberg T.
      - name: Zimmermann L.
      - name: Walzer M.
      - name: Monecke T.
      - name: Ficner R.
      - name: Dybkov O.
      - name: Urlaub H.
      - name: Kohlbacher O.
      citationCount: 0
      date: '2020-12-01T00:00:00Z'
      journal: Molecular and Cellular Proteomics
      title: 'OpenPepXL: An Open-Source Tool for Sensitive Identification of Cross-Linked
        Peptides in XL-MS'
    note: null
    pmcid: PMC7710140
    pmid: '33067342'
    type: []
    version: null
  relation: []
  toolType:
  - Command-line tool
  topic:
  - term: Proteomics experiment
    uri: http://edamontology.org/topic_3520
  - term: Small molecules
    uri: http://edamontology.org/topic_0154
  - term: Proteomics
    uri: http://edamontology.org/topic_0121
  validated: 0
  version: []
- accessibility: null
  additionDate: '2023-09-30T19:54:03.880432Z'
  biotoolsCURIE: biotools:flashida
  biotoolsID: flashida
  collectionID: []
  confidence_flag: null
  cost: null
  credit: []
  description: FLASHIda is an intelligent online data acquisition algorithm for top-down
    proteomics (TDP) that ensures the real-time selection of high-quality precursors
    of diverse proteoforms. FLASHIda combines fast decharging algorithms in FLASHDeconv
    and machine learning-based quality assessment to identify optimal precursors for
    fragmentation. Currently the C# source code and instruction of FLASHIda is available
    in here under a BSD three-clause license. We are working on merging FLASHIda into
    OpenMS.
  documentation: []
  download: []
  editPermission:
    authors: []
    type: private
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function: []
  homepage: https://www.openms.org/applications/flashida/
  homepage_status: 0
  language: []
  lastUpdate: '2025-04-30T11:39:18.106379Z'
  license: null
  link: []
  maturity: null
  name: FLASHIda
  operatingSystem: []
  otherID: []
  owner: samwein
  publication: []
  relation: []
  toolType: []
  topic: []
  validated: 0
  version: []
- accessibility: null
  additionDate: '2023-09-30T19:58:13.012473Z'
  biotoolsCURIE: biotools:flashida2
  biotoolsID: flashida2
  collectionID: []
  confidence_flag: null
  cost: null
  credit: []
  description: FLASHIda is an intelligent online data acquisition algorithm for top-down
    proteomics (TDP) that ensures the real-time selection of high-quality precursors
    of diverse proteoforms. FLASHIda combines fast decharging algorithms in FLASHDeconv
    and machine learning-based quality assessment to identify optimal precursors for
    fragmentation. Currently the C# source code and instruction of FLASHIda is available
    in here under a BSD three-clause license. We are working on merging FLASHIda into
    OpenMS.
  documentation: []
  download: []
  editPermission:
    authors: []
    type: private
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function: []
  homepage: https://www.openms.org/applications/flashida/
  homepage_status: 0
  language: []
  lastUpdate: '2025-04-30T11:39:17.046987Z'
  license: null
  link: []
  maturity: null
  name: FLASHIda
  operatingSystem: []
  otherID: []
  owner: samwein
  publication: []
  relation: []
  toolType: []
  topic: []
  validated: 0
  version: []
- accessibility: Open access
  additionDate: '2025-04-29T17:07:56.642694Z'
  biotoolsCURIE: biotools:biosurfdb
  biotoolsID: biosurfdb
  collectionID: []
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: jorge.oliveira@tecnico.ulisboa.pt
    fundrefid: null
    gridid: null
    name: Jorge S. Oliveira
    note: null
    orcidid: https://orcid.org/0000-0001-6425-2176
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: https://web.tecnico.ulisboa.pt/jorge.oliveira/
  - email: ana.freitas@tecnico.ulisboa.pt
    fundrefid: null
    gridid: null
    name: Ana Teresa Freitas
    note: null
    orcidid: http://orcid.org/0000-0003-4638-2879
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  - email: atrv@lncc.br
    fundrefid: null
    gridid: null
    name: Ana Tereza Ribeiro de Vasconcelos
    note: null
    orcidid: http://orcid.org/0000-0002-4632-2086
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  - email: lucymara.agnez@ufrn.br
    fundrefid: null
    gridid: null
    name: Lucymara Fassarella Agnez-Lima
    note: null
    orcidid: http://orcid.org/0000-0003-0642-3162
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  - email: gpo@biodata.pt
    fundrefid: null
    gridid: null
    name: Gil Poiares-Oliveira
    note: null
    orcidid: https://orcid.org/0000-0003-4638-2879
    rorid: null
    typeEntity: Person
    typeRole:
    - Maintainer
    url: https://web.tecnico.ulisboa.pt/gil.oliveira
  description: BioSurfDB is a online database for biodegradation and biosurfactants.
  documentation: []
  download: []
  editPermission:
    authors:
    - gpo
    type: group
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  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: Local alignment
      uri: http://edamontology.org/operation_0495
    output:
    - data:
        term: Nucleic acid sequence alignment
        uri: http://edamontology.org/data_1383
      format: []
    - data:
        term: Hybrid sequence alignment
        uri: http://edamontology.org/data_1385
      format: []
  - cmd: null
    input: []
    note: null
    operation:
    - term: Sequence database search (by property)
      uri: http://edamontology.org/operation_0349
    output:
    - data:
        term: Gene symbol
        uri: http://edamontology.org/data_1026
      format: []
    - data:
        term: Gene ID (NCBI)
        uri: http://edamontology.org/data_1027
      format: []
    - data:
        term: Gene name
        uri: http://edamontology.org/data_2299
      format: []
    - data:
        term: DNA sequence
        uri: http://edamontology.org/data_3494
      format: []
  homepage: https://www.biosurfdb.org
  homepage_status: 0
  language: []
  lastUpdate: '2025-04-29T17:35:41.655075Z'
  license: null
  link: []
  maturity: Mature
  name: BioSurfDB
  operatingSystem: []
  otherID: []
  owner: ELIXIR-PT
  publication:
  - doi: 10.1093/database/bav033
    metadata:
      abstract: 'Crude oil extraction, transportation and use provoke the contamination
        of countless ecosystems. Therefore, bioremediation through surfactants mobilization
        or biodegradation is an important subject, both economically and environmentally.
        Bioremediation research had a great boost with the recent advances in Metagenomics,
        as it enabled the sequencing of uncultured microorganisms providing new insights
        on surfactant-producing and/or oil-degrading bacteria. Many research studies
        are making available genomic data from unknown organisms obtained from metagenomics
        analysis of oil-contaminated environmental samples. These new datasets are
        presently demanding the development of new tools and data repositories tailored
        for the biological analysis in a context of bioremediation data analysis.
        This work presents BioSurfDB, www.biosurfdb.org, a curated relational information
        system integrating data from: (i) metagenomes; (ii) organisms; (iii) biodegradation
        relevant genes; proteins and their metabolic pathways; (iv) bioremediation
        experiments results, with specific pollutants treatment efficiencies by surfactant
        producing organisms; and (v) a biosurfactant-curated list, grouped by producing
        organism, surfactant name, class and reference. The main goal of this repository
        is to gather information on the characterization of biological compounds and
        mechanisms involved in biosurfactant production and/or biodegradation and
        make it available in a curated way and associated with a number of computational
        tools to support studies of genomic and metagenomic data.'
      authors:
      - name: Oliveira J.S.
      - name: Araujo W.
      - name: Sales A.I.L.
      - name: De Brito Guerra A.
      - name: Da Silva Araujo S.C.
      - name: De Vasconcelos A.T.R.
      - name: Agnez-Lima L.F.
      - name: Freitas A.T.
      citationCount: 30
      date: '2015-01-01T00:00:00Z'
      journal: Database
      title: 'BioSurfDB: Knowledge and algorithms to support biosurfactants and biodegradation
        studies'
    note: null
    pmcid: null
    pmid: null
    type:
    - Primary
    version: null
  relation: []
  toolType:
  - Database portal
  topic:
  - term: Biotechnology
    uri: http://edamontology.org/topic_3297
  - term: Microbiology
    uri: http://edamontology.org/topic_3301
  - term: Enzymes
    uri: http://edamontology.org/topic_0821
  validated: 0
  version: []
- accessibility: null
  additionDate: '2025-04-15T17:42:40.968987Z'
  biotoolsCURIE: biotools:dicom_file_integrity_checker_by_gibi230
  biotoolsID: dicom_file_integrity_checker_by_gibi230
  collectionID:
  - EUCAIM
  confidence_flag: null
  cost: null
  credit:
  - email: null
    fundrefid: null
    gridid: null
    name: GIBI230 - HULAFE
    note: null
    orcidid: null
    rorid: null
    typeEntity: null
    typeRole: []
    url: null
  description: 'The tool performs a DICOM quality check in terms of correct number
    of files per sequence, corrupted files, precise directory hierarchy, separated
    dynamic series merging them, interest series filtering/selection by specific series
    description lists and diffusion sequence identification by b-values. It applies
    the desired changes to the dataset and generates a report containing information
    about the selected sequences, corrupted files, missing files and merged files.


    Status : Containerized'
  documentation:
  - note: "Pedro-Miguel Martinez-Girones 1,*, Adrian Galiana-Bordera 1, Carina Soler-Pons\
      \ 1, Ignacio Gomez-Rico-Junquero 1, Ignacio Blanquer-Espert 3, Leonor Cerda-Alberich\
      \ 1 and Luis Marti-Bonmati 1,2\n1\tBiomedical Imaging Research Group (GIBI230),\
      \ La Fe Health Research Institute (IIS La Fe), Avenida Fernando Abril Martorell,\
      \ València, 46026, Spain.\n2\tLa Fe Medical Imaging Department, Avenida Fernando\
      \ Abril Martorell, València, 46026, Spain.\n3\tComputing Science Department,\
      \ Universitat Politècnica de València, Cami de Vera s/n, València, 46022, Spain."
    type:
    - General
    url: https://drive.google.com/file/d/1s8-nVAvSuAGTHWwun4AQcgHtRWclsFg2/view?usp=sharing
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  function: []
  homepage: https://harbor.eucaim.cancerimage.eu/harbor/projects/3/repositories/dicom_file_integrity_checker/artifacts-tab
  homepage_status: 0
  language:
  - Python
  lastUpdate: '2025-04-29T14:29:57.293088Z'
  license: null
  link:
  - note: null
    type:
    - Social media
    url: https://www.linkedin.com/company/grupo-de-investigaci%C3%B3n-biom%C3%A9dica-en-imagen/
  maturity: null
  name: DICOM File Integrity Checker
  operatingSystem:
  - Linux
  - Windows
  otherID: []
  owner: pedromiguel_martinez_HULAFE
  publication: []
  relation: []
  toolType:
  - Library
  topic:
  - term: Computer science
    uri: http://edamontology.org/topic_3316
  - term: Data acquisition
    uri: http://edamontology.org/topic_3077
  - term: Data management
    uri: http://edamontology.org/topic_3071
  validated: 0
  version:
  - 1.2.9
  - 2.0.0
- accessibility: null
  additionDate: '2025-04-17T13:07:06.039592Z'
  biotoolsCURIE: biotools:data_ingestion_tool_upv_reference_node
  biotoolsID: data_ingestion_tool_upv_reference_node
  collectionID:
  - EUCAIM
  confidence_flag: null
  cost: null
  credit: []
  description: User Interface Tool to ingest data to the UPV Reference Node through
    the QP-Insights API
  documentation: []
  download: []
  editPermission:
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  function: []
  homepage: https://harbor.eucaim.cancerimage.eu/harbor/projects/3/repositories/data_ingestion_tool_upv_reference_node/artifacts-tab
  homepage_status: 0
  language:
  - Python
  lastUpdate: '2025-04-29T14:28:43.124748Z'
  license: null
  link:
  - note: null
    type:
    - Social media
    url: https://www.linkedin.com/company/grupo-de-investigaci%C3%B3n-biom%C3%A9dica-en-imagen/
  maturity: null
  name: Data Ingestion Tool (UPV Reference Node)
  operatingSystem:
  - Windows
  otherID: []
  owner: casopon
  publication: []
  relation: []
  toolType:
  - Web application
  topic:
  - term: Data integration and warehousing
    uri: http://edamontology.org/topic_3366
  - term: Software engineering
    uri: http://edamontology.org/topic_3372
  - term: Imaging
    uri: http://edamontology.org/topic_3382
  validated: 0
  version:
  - 1.0.5
- accessibility: null
  additionDate: '2017-01-17T15:08:16Z'
  biotoolsCURIE: biotools:go_enrichment_tool
  biotoolsID: go_enrichment_tool
  collectionID:
  - GO Tools
  confidence_flag: null
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  - email: null
    fundrefid: null
    gridid: null
    name: null
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: http://geneontology.org/form/contact-go
  description: A tool for GO term enrichment analysis.
  documentation:
  - note: null
    type:
    - General
    url: http://geneontology.org/page/go-enrichment-analysis
  download: []
  editPermission:
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    - Taufik
    type: group
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  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Enrichment analysis
      uri: http://edamontology.org/operation_3501
    output: []
  homepage: http://geneontology.org/page/go-enrichment-analysis
  homepage_status: 0
  language: []
  lastUpdate: '2025-04-29T13:02:02.508664Z'
  license: null
  link: []
  maturity: null
  name: GO enrichment analysis tool
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: training_go_import
  publication:
  - doi: 10.1038/75556
    metadata: null
    note: null
    pmcid: PMC3037419
    pmid: '10802651'
    type: []
    version: null
  - doi: 10.1093/nar/gku1179
    metadata: null
    note: null
    pmcid: PMC4383973
    pmid: '25428369'
    type: []
    version: null
  relation: []
  toolType:
  - Web application
  topic:
  - term: Nucleic acids
    uri: http://edamontology.org/topic_0077
  - term: Proteins
    uri: http://edamontology.org/topic_0078
  - term: Ontology and terminology
    uri: http://edamontology.org/topic_0089
  validated: 1
  version: []
- accessibility: Restricted access
  additionDate: '2024-11-18T14:47:41.753481Z'
  biotoolsCURIE: biotools:trace4medicalimagecleaning
  biotoolsID: trace4medicalimagecleaning
  collectionID:
  - EUCAIM
  confidence_flag: null
  cost: Commercial
  credit: []
  description: Trace4MedicalImageCleaning™ is a tool aimed at automatically detecting
    and removing text in medical images, with a specific focus on 2D ultrasound and
    mammography studies.
  documentation: []
  download: []
  editPermission:
    authors: []
    type: private
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function: []
  homepage: http://deeptracetech.com/
  homepage_status: 0
  language:
  - MATLAB
  - Python
  lastUpdate: '2025-04-29T10:39:22.111602Z'
  license: Proprietary
  link: []
  maturity: Emerging
  name: Trace4MedicalImageCleaning
  operatingSystem:
  - Windows
  - Linux
  otherID: []
  owner: christian.salvatore
  publication: []
  relation: []
  toolType:
  - Library
  topic: []
  validated: 0
  version:
  - '1.0'
- accessibility: Open access
  additionDate: '2018-07-09T23:06:59Z'
  biotoolsCURIE: biotools:metexplore
  biotoolsID: metexplore
  collectionID:
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  - EBI Training Tools
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: fabien.jourdan@inra.fr
    fundrefid: null
    gridid: null
    name: Fabien JOURDAN
    note: null
    orcidid: https://orcid.org/0000-0001-9401-2894
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: https://sites.google.com/site/fabienjourdan/
  - email: ludovic.cottret@inra.fr
    fundrefid: null
    gridid: null
    name: null
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  - email: metexplore@oulouse.inra.fr
    fundrefid: null
    gridid: null
    name: null
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Support
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: MetaboHub
    note: null
    orcidid: null
    rorid: null
    typeEntity: Consortium
    typeRole: []
    url: null
  description: Metabolic network curation, visualisation and omics data analysis.
    It is possible to curate and annotate metabolic networks in a collaborative environment.
    Several tools are available for metabolomics data mapping in networks and visualisation.
  documentation:
  - note: User documentation on MetExplore main features.
    type:
    - User manual
    url: https://metexplore.toulouse.inra.fr/metexplore-doc/index.php
  - note: MetExploreViz (metabolic network visualsiation) documentation.
    type:
    - User manual
    url: https://metexplore.toulouse.inra.fr/metexploreViz/doc/documentation.php
  - note: MetExplore webservice documentation
    type:
    - API documentation
    url: https://metexplore.toulouse.inra.fr/metexplore-webservice-documentation/
  - note: How to use MetExplore to map metabolomics data onto metabolic networks.
    type:
    - Training material
    url: https://metexplore.pages.mia.inra.fr/metexplore-training/
  download: []
  editPermission:
    authors:
    - lcottret
    - Jennifer
    type: group
  elixirCommunity: []
  elixirNode:
  - France
  elixirPlatform:
  - Tools
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Pathway or network
        uri: http://edamontology.org/data_2600
      format:
      - term: SBML
        uri: http://edamontology.org/format_2585
    note: null
    operation:
    - term: Pathway or network analysis
      uri: http://edamontology.org/operation_2497
    - term: Pathway or network visualisation
      uri: http://edamontology.org/operation_3083
    output:
    - data:
        term: Pathway or network
        uri: http://edamontology.org/data_2600
      format:
      - term: xlsx
        uri: http://edamontology.org/format_3620
      - term: GML
        uri: http://edamontology.org/format_3822
      - term: SBML
        uri: http://edamontology.org/format_2585
      - term: PNG
        uri: http://edamontology.org/format_3603
      - term: JPG
        uri: http://edamontology.org/format_3579
      - term: SVG
        uri: http://edamontology.org/format_3604
  - cmd: null
    input: []
    note: null
    operation:
    - term: Pathway or network comparison
      uri: http://edamontology.org/operation_0277
    - term: Pathway or network visualisation
      uri: http://edamontology.org/operation_3083
    output: []
  homepage: http://www.metexplore.fr/
  homepage_status: 0
  language: []
  lastUpdate: '2025-04-28T07:17:11.601858Z'
  license: null
  link: []
  maturity: Mature
  name: MetExplore
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: fabienjourdan
  publication:
  - doi: 10.1093/nar/gky301
    metadata:
      abstract: Metabolism of an organism is composed of hundreds to thousands of
        interconnected biochemical reactions responding to environmental or genetic
        constraints. This metabolic network provides a rich knowledge to contextualize
        omics data and to elaborate hypotheses on metabolic modulations. Nevertheless,
        performing this kind of integrative analysis is challenging for end users
        with not sufficiently advanced computer skills since it requires the use of
        various tools and web servers. MetExplore offers an all-in-one online solution
        composed of interactive tools for metabolic network curation, network exploration
        and omics data analysis. In particular, it is possible to curate and annotate
        metabolic networks in a collaborative environment. The network exploration
        is also facilitated in MetExplore by a system of interactive tables connected
        to a powerful network visualization module. Finally, the contextualization
        of metabolic elements in the network and the calculation of over-representation
        statistics make it possible to interpret any kind of omics data.
      authors:
      - name: Cottret L.
      - name: Frainay C.
      - name: Chazalviel M.
      - name: Cabanettes F.
      - name: Gloaguen Y.
      - name: Camenen E.
      - name: Merlet B.
      - name: Heux S.
      - name: Portais J.-C.
      - name: Poupin N.
      - name: Vinson F.
      - name: Jourdan F.
      citationCount: 92
      date: '2018-07-02T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'MetExplore: Collaborative edition and exploration of metabolic networks'
    note: null
    pmcid: PMC6030842
    pmid: '29718355'
    type:
    - Primary
    version: null
  - doi: 10.1093/nar/gkq312
    metadata:
      abstract: High-throughput metabolomic experiments aim at identifying and ultimately
        quantifying all metabolites present in biological systems. The metabolites
        are interconnected through metabolic reactions, generally grouped into metabolic
        pathways. Classical metabolic maps provide a relational context to help interpret
        metabolomics experiments and a wide range of tools have been developed to
        help place metabolites within metabolic pathways. However, the representation
        of metabolites within separate disconnected pathways overlooks most of the
        connectivity of the metabolome. By definition, reference pathways cannot integrate
        novel pathways nor show relationships between metabolites that may be linked
        by common neighbours without being considered as joint members of a classical
        biochemical pathway. MetExplore is a web server that offers the possibility
        to link metabolites identified in untargeted metabolomics experiments within
        the context of genome-scale reconstructed metabolic networks. The analysis
        pipeline comprises mapping metabolomics data onto the specific metabolic network
        of an organism, then applying graph-based methods and advanced visualization
        tools to enhance data analysis. The MetExplore web server is freely accessible
        at http://metexplore.toulouse.inra.fr. © The Author(s) 2010. Published by
        Oxford University Press.
      authors:
      - name: Cottret L.
      - name: Wildridge D.
      - name: Vinson F.
      - name: Barrett M.P.
      - name: Charles H.
      - name: Sagot M.-F.
      - name: Jourdan F.
      citationCount: 144
      date: '2010-05-05T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'MetExplore: A web server to link metabolomic experiments and genome-scale
        metabolic networks'
    note: null
    pmcid: PMC2896158
    pmid: '20444866'
    type:
    - Primary
    version: null
  - doi: 10.1093/bioinformatics/btx588
    metadata:
      abstract: Summary MetExploreViz is an open source web component that can be
        easily embedded in any web site. It provides features dedicated to the visualization
        of metabolic networks and pathways and thus offers a flexible solution to
        analyse omics data in a biochemical context.
      authors:
      - name: Chazalviel M.
      - name: Frainay C.
      - name: Poupin N.
      - name: Vinson F.
      - name: Merlet B.
      - name: Gloaguen Y.
      - name: Cottret L.
      - name: Jourdan F.
      citationCount: 36
      date: '2018-01-15T00:00:00Z'
      journal: Bioinformatics
      title: 'MetExploreViz: Web component for interactive metabolic network visualization'
    note: null
    pmcid: PMC5860210
    pmid: '28968733'
    type:
    - Method
    version: null
  relation: []
  toolType:
  - Web application
  - Web service
  - Workbench
  topic:
  - term: Molecular interactions, pathways and networks
    uri: http://edamontology.org/topic_0602
  validated: 1
  version:
  - '2.40'
- accessibility: null
  additionDate: '2025-04-14T16:46:40.806977Z'
  biotoolsCURIE: biotools:eucaim_dicom_anonymizer
  biotoolsID: eucaim_dicom_anonymizer
  collectionID:
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  confidence_flag: null
  cost: null
  credit: []
  description: The EUCAIM DICOM Anonymizer  anonymizes a set of DICOM files. It supports
    both anonymization on a case-by-case scenario, meaning one DICOM Study at a time
    (single-mode) or on multiple cases concurrently (batch mode). Additionally it
    hashes and links clinical data.
  documentation: []
  download: []
  editPermission:
    authors: []
    type: private
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  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Anonymisation
      uri: http://edamontology.org/operation_3283
    output: []
  homepage: https://harbor.eucaim.cancerimage.eu/harbor/projects/3/repositories/eucaim-anonymizer/
  homepage_status: 0
  language:
  - C++
  lastUpdate: '2025-04-24T13:06:17.802389Z'
  license: null
  link: []
  maturity: null
  name: EUCAIM DICOM Anonymizer
  operatingSystem:
  - Mac
  - Windows
  - Linux
  otherID: []
  owner: vkalokyri
  publication: []
  relation: []
  toolType: []
  topic:
  - term: Medical imaging
    uri: http://edamontology.org/topic_3384
  validated: 0
  version:
  - 0.12.0
- accessibility: null
  additionDate: '2023-12-06T15:45:20.587393Z'
  biotoolsCURIE: biotools:sylph
  biotoolsID: sylph
  collectionID: []
  confidence_flag: null
  cost: null
  credit: []
  description: fast and precise species-level metagenomic profiling with ANIs
  documentation: []
  download: []
  editPermission:
    authors:
    - vashokan
    type: group
  elixirCommunity: []
  elixirNode: []
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  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: DNA sequence
        uri: http://edamontology.org/data_3494
      format:
      - term: FASTQ
        uri: http://edamontology.org/format_1930
    note: null
    operation:
    - term: Taxonomic classification
      uri: http://edamontology.org/operation_3460
    output:
    - data:
        term: Taxonomy
        uri: http://edamontology.org/data_3028
      format:
      - term: DSV
        uri: http://edamontology.org/format_3751
  homepage: https://github.com/bluenote-1577/sylph
  homepage_status: 0
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  lastUpdate: '2025-04-24T09:31:08.371089Z'
  license: null
  link: []
  maturity: null
  name: sylph
  operatingSystem:
  - Linux
  otherID: []
  owner: pauffret
  publication: []
  relation: []
  toolType:
  - Command-line tool
  topic:
  - term: Metagenomics
    uri: http://edamontology.org/topic_3174
  validated: 0
  version:
  - v0.4.1
- accessibility: null
  additionDate: '2025-04-23T10:31:12.521148Z'
  biotoolsCURIE: biotools:longitools_exposome_toolbox
  biotoolsID: longitools_exposome_toolbox
  collectionID: []
  confidence_flag: null
  cost: null
  credit:
  - email: karim.lekadir@ub.edu
    fundrefid: null
    gridid: null
    name: Karim Lekadir
    note: null
    orcidid: https://orcid.org/0000-0002-9456-1612
    rorid: null
    typeEntity: null
    typeRole:
    - Primary contact
    url: null
  description: The LongITools toolbox is an open-source platform developed to support
    exposome research analysis. This cloud-based computational environment enables
    researchers to construct customized analytical platforms suited to their specific
    research requirements. The system provides a web-based interface that integrates
    various analytical resources, including statistical tools, computational pipelines,
    connections to external data repositories, and data visualization capabilities.
  documentation:
  - note: null
    type:
    - Quick start guide
    url: https://github.com/inab/openVRE/tree/longitools
  download: []
  editPermission:
    authors: []
    type: private
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  elixir_badge: 0
  function: []
  homepage: https://longitools.bsc.es/vre/
  homepage_status: 0
  language:
  - R
  - Python
  - PHP
  lastUpdate: '2025-04-23T10:31:21.719823Z'
  license: null
  link:
  - note: null
    type:
    - Other
    url: https://longitools.bsc.es/vre/
  maturity: Mature
  name: Longitools Exposome Toolbox
  operatingSystem: []
  otherID: []
  owner: noussair
  publication: []
  relation: []
  toolType:
  - Web application
  - Command-line tool
  - Web service
  topic:
  - term: Bioinformatics
    uri: http://edamontology.org/topic_0091
  - term: Medicines research and development
    uri: http://edamontology.org/topic_3376
  validated: 0
  version:
  - '2.0'
- 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: Statistical method that computes the abundance of species in DNA sequences
    from a metagenomics sample.
  documentation:
  - note: null
    type:
    - User manual
    url: https://ccb.jhu.edu/software/bracken/index.shtml?t=manual
  download: []
  editPermission:
    authors:
    - animalandcropgenomics
    - ELIXIR-CZ
    - bebatut
    - vashokan
    type: group
  elixirCommunity: []
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  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Statistical calculation
      uri: http://edamontology.org/operation_2238
    output: []
  homepage: https://ccb.jhu.edu/software/bracken/
  homepage_status: 0
  language:
  - Perl
  - Python
  lastUpdate: '2025-04-23T07:43:18.805990Z'
  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: 900
      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: []
  toolType:
  - Command-line tool
  topic:
  - term: Metagenomics
    uri: http://edamontology.org/topic_3174
  - term: Microbial ecology
    uri: http://edamontology.org/topic_3697
  validated: 1
  version: []
- accessibility: Open access (with restrictions)
  additionDate: '2017-04-22T17:35:18Z'
  biotoolsCURIE: biotools:gemma
  biotoolsID: gemma
  collectionID: []
  confidence_flag: null
  cost: Free of charge (with restrictions)
  credit:
  - email: pavlab-support@msl.ubc.ca
    fundrefid: null
    gridid: null
    name: Pavlidis Lab Support
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Support
    url: https://pavlab.msl.ubc.ca/
  description: Gemma provides data, experimental design annotations, and differential
    expression analysis results for thousands of microarray and RNA-seq experiments.
    We re-analyze raw data from public sources (primarily NCBI GEO), annotate experimental
    conditions, conduct quality control and compute differential expression using
    standardized procedures. We have especially good coverage of experiments relevant
    to the nervous system.
  documentation:
  - note: null
    type:
    - General
    url: https://pavlidislab.github.io/Gemma/
  - note: Documentation for the Gemma REST API.
    type:
    - API documentation
    url: https://gemma.msl.ubc.ca/resources/restapidocs/
  download:
  - note: null
    type: Downloads page
    url: https://github.com/PavlidisLab/Gemma/releases
    version: null
  editPermission:
    authors:
    - artrymix
    - paulpavlidis
    type: group
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  elixirNode: []
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  function:
  - cmd: null
    input:
    - data:
        term: Gene expression matrix
        uri: http://edamontology.org/data_3112
      format: []
    - data:
        term: Raw microarray data
        uri: http://edamontology.org/data_3110
      format: []
    note: null
    operation:
    - term: Differential gene expression profiling
      uri: http://edamontology.org/operation_3223
    output:
    - data:
        term: Heat map
        uri: http://edamontology.org/data_1636
      format: []
    - data:
        term: Quality control report
        uri: http://edamontology.org/data_3914
      format: []
  homepage: https://gemma.msl.ubc.ca/
  homepage_status: 0
  language:
  - Java
  - JavaScript
  lastUpdate: '2025-04-22T22:09:03.811075Z'
  license: CC-BY-NC-4.0
  link:
  - note: null
    type:
    - Repository
    - Issue tracker
    url: https://github.com/PavlidisLab/Gemma
  maturity: Mature
  name: Gemma
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: artrymix
  publication:
  - doi: 10.1093/bioinformatics/btp259
    metadata:
      abstract: 'Motivation: Many microarray datasets are available online with formalized
        standards describing the probe sequences and expression values. Unfortunately,
        the description, conditions and parameters of the experiments are less commonly
        formalized and often occur as natural language text. This hinders searching,
        high-throughput analysis, organization and integration of the datasets. Results:
        We use the lexical resources and software tools from the Unified Medical Language
        System (UMLS) to extract concepts from text. We then link the UMLS concepts
        to classes in open biomedical ontologies. The result is accessible and clear
        semantic annotations of gene expression experiments. We applied the method
        to 595 expression experiments from Gemma, a resource for re-use and meta-analysis
        of gene expression profiling data. We evaluated and corrected all stages of
        the annotation process. The majority of missed annotations were due to a lack
        of cross-references. The most error-prone stage was the extraction of concepts
        from phrases. Final review of the annotations in context of the experiments
        revealed 89% precision. A naive system, lacking the phrase to concept corrections
        is 68% precise. We have integrated this annotation pipeline into Gemma. ©
        2009 The Author(s).'
      authors:
      - name: French L.
      - name: Lane S.
      - name: Law T.
      - name: Xu L.
      - name: Pavlidis P.
      citationCount: 9
      date: '2009-06-09T00:00:00Z'
      journal: Bioinformatics
      title: Application and evaluation of automated semantic annotation of gene expression
        experiments
    note: null
    pmcid: PMC2687992
    pmid: '19376825'
    type:
    - Primary
    version: null
  - doi: 10.1093/database/baab006
    metadata:
      abstract: 'Vast amounts of transcriptomic data reside in public repositories,
        but effective reuse remains challenging. Issues include unstructured dataset
        metadata, inconsistent data processing and quality control, and inconsistent
        probe-gene mappings across microarray technologies. Thus, extensive curation
        and data reprocessing are necessary prior to any reuse. The Gemma bioinformatics
        system was created to help address these issues. Gemma consists of a database
        of curated transcriptomic datasets, analytical software, a web interface and
        web services. Here we present an update on Gemma''s holdings, data processing
        and analysis pipelines, our curation guidelines, and software features. As
        of June 2020, Gemma contains 10 811 manually curated datasets (primarily human,
        mouse and rat), over 395 000 samples and hundreds of curated transcriptomic
        platforms (both microarray and RNA sequencing). Dataset topics were represented
        with 10 215 distinct terms from 12 ontologies, for a total of 54 316 topic
        annotations (mean topics/dataset = 5.2). While Gemma has broad coverage of
        conditions and tissues, it captures a large majority of available brain-related
        datasets, accounting for 34% of its holdings. Users can access the curated
        data and differential expression analyses through the Gemma website, RESTful
        service and an R package. Database URL: https://gemma.msl.ubc.ca/home.html'
      authors:
      - name: Lim N.
      - name: Tesar S.
      - name: Belmadani M.
      - name: Poirier-Morency G.
      - name: Mancarci B.O.
      - name: Sicherman J.
      - name: Jacobson M.
      - name: Leong J.
      - name: Tan P.
      - name: Pavlidis P.
      citationCount: 21
      date: '2021-01-01T00:00:00Z'
      journal: Database
      title: Curation of over 10 000 transcriptomic studies to enable data reuse
    note: null
    pmcid: PMC7904053
    pmid: '33599246'
    type:
    - Primary
    version: null
  relation:
  - biotoolsID: rsem
    type: uses
  - biotoolsID: multiqc
    type: uses
  - biotoolsID: cutadapt
    type: uses
  - biotoolsID: star
    type: uses
  - biotoolsID: ncbi_geo
    type: uses
  - biotoolsID: sradb
    type: uses
  - biotoolsID: ncbi_gene
    type: uses
  toolType:
  - Web application
  - Web API
  topic:
  - term: RNA-Seq
    uri: http://edamontology.org/topic_3170
  - term: Gene expression
    uri: http://edamontology.org/topic_0203
  - term: Genetics
    uri: http://edamontology.org/topic_3053
  - term: Microarray experiment
    uri: http://edamontology.org/topic_3518
  - term: Data curation and archival
    uri: http://edamontology.org/topic_0219
  validated: 1
  version:
  - 1.31.13
- accessibility: null
  additionDate: '2017-08-20T15:57:59Z'
  biotoolsCURIE: biotools:metaphlan
  biotoolsID: metaphlan
  collectionID:
  - Animal and Crop Genomics
  confidence_flag: null
  cost: null
  credit:
  - email: null
    fundrefid: null
    gridid: null
    name: null
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: https://groups.google.com/forum/#!forum/metaphlan-users
  description: Computational tool for profiling the composition of microbial communities
    from metagenomic shotgun sequencing data.
  documentation:
  - note: null
    type:
    - General
    url: https://github.com/biobakery/MetaPhlAn
  download: []
  editPermission:
    authors:
    - animalandcropgenomics
    - ELIXIR-CZ
    - bebatut
    - vashokan
    type: group
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: metaphlan <fastq_input> --input_type fastq -o <output>
    input:
    - data:
        term: DNA sequence
        uri: http://edamontology.org/data_3494
      format:
      - term: FASTQ
        uri: http://edamontology.org/format_1930
      - term: FASTA
        uri: http://edamontology.org/format_1929
      - term: SAM
        uri: http://edamontology.org/format_2573
    note: null
    operation:
    - term: Taxonomic classification
      uri: http://edamontology.org/operation_3460
    output:
    - data:
        term: Taxonomy
        uri: http://edamontology.org/data_3028
      format:
      - term: DSV
        uri: http://edamontology.org/format_3751
  - cmd: sgb_to_gtdb_profile.py -i <metaphlan_output> -o <gtdb_metaphlan_output>
    input:
    - data:
        term: Taxonomy
        uri: http://edamontology.org/data_3028
      format:
      - term: DSV
        uri: http://edamontology.org/format_3751
    note: Convert SGB-based profile to GTDB taxonomy
    operation:
    - term: Taxonomic classification
      uri: http://edamontology.org/operation_3460
    output:
    - data:
        term: Taxonomy
        uri: http://edamontology.org/data_3028
      format:
      - term: DSV
        uri: http://edamontology.org/format_3751
  homepage: http://segatalab.cibio.unitn.it/tools/metaphlan/index.html
  homepage_status: 0
  language:
  - Python
  lastUpdate: '2025-04-22T12:44:24.859435Z'
  license: MIT
  link: []
  maturity: null
  name: MetaPhlAn
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: admin
  publication:
  - doi: 10.1038/nmeth.2066
    metadata:
      abstract: Metagenomic shotgun sequencing data can identify microbes populating
        a microbial community and their proportions, but existing taxonomic profiling
        methods are inefficient for increasingly large data sets. We present an approach
        that uses clade-specific marker genes to unambiguously assign reads to microbial
        clades more accurately and >50Ã-faster than current approaches. We validated
        our metagenomic phylogenetic analysis tool, MetaPhlAn, on terabases of short
        reads and provide the largest metagenomic profiling to date of the human gut.
        It can be accessed at http://huttenhower.sph.harvard.edu/ metaphlan/. © 2012
        Nature America, Inc. All rights reserved.
      authors:
      - name: Segata N.
      - name: Waldron L.
      - name: Ballarini A.
      - name: Narasimhan V.
      - name: Jousson O.
      - name: Huttenhower C.
      citationCount: 1300
      date: '2012-08-01T00:00:00Z'
      journal: Nature Methods
      title: Metagenomic microbial community profiling using unique clade-specific
        marker genes
    note: null
    pmcid: PMC3443552
    pmid: '22688413'
    type:
    - Primary
    version: null
  relation: []
  toolType:
  - Command-line tool
  topic:
  - term: Metagenomics
    uri: http://edamontology.org/topic_3174
  - term: Phylogenomics
    uri: http://edamontology.org/topic_0194
  validated: 1
  version: []
- accessibility: null
  additionDate: '2025-04-21T21:06:51.624399Z'
  biotoolsCURIE: biotools:samclip
  biotoolsID: samclip
  collectionID: []
  confidence_flag: null
  cost: null
  credit: []
  description: Filter SAM file for soft and hard clipped alignments
  documentation:
  - note: null
    type:
    - General
    url: https://github.com/tseemann/samclip
  download:
  - note: null
    type: Software package
    url: https://anaconda.org/bioconda/samclip
    version: 0.4.0
  editPermission:
    authors: []
    type: group
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Nucleic acid sequence alignment
        uri: http://edamontology.org/data_1383
      format: []
    note: null
    operation:
    - term: Sequence trimming
      uri: http://edamontology.org/operation_3192
    output:
    - data:
        term: Nucleic acid sequence alignment
        uri: http://edamontology.org/data_1383
      format: []
  homepage: https://github.com/tseemann/samclip
  homepage_status: 0
  language:
  - Perl
  lastUpdate: '2025-04-21T21:06:51.626575Z'
  license: null
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/tseemann/samclip
  maturity: null
  name: samclip
  operatingSystem:
  - Linux
  - Mac
  otherID: []
  owner: emmcauley
  publication: []
  relation: []
  toolType:
  - Command-line tool
  topic:
  - term: Genomics
    uri: http://edamontology.org/topic_0622
  - term: Bioinformatics
    uri: http://edamontology.org/topic_0091
  - term: Mapping
    uri: http://edamontology.org/topic_0102
  validated: 0
  version:
  - 0.4.0
- accessibility: null
  additionDate: '2015-06-29T10:14:28Z'
  biotoolsCURIE: biotools:netpicorna
  biotoolsID: netpicorna
  collectionID: []
  confidence_flag: null
  cost: Free of charge (with restrictions)
  credit:
  - email: null
    fundrefid: null
    gridid: null
    name: CBS
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
    - Provider
    url: null
  - email: nikob@cbs.dtu.dk
    fundrefid: null
    gridid: null
    name: Nikolaj Sorgenfrei Blom
    note: null
    orcidid: https://orcid.org/0000-0001-7787-7853
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  description: Neural network predictions of cleavage sites of picornaviral proteases.
  documentation:
  - note: null
    type:
    - General
    url: http://www.cbs.dtu.dk/services/NetPicoRNA/instructions.php
  download: []
  editPermission:
    authors:
    - powehi
    type: group
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Sequence
        uri: http://edamontology.org/data_2044
      format:
      - term: FASTA
        uri: http://edamontology.org/format_1929
    note: produces neural network predictions of cleavage sites of picornaviral proteases
    operation:
    - term: Protein cleavage site prediction
      uri: http://edamontology.org/operation_0422
    output:
    - data:
        term: Protein features
        uri: http://edamontology.org/data_1277
      format:
      - term: Textual format
        uri: http://edamontology.org/format_2330
    - data:
        term: Sequence report
        uri: http://edamontology.org/data_2955
      format:
      - term: Binary format
        uri: http://edamontology.org/format_2333
  homepage: http://cbs.dtu.dk/services/NetPicoRNA/
  homepage_status: 0
  language: []
  lastUpdate: '2025-04-21T12:49:56.070719Z'
  license: Other
  link:
  - note: null
    type:
    - Software catalogue
    url: http://cbs.dtu.dk/services
  maturity: Legacy
  name: NetPicoRNA
  operatingSystem:
  - Linux
  otherID: []
  owner: powehi
  publication:
  - doi: 10.1002/pro.5560051107
    metadata:
      abstract: Picornaviral proteinases are responsible for maturation cleavages
        of the viral polyprotein, but also catalyze the degradation of cellular targets.
        Using graphical visualization techniques and neural network algorithms, we
        have investigated the sequence specificity of the two proteinases 2A(pro)
        and 3C(pro). The cleavage of VP0 (giving rise to VP2 and VP4), which is carried
        out by a so-far unknown proteinase, was also examined. In combination with
        a novel surface exposure prediction algorithm, our neural network approach
        successfully distinguishes known cleavage sites from noncleavage sites and
        yields a more consistent definition of features common to these sites. The
        method is able to predict experimentally determined cleavage sites in cellular
        proteins. We present a list of mammalian and other proteins that are predicted
        to be possible targets for the vital proteinases. Whether these proteins are
        indeed cleaved awaits experimental verification. Additionally, we report several
        errors detected in the protein databases.
      authors:
      - name: Blom N.
      - name: Hansen J.
      - name: Blaas D.
      - name: Brunak S.
      citationCount: 204
      date: '1996-01-01T00:00:00Z'
      journal: Protein Science
      title: 'Cleavage site analysis in picornaviral polyproteins: Discovering cellular
        targets by neural networks'
    note: null
    pmcid: PMC2143287
    pmid: '8931139'
    type:
    - Primary
    version: null
  relation: []
  toolType:
  - Web application
  topic:
  - term: Protein sites, features and motifs
    uri: http://edamontology.org/topic_3510
  - term: Sequence sites, features and motifs
    uri: http://edamontology.org/topic_0160
  validated: 1
  version:
  - '1.0'
- 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:
    - Primary contact
    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:
    authors: []
    type: private
  elixirCommunity: []
  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: '2025-04-18T17:40:38.228809Z'
  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: With the desire to model population genetic processes under increasingly
        realistic scenarios, forward genetic simulations have become a critical part
        of the toolbox of modern evolutionary biology. The SLiM forward genetic simulation
        framework is one of the most powerful and widely used tools in this area.
        However, its foundation in the Wright-Fisher model has been found to pose
        an obstacle to implementing many types of models; it is difficult to adapt
        the Wright-Fisher model, with its many assumptions, to modeling ecologically
        realistic scenarios such as explicit space, overlapping generations, individual
        variation in reproduction, density-dependent population regulation, individual
        variation in dispersal or migration, local extinction and recolonization,
        mating between subpopulations, age structure, fitness-based survival and hard
        selection, emergent sex ratios, and so forth. In response to this need, we
        here introduce SLiM 3, which contains two key advancements aimed at abolishing
        these limitations. First, the new non-Wright-Fisher or "nonWF" model type
        provides a much more flexible foundation that allows the easy implementation
        of all of the above scenarios and many more. Second, SLiM 3 adds support for
        continuous space, including spatial interactions and spatial maps of environmental
        variables. We provide a conceptual overview of these new features, and present
        several example models to illustrate their use.
      authors:
      - name: Haller B.C.
      - name: Messer P.W.
      citationCount: 504
      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:
    - Other
    version: null
  - doi: 10.1093/molbev/msy237
    metadata:
      abstract: The SLiM forward genetic simulation framework has proved to be a powerful
        and flexible tool for population genetic modeling. However, as a complex piece
        of software with many features that allow simulating a diverse assortment
        of evolutionary models, its initial learning curve can be difficult. Here
        we provide a step-by-step demonstration of how to build a simple evolutionary
        model in SLiM 3, to help new users get started. We will begin with a panmictic
        neutral model, and build up to a model of the evolution of a polygenic quantitative
        trait under selection for an environmental phenotypic optimum.
      authors:
      - name: Haller B.C.
      - name: Messer P.W.
      citationCount: 12
      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:
    - Usage
    version: null
  - doi: 10.1111/1755-0998.12968
    metadata:
      abstract: 'There is an increasing demand for evolutionary models to incorporate
        relatively realistic dynamics, ranging from selection at many genomic sites
        to complex demography, population structure, and ecological interactions.
        Such models can generally be implemented as individual-based forward simulations,
        but the large computational overhead of these models often makes simulation
        of whole chromosome sequences in large populations infeasible. This situation
        presents an important obstacle to the field that requires conceptual advances
        to overcome. The recently developed tree-sequence recording method (Kelleher,
        Thornton, Ashander, & Ralph, 2018), which stores the genealogical history
        of all genomes in the simulated population, could provide such an advance.
        This method has several benefits: (1) it allows neutral mutations to be omitted
        entirely from forward-time simulations and added later, thereby dramatically
        improving computational efficiency; (2) it allows neutral burn-in to be constructed
        extremely efficiently after the fact, using “recapitation”; (3) it allows
        direct examination and analysis of the genealogical trees along the genome;
        and (4) it provides a compact representation of a population''s genealogy
        that can be analysed in Python using the msprime package. We have implemented
        the tree-sequence recording method in SLiM 3 (a free, open-source evolutionary
        simulation software package) and extended it to allow the recording of non-neutral
        mutations, greatly broadening the utility of this method. To demonstrate the
        versatility and performance of this approach, we showcase several practical
        applications that would have been beyond the reach of previously existing
        methods, opening up new horizons for the modelling and exploration of evolutionary
        processes.'
      authors:
      - name: Haller B.C.
      - name: Galloway J.
      - name: Kelleher J.
      - name: Messer P.W.
      - name: Ralph P.L.
      citationCount: 109
      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:
    - Method
    version: null
  - doi: 10.1086/723601
    metadata:
      abstract: The SLiM software framework for genetically explicit forward simulation
        has been widely used in population genetics. However, it has been largely
        restricted to modeling only a single species, which has limited its broader
        utility in evolutionary biology. Indeed, to our knowledge no general-purpose,
        flexible modeling framework exists that provides support for simulating multiple
        species while also providing other key features, such as explicit genetics
        and continuous space. The lack of such software has limited our ability to
        model higher biological levels such as communities, eco-systems, coevolutionary
        and eco-evolutionary processes, and bio-diversity, which is crucial for many
        purposes, from extending our basic understanding of evolutionary ecology to
        informing conservation and management decisions. We here announce the release
        of SLiM 4, which fills this important gap by adding support for multiple species,
        including ecological interactions between species such as predation, parasitism,
        and mutualism, and illustrate its new features with examples.
      authors:
      - name: Haller B.C.
      - name: Messer P.W.
      citationCount: 79
      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: null
  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:
  - '5.0'
- accessibility: null
  additionDate: '2025-04-18T15:04:18.411979Z'
  biotoolsCURIE: biotools:dicom_tags_extractor
  biotoolsID: dicom_tags_extractor
  collectionID:
  - EUCAIM
  confidence_flag: null
  cost: Free of charge (with restrictions)
  credit:
  - email: null
    fundrefid: null
    gridid: null
    name: BC|Platforms
    note: null
    orcidid: null
    rorid: null
    typeEntity: null
    typeRole: []
    url: null
  description: 'The tool scans the imaging DICOM files of a defined directory at the
    series level, and produces as output one single JSON file containing all the DICOM
    tags for each detected series.

    If a list of selected DICOM tags is provided, the tool can also produce one single
    csv file containing the listed DICOM tags.

    To use this tool, the user can download an executable file (.exe). Two execution
    modes are available : manual execution and command line execution.

    For the tool to scan data successfully, it is important that : 1/ the extension
    “.dcm” is visible, as the tool only scans those files, and discard any other;
    2/ each DICOM series has its own folder, as the tool gets a single .dcm file from
    each folder and extracts the tags.'
  documentation: []
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  elixir_badge: 0
  function:
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    note: null
    operation:
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      uri: http://edamontology.org/operation_0335
    output: []
  homepage: https://www.bcplatforms.com/
  homepage_status: 0
  language: []
  lastUpdate: '2025-04-18T15:15:06.042639Z'
  license: Not licensed
  link:
  - note: null
    type:
    - Other
    url: https://www.bcplatforms.com/
  maturity: Emerging
  name: DICOM tags extractor
  operatingSystem: []
  otherID: []
  owner: lsaint-aubert
  publication: []
  relation: []
  toolType:
  - Command-line tool
  topic:
  - term: Data architecture, analysis and design
    uri: http://edamontology.org/topic_3365
  - term: Medical imaging
    uri: http://edamontology.org/topic_3384
  validated: 0
  version: []
- accessibility: null
  additionDate: '2025-04-16T19:07:02.592454Z'
  biotoolsCURIE: biotools:enrsa
  biotoolsID: enrsa
  collectionID: []
  confidence_flag: null
  cost: null
  credit: []
  description: eNRSA is an enhanced version of NRSA for analyzing nascent transcription
    profiles generated by PRO-seq, GRO-seq, (m)NET-seq, and Butt-seq data.
  documentation:
  - note: null
    type:
    - User manual
    url: https://bioinfo.vanderbilt.edu/eNRSA/
  download:
  - note: null
    type: Source code
    url: https://github.com/chc-code/eNRSA
    version: null
  editPermission:
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    type: private
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  homepage: https://bioinfo.vanderbilt.edu/eNRSA/
  homepage_status: 0
  language: []
  lastUpdate: '2025-04-16T19:07:12.773939Z'
  license: null
  link:
  - note: link to github repo
    type:
    - Software catalogue
    url: https://github.com/chc-code/eNRSA
  maturity: null
  name: eNRSA
  operatingSystem: []
  otherID: []
  owner: chcvandy
  publication: []
  relation: []
  toolType: []
  topic: []
  validated: 0
  version: []
- accessibility: null
  additionDate: '2016-04-15T11:52:42Z'
  biotoolsCURIE: biotools:comparems2
  biotoolsID: comparems2
  collectionID:
  - ms-utils
  - Proteomics
  confidence_flag: tool
  cost: Free of charge
  credit:
  - email: null
    fundrefid: null
    gridid: null
    name: lumc.nl
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
    - Support
    url: https://www.lumc.nl
  - email: magnus.palmblad@gmail.com
    fundrefid: null
    gridid: null
    name: Magnus Palmblad
    note: null
    orcidid: http://orcid.org/0000-0002-5865-8994
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    - Primary contact
    - Documentor
    url: https://github.com/magnuspalmblad
  - email: null
    fundrefid: null
    gridid: null
    name: Rob Marissen
    note: null
    orcidid: https://orcid.org/0000-0002-1220-9173
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: https://github.com/524D
  description: compareMS2 is a tool for comparing sets of (tandem) mass spectra for
    clustering samples, molecular phylogenetics, identification of biological species
    or tissues, and quality control. compareMS2 currently consumes Mascot Generic
    Format, or MGF, and produces output in a variety of common image and distance
    matrix formats.
  documentation:
  - note: null
    type:
    - General
    - Command-line options
    url: http://www.ms-utils.org/compareMS2.html
  - note: null
    type:
    - General
    - User manual
    - Command-line options
    - Installation instructions
    url: https://github.com/524D/compareMS2
  download:
  - note: null
    type: Source code
    url: http://www.ms-utils.org/compareMS2.c
    version: '1.0'
  - note: null
    type: Binaries
    url: http://www.ms-utils.org/compareMS2.html
    version: '1.0'
  - note: null
    type: Source code
    url: http://www.ms-utils.org/compareMS2.c
    version: '1.0'
  - note: null
    type: Source code
    url: https://github.com/524D/compareMS2/tree/main/src
    version: '2.0'
  - note: null
    type: Binaries
    url: https://github.com/524D/compareMS2/tree/main
    version: '2.0'
  editPermission:
    authors:
    - proteomics.bio.tools
    type: group
  elixirCommunity:
  - Proteomics
  elixirNode:
  - Netherlands
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Mass spectrometry data
        uri: http://edamontology.org/data_2536
      format:
      - term: MGF
        uri: http://edamontology.org/format_3651
    note: null
    operation:
    - term: Comparison
      uri: http://edamontology.org/operation_2424
    - term: Phylogenetic tree visualisation
      uri: http://edamontology.org/operation_0567
    output:
    - data:
        term: Species tree
        uri: http://edamontology.org/data_3272
      format:
      - term: PNG
        uri: http://edamontology.org/format_3603
      - term: SVG
        uri: http://edamontology.org/format_3604
    - data:
        term: Distance matrix
        uri: http://edamontology.org/data_2855
      format:
      - term: mega
        uri: http://edamontology.org/format_1991
      - term: Nexus format
        uri: http://edamontology.org/format_1912
      - term: newick
        uri: http://edamontology.org/format_1910
  homepage: https://github.com/524D/compareMS2
  homepage_status: 0
  language:
  - C
  - JavaScript
  lastUpdate: '2025-04-16T14:22:04.957317Z'
  license: MIT
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/524D/compareMS2
  - note: null
    type:
    - Software catalogue
    url: https://www.ms-utils.org/compareMS2.html
  - note: null
    type:
    - Software catalogue
    url: https://research-software-directory.org/software/comparems2
  maturity: Mature
  name: compareMS2
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: n.m.palmblad@lumc.nl
  publication:
  - doi: 10.1002/rcm.6162
    metadata:
      abstract: 'Rationale: Molecular phylogenetics is the study of evolution and
        relatedness of organisms or genes. Mass spectrometry is used routinely for
        bacterial identification and has also been used for phylogenetic analysis,
        for instance from bone material. Unfortunately, only a small fraction of the
        acquired tandem mass spectra allow direct interpretation. Methods: We describe
        a new algorithm and software for molecular phylogenetics using pairwise comparisons
        of tandem mass spectra from enzymatically digested proteins. The spectra need
        not be annotated and all acquired data is used in the analysis. To demonstrate
        the method, we analyzed tryptic digests of sera from four great apes and two
        other primates. Results: The distribution of spectra dot products for thousands
        of tandem mass spectra collected from two samples provides a measure on the
        fraction of shared peptides between the two samples. When inverted, this becomes
        a distance metric. By pairwise comparison between species and averaging over
        four individuals per species, it was possible to reconstruct the unique correct
        phylogenetic tree for the great apes and other primates. Conclusions: The
        new method described here has several attractive features compared with existing
        methods, among them simplicity, the unbiased use of all acquired data rather
        than a small subset of spectra, and the potential use of heavily degraded
        proteins or proteins with a priori unknown modifications. © 2012 John Wiley
        & Sons, Ltd.'
      authors:
      - name: Palmblad M.
      - name: Deelder A.M.
      citationCount: 30
      date: '2012-04-15T00:00:00Z'
      journal: Rapid Communications in Mass Spectrometry
      title: Molecular phylogenetics by direct comparison of tandem mass spectra
    note: null
    pmcid: null
    pmid: '22368051'
    type:
    - Primary
    version: '1.0'
  - doi: 10.1021/acs.jproteome.2c00457
    metadata:
      abstract: It has long been known that biological species can be identified from
        mass spectrometry data alone. Ten years ago, we described a method and software
        tool, compareMS2, for calculating a distance between sets of tandem mass spectra,
        as routinely collected in proteomics. This method has seen use in species
        identification and mixture characterization in food and feed products, as
        well as other applications. Here, we present the first major update of this
        software, including a new metric, a graphical user interface and additional
        functionality. The data have been deposited to ProteomeXchange with dataset
        identifier PXD034932.
      authors:
      - name: Marissen R.
      - name: Varunjikar M.S.
      - name: Laros J.F.J.
      - name: Rasinger J.D.
      - name: Neely B.A.
      - name: Palmblad M.
      citationCount: 7
      date: '2023-02-03T00:00:00Z'
      journal: Journal of Proteome Research
      title: 'compareMS2 2.0: An Improved Software for Comparing Tandem Mass Spectrometry
        Datasets'
    note: null
    pmcid: PMC9903320
    pmid: '36173614'
    type:
    - Primary
    version: '2.0'
  - doi: 10.1021/acs.jproteome.1c00528
    metadata:
      abstract: Science is full of overlooked and undervalued research waiting to
        be rediscovered. Proteomics is no exception. In this perspective, we follow
        the ripples from a 1960 study of Zuckerkandl, Jones, and Pauling comparing
        tryptic peptides across animal species. This pioneering work directly led
        to the molecular clock hypothesis and the ensuing explosion in molecular phylogenetics.
        In the decades following, proteins continued to provide essential clues on
        evolutionary history. While technology has continued to improve, contemporary
        proteomics has strayed from this larger biological context, rarely comparing
        species or asking how protein structure, function, and interactions have evolved.
        Here we recombine proteomics with molecular phylogenetics, highlighting the
        value of framing proteomic results in a larger biological context and how
        almost forgotten research, though technologically surpassed, can still generate
        new ideas and illuminate our work from a different perspective. Though it
        is infeasible to read all research published on a large topic, looking up
        older papers can be surprisingly rewarding when rediscovering a "gem"at the
        end of a long citation chain, aided by digital collections and perpetually
        helpful librarians. Proper literature study reduces unnecessary repetition
        and allows research to be more insightful and impactful by truly standing
        on the shoulders of giants. All data was uploaded to MassIVE (https://massive.ucsd.edu/)
        as dataset MSV000087993.
      authors:
      - name: Neely B.A.
      - name: Palmblad M.
      citationCount: 1
      date: '2021-10-01T00:00:00Z'
      journal: Journal of Proteome Research
      title: 'Rewinding the Molecular Clock: Looking at Pioneering Molecular Phylogenetics
        Experiments in the Light of Proteomics'
    note: null
    pmcid: PMC8491155
    pmid: '34523928'
    type:
    - Review
    version: '2.0'
  relation: []
  toolType:
  - Command-line tool
  - Desktop application
  topic:
  - term: Phylogeny
    uri: http://edamontology.org/topic_0084
  - term: Proteomics
    uri: http://edamontology.org/topic_0121
  - term: Metabolomics
    uri: http://edamontology.org/topic_3172
  - term: Proteomics experiment
    uri: http://edamontology.org/topic_3520
  validated: 1
  version:
  - '1.0'
  - '2.0'
- accessibility: null
  additionDate: '2024-12-23T12:44:47.964606Z'
  biotoolsCURIE: biotools:gibi230_radiomic_features_extraction
  biotoolsID: gibi230_radiomic_features_extraction
  collectionID:
  - EUCAIM
  confidence_flag: null
  cost: null
  credit: []
  description: "Implemented by GIBI230, this tool is a Docker-based software designed\
    \ for extracting radiomic features from 3D medical images in NIfTI format using\
    \ the PyRadiomics library (if DICOM images, the DICOM to NIFTI converter must\
    \ be run before using this tool). It streamlines the radiomics calculation process\
    \ by generating a structured CSV file containing all extracted variables from\
    \ medical images.\nThe dockerized software enables users to configure parameters\
    \ like filters, bin width, resampling spacing, and normalization settings can\
    \ be specified. The output radiomic variables provide quantitative information\
    \ for further analysis in medical imaging research and machine learning applications.\
    \ \nSpecially important the parameter selection of the band width. For robust\
    \ and reproducible results, a bin width of 5 is commonly recommended, but it should\
    \ be adjusted based on image resolution, modality, and noise levels."
  documentation: []
  download: []
  editPermission:
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    type: group
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  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function: []
  homepage: https://www.acim.lafe.san.gva.es/acim/?page_id=675&lang=es
  homepage_status: 0
  language:
  - Python
  lastUpdate: '2025-04-16T12:17:50.036263Z'
  license: null
  link: []
  maturity: null
  name: Radiomic features extraction
  operatingSystem: []
  otherID: []
  owner: pedromiguel_martinez_HULAFE
  publication: []
  relation: []
  toolType: []
  topic: []
  validated: 0
  version:
  - 1.0.0
- accessibility: Open access
  additionDate: '2025-04-16T08:53:57.270825Z'
  biotoolsCURIE: biotools:openvre
  biotoolsID: openvre
  collectionID:
  - EUCAIM
  confidence_flag: tool
  cost: Free of charge
  credit:
  - email: laia.codo@bsc.es
    fundrefid: 10.13039/501100006433
    gridid: grid.10097.3f
    name: Laia Codó
    note: Senior Researcher at Barcelona Supercomputing Center. Lead of Trusted Research
      Environments and Cloud Computing at INB Lab.
    orcidid: https://orcid.org/0000-0002-6797-8746
    rorid: 05sd8tv96
    typeEntity: Person
    typeRole:
    - Primary contact
    url: https://www.bsc.es/codo-laia
  - email: gelpi@ub.edu
    fundrefid: 10.13039/501100005774
    gridid: grid.5841.8
    name: Josep Lluís Gelpí
    note: Professor at University of Barcelona and Team Leader at BSC's INB Laboratory
    orcidid: http://orcid.org/0000-0002-0566-7723
    rorid: 021018s57
    typeEntity: Person
    typeRole:
    - Contributor
    url: https://webgrec.ub.edu/webpages/000011/ang/gelpi.ub.edu.html
  description: The Open Virtual Research Environment is a general purpose analysis
    platform that can be tailored for domain specific analyses.
  documentation:
  - note: Getting Started Guide
    type:
    - Quick start guide
    url: http://vre.multiscalegenomics.eu/help/starting.php
  download:
  - note: null
    type: Source code
    url: https://github.com/inab/openVRE
    version: '1.0'
  editPermission:
    authors:
    - gelpi@ub.edu
    type: group
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  elixirNode:
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  elixirPlatform:
  - Tools
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Service management
      uri: http://edamontology.org/operation_3760
    output: []
  homepage: https://github.com/inab/openVRE/wiki
  homepage_status: 0
  language:
  - PHP
  - Python
  - JavaScript
  lastUpdate: '2025-04-16T08:53:57.280528Z'
  license: Apache-2.0
  link: []
  maturity: Mature
  name: openVRE
  operatingSystem:
  - Linux
  otherID: []
  owner: gelpi@ub.edu
  publication: []
  relation:
  - biotoolsID: mugvre
    type: isNewVersionOf
  toolType:
  - Bioinformatics portal
  - Workbench
  topic:
  - term: Bioinformatics
    uri: http://edamontology.org/topic_0091
  validated: 0
  version:
  - '1.0'
- accessibility: Restricted access
  additionDate: '2025-03-17T14:01:59.601345Z'
  biotoolsCURIE: biotools:exposome_maps
  biotoolsID: exposome_maps
  collectionID:
  - EXPANSE
  - EHEN
  confidence_flag: null
  cost: Free of charge (with restrictions)
  credit:
  - email: R.C.H.Vermeulen@uu.nl
    fundrefid: null
    gridid: null
    name: Roel Vermeulen
    note: null
    orcidid: https://orcid.org/0000-0003-4082-8163
    rorid: null
    typeEntity: null
    typeRole:
    - Primary contact
    url: null
  - email: z.s.r.m.boudewijns@uu.nl
    fundrefid: null
    gridid: null
    name: Zimbo Boudewijns
    note: null
    orcidid: https://orcid.org/0000-0002-9383-9571
    rorid: null
    typeEntity: null
    typeRole:
    - Maintainer
    url: null
  - email: l.q.roga@uu.nl
    fundrefid: null
    gridid: null
    name: Lloyd Roga
    note: null
    orcidid: null
    rorid: null
    typeEntity: null
    typeRole:
    - Developer
    url: null
  description: "The Exposome Maps contain geospatially resolved data on environmental\
    \ exposures (Exposome Surfaces), categorized into the following Exposome dimensions:\n\
    Built Environment28 exposures related to:\n•\tGreen space\n•\tBlue space\n•\t\
    Grey space\nFood Environment4 exposures related to:\n•\tFood landscape / healthy\
    \ food index\nPhysico-Chemical Environment99 exposures related to:\n•\tAir pollution\n\
    •\tBiodiversity\n•\tWeather conditions\n•\tLight intensity at night\n•\tNoise\n\
    •\tPesticides\n•\tElectromagnetic fields\nSocial Environment70 exposures related\
    \ to:\n•\tNeighbourhood socio-economic position\n•\tNeighbourhood Demographic\
    \ surfaces and population characteristics\n•\tSocial capital\n•\tSecurity\n•\t\
    Mental health\n•\tProximity to facilities\n•\tEnergy use\n•\tLabour market"
  documentation:
  - note: Description of Environmental variables available through Exposome Maps
    type:
    - User manual
    url: https://surfdrive.surf.nl/files/index.php/s/uqUORDrd428H2F9
  - note: Exposome-NL data platform Data Access and Publication Policy
    type:
    - Terms of use
    url: https://surfdrive.surf.nl/files/index.php/s/fI0Gmuu5O1MJAI9
  download: []
  editPermission:
    authors:
    - hkucukali
    type: group
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function: []
  homepage: https://exposome.dataplatform.nl/
  homepage_status: 0
  language: []
  lastUpdate: '2025-04-15T08:35:02.159681Z'
  license: Other
  link:
  - note: Project information page
    type:
    - Other
    url: https://expanseproject.eu/
  maturity: Mature
  name: Exposome Maps
  operatingSystem: []
  otherID: []
  owner: Channel2291
  publication:
  - doi: 10.1126/science.aay3164
    metadata:
      abstract: Despite extensive evidence showing that exposure to specific chemicals
        can lead to disease, current research approaches and regulatory policies fail
        to address the chemical complexity of our world. To safeguard current and
        future generations from the increasing number of chemicals polluting our environment,
        a systematic and agnostic approach is needed. The “exposome” concept strives
        to capture the diversity and range of exposures to synthetic chemicals, dietary
        constituents, psychosocial stressors, and physical factors, as well as their
        corresponding biological responses. Technological advances such as high-resolution
        mass spectrometry and network science have allowed us to take the first steps
        toward a comprehensive assessment of the exposome. Given the increased recognition
        of the dominant role that nongenetic factors play in disease, an effort to
        characterize the exposome at a scale comparable to that of the human genome
        is warranted.
      authors:
      - name: Vermeulen R.
      - name: Schymanski E.L.
      - name: Barabasi A.-L.
      - name: Miller G.W.
      citationCount: 597
      date: '2020-01-24T00:00:00Z'
      journal: Science
      title: 'The exposome and health: Where chemistry meets biology'
    note: null
    pmcid: null
    pmid: null
    type: []
    version: null
  - doi: 10.1097/EE9.0000000000000162
    metadata:
      abstract: 'By 2030, more than 80% of Europe''s population will live in an urban
        environment. The urban exposome, consisting of factors such as where we live
        and work, where and what we eat, our social network, and what chemical and
        physical hazards we are exposed to, provides important targets to improve
        population health. The EXPANSE (EXposome Powered tools for healthy living
        in urbAN SEttings) project will study the impact of the urban exposome on
        the major contributors to Europe''s burden of disease: Cardio-Metabolic and
        Pulmonary Disease. EXPANSE will address one of the most pertinent questions
        for urban planners, policy makers, and European citizens: "How to maximize
        one''s health in a modern urban environment?" EXPANSE will take the next step
        in exposome research by (1) bringing together exposome and health data of
        more than 55 million adult Europeans and OMICS information for more than 2
        million Europeans; (2) perform personalized exposome assessment for 5,000
        individuals in five urban regions; (3) applying ultra-high-resolution mass-spectrometry
        to screen for chemicals in 10,000 blood samples; (4) evaluating the evolution
        of the exposome and health through the life course; and (5) evaluating the
        impact of changes in the urban exposome on the burden of cardiometabolic and
        pulmonary disease. EXPANSE will translate its insights and innovations into
        research and dissemination tools that will be openly accessible via the EXPANSE
        toolbox. By applying innovative ethics-by-design throughout the project, the
        social and ethical acceptability of these tools will be safeguarded. EXPANSE
        is part of the European Human Exposome Network.'
      authors:
      - name: Vlaanderen J.
      - name: De Hoogh K.
      - name: Hoek G.
      - name: Peters A.
      - name: Probst-Hensch N.
      - name: Scalbert A.
      - name: Melen E.
      - name: Tonne C.
      - name: De Wit G.A.
      - name: Chadeau-Hyam M.
      - name: Katsouyanni K.
      - name: Esko T.
      - name: Jongsma K.R.
      - name: Vermeulen R.
      citationCount: 38
      date: '2021-08-01T00:00:00Z'
      journal: Environmental Epidemiology
      title: 'Developing the building blocks to elucidate the impact of the urban
        exposome on cardiometabolic-pulmonary disease: The EU EXPANSE project'
    note: null
    pmcid: null
    pmid: null
    type: []
    version: null
  relation: []
  toolType: []
  topic:
  - term: FAIR data
    uri: http://edamontology.org/topic_4012
  - term: Environmental sciences
    uri: http://edamontology.org/topic_3855
  validated: 0
  version: []
- accessibility: null
  additionDate: '2024-04-18T08:31:46.459964Z'
  biotoolsCURIE: biotools:hictkpy
  biotoolsID: hictkpy
  collectionID: []
  confidence_flag: null
  cost: null
  credit: []
  description: 'Python bindings for hictk: read and write .cool and .hic files directly
    from Python'
  documentation:
  - note: null
    type:
    - General
    url: https://hictkpy.readthedocs.io/en/stable/
  - note: null
    type:
    - Installation instructions
    url: https://hictkpy.readthedocs.io/en/stable/installation.html
  - note: null
    type:
    - Quick start guide
    url: https://hictkpy.readthedocs.io/en/stable/quickstart.html
  - note: null
    type:
    - API documentation
    url: https://hictkpy.readthedocs.io/en/stable/api/index.html
  download:
  - note: null
    type: Downloads page
    url: https://github.com/paulsengroup/hictkpy/releases
    version: null
  - note: null
    type: Binaries
    url: https://pypi.org/project/hictkpy/
    version: null
  - note: null
    type: Binaries
    url: https://anaconda.org/bioconda/hictkpy
    version: null
  editPermission:
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  homepage: https://github.com/paulsengroup/hictkpy
  homepage_status: 0
  language:
  - Python
  lastUpdate: '2025-04-14T22:54:26.266145Z'
  license: MIT
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/paulsengroup/hictkpy
  - note: null
    type:
    - Issue tracker
    url: https://github.com/paulsengroup/hictkpy/issues
  - note: null
    type:
    - Helpdesk
    url: https://github.com/paulsengroup/hictkpy/discussions
  maturity: Mature
  name: hictkpy
  operatingSystem:
  - Linux
  - Mac
  - Windows
  otherID: []
  owner: robomics
  publication:
  - doi: 10.1093/bioinformatics/btae408
    metadata:
      abstract: 'Motivation: Hi-C is gaining prominence as a method for mapping genome
        organization. With declining sequencing costs and a growing demand for higher-resolution
        data, efficient tools for processing Hi-C datasets at different resolutions
        are crucial. Over the past decade, the. hic and Cooler file formats have become
        the de-facto standard to store interaction matrices produced by Hi-C experiments
        in binary format. Interoperability issues make it unnecessarily difficult
        to convert between the two formats and to develop applications that can process
        each format natively. Results: We developed hictk, a toolkit that can transparently
        operate on. hic and. cool files with excellent performance. The toolkit is
        written in C++ and consists of a C++ library with Python and R bindings as
        well as CLI tools to perform common operations directly from the shell, including
        converting between. hic and. mcool formats. We benchmark the performance of
        hictk and compare it with other popular tools and libraries. We conclude that
        hictk significantly outperforms existing tools while providing the flexibility
        of natively working with both file formats without code duplication.'
      authors:
      - name: Rossini R.
      - name: Paulsen J.
      citationCount: 0
      date: '2024-07-01T00:00:00Z'
      journal: Bioinformatics
      title: 'hictk: blazing fast toolkit to work with. hic and. cool files'
    note: null
    pmcid: null
    pmid: null
    type: []
    version: null
  relation:
  - biotoolsID: hictk
    type: uses
  toolType:
  - Library
  topic:
  - term: Bioinformatics
    uri: http://edamontology.org/topic_0091
  - term: Sequence analysis
    uri: http://edamontology.org/topic_0080
  validated: 0
  version:
  - 0.0.1
  - 0.0.2
  - 0.0.3
  - 0.0.4
  - 0.0.5
  - 1.0.0
  - 1.1.0
  - 1.2.0
- accessibility: null
  additionDate: '2024-02-02T14:42:46.030561Z'
  biotoolsCURIE: biotools:hictk
  biotoolsID: hictk
  collectionID: []
  confidence_flag: null
  cost: null
  credit: []
  description: Blazing fast toolkit to work with .hic and .cool files
  documentation:
  - note: null
    type:
    - User manual
    url: https://hictk.readthedocs.io/en/stable/index.html
  download:
  - note: null
    type: Downloads page
    url: https://github.com/paulsengroup/hictk/releases
    version: null
  - note: null
    type: Binaries
    url: https://anaconda.org/bioconda/hictk
    version: null
  - note: null
    type: Container file
    url: https://github.com/paulsengroup/hictk/pkgs/container/hictk
    version: null
  editPermission:
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  homepage: https://github.com/paulsengroup/hictk
  homepage_status: 0
  language: []
  lastUpdate: '2025-04-14T22:54:16.319235Z'
  license: MIT
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/paulsengroup/hictk
  - note: null
    type:
    - Issue tracker
    url: https://github.com/paulsengroup/hictk/issues
  - note: null
    type:
    - Helpdesk
    url: https://github.com/paulsengroup/hictk/discussions
  maturity: Mature
  name: hictk
  operatingSystem:
  - Linux
  - Mac
  - Windows
  otherID: []
  owner: robomics
  publication:
  - doi: 10.1093/bioinformatics/btae408
    metadata:
      abstract: 'Motivation: Hi-C is gaining prominence as a method for mapping genome
        organization. With declining sequencing costs and a growing demand for higher-resolution
        data, efficient tools for processing Hi-C datasets at different resolutions
        are crucial. Over the past decade, the. hic and Cooler file formats have become
        the de-facto standard to store interaction matrices produced by Hi-C experiments
        in binary format. Interoperability issues make it unnecessarily difficult
        to convert between the two formats and to develop applications that can process
        each format natively. Results: We developed hictk, a toolkit that can transparently
        operate on. hic and. cool files with excellent performance. The toolkit is
        written in C++ and consists of a C++ library with Python and R bindings as
        well as CLI tools to perform common operations directly from the shell, including
        converting between. hic and. mcool formats. We benchmark the performance of
        hictk and compare it with other popular tools and libraries. We conclude that
        hictk significantly outperforms existing tools while providing the flexibility
        of natively working with both file formats without code duplication.'
      authors:
      - name: Rossini R.
      - name: Paulsen J.
      citationCount: 0
      date: '2024-07-01T00:00:00Z'
      journal: Bioinformatics
      title: 'hictk: blazing fast toolkit to work with. hic and. cool files'
    note: null
    pmcid: null
    pmid: null
    type:
    - Primary
    version: null
  relation:
  - biotoolsID: hictkpy
    type: usedBy
  - biotoolsID: hictkr
    type: usedBy
  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:
  - 0.0.1
  - 0.0.2
  - 0.0.3
  - 0.0.4
  - 0.0.5
  - 0.0.6
  - 0.0.7
  - 0.0.8
  - 0.0.9
  - 0.0.10
  - 0.0.11
  - 0.0.12
  - 1.0.0
  - 2.0.0
  - 2.0.1
  - 2.0.2
  - 2.1.0
  - 2.1.1
- accessibility: null
  additionDate: '2021-03-19T08:44:58Z'
  biotoolsCURIE: biotools:pr2
  biotoolsID: pr2
  collectionID: []
  confidence_flag: tool
  cost: null
  credit:
  - email: vaulot@gmail.com
    fundrefid: null
    gridid: null
    name: Daniel Vaulot
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  description: 'an 18S rRNA primer database for protists.


    An interactive database of eukaryotic rRNA primers and primer sets for metabarcoding
    studies compiled from the literature.


    A database of eukaryotic rRNA primers and primer sets for metabarcoding studies
    compiled from the literature.'
  documentation: []
  download:
  - note: null
    type: Container file
    url: https://hub.docker.com/repository/docker/vaulot/pr2-primers
    version: null
  editPermission:
    authors: []
    type: private
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: PCR primer design
      uri: http://edamontology.org/operation_0308
    - term: Deposition
      uri: http://edamontology.org/operation_3431
    - term: Primer removal
      uri: http://edamontology.org/operation_3237
    output: []
  homepage: https://app.pr2-primers.org
  homepage_status: 0
  language:
  - R
  lastUpdate: '2025-04-14T13:56:12.948169Z'
  license: null
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/pr2database/pr2-primers
  maturity: null
  name: PR2
  operatingSystem: []
  otherID: []
  owner: vaulot
  publication:
  - doi: 10.1101/2021.01.04.425170
    metadata: null
    note: null
    pmcid: null
    pmid: null
    type: []
    version: null
  relation: []
  toolType:
  - Database portal
  - Web application
  topic:
  - term: Probes and primers
    uri: http://edamontology.org/topic_0632
  - term: Sequencing
    uri: http://edamontology.org/topic_3168
  - term: Functional, regulatory and non-coding RNA
    uri: http://edamontology.org/topic_0659
  - term: Model organisms
    uri: http://edamontology.org/topic_0621
  - term: Literature and language
    uri: http://edamontology.org/topic_3068
  validated: 0
  version: []
- accessibility: Open access
  additionDate: '2019-08-26T14:34:55Z'
  biotoolsCURIE: biotools:MINERVA_Platform
  biotoolsID: MINERVA_Platform
  collectionID:
  - ELIXIR-LU
  - LCSB
  confidence_flag: null
  cost: Free of charge
  credit: []
  description: 'The MINERVA (Molecular Interaction NEtwoRk VisuAlization) platform
    is a standalone webserver for visualization, exploration and management of molecular
    networks encoded in SBGN-compliant format, including files produced using CellDesigner
    or SBGN editors. Visualization of uploaded networks generated by the platform
    is accessible via a web browser to all viewers with the weblink to the resource.


    The MINERVA Platform is a webservice using the Java Server Faces 2 technology.
    The server side, including data parsing, integration, annotation and verification,
    is implemented in Java. The platform uses the Postgres SQL database for data storage
    and the Hibernate framework as a middle layer between web server and database.
    The user web-interface is generated using React.js. The displayed content is visualized
    by OpenLayers API, dedicated JavaScript and CSS.'
  documentation:
  - note: null
    type:
    - Quick start guide
    - Release notes
    - User manual
    - API documentation
    - Citation instructions
    - Terms of use
    url: https://minerva.uni.lu
  download:
  - note: Installation instructions, including debian package, virtual machine images
      and docker containers.
    type: Other
    url: https://minerva.pages.uni.lu/doc/install/
    version: 13.1.3 - 18.1.1
  editPermission:
    authors:
    - sascha.herzinger
    type: group
  elixirCommunity: []
  elixirNode:
  - Luxembourg
  elixirPlatform:
  - Tools
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Pathway visualisation
      uri: http://edamontology.org/operation_3926
    output: []
  - cmd: null
    input: []
    note: null
    operation:
    - term: Expression data visualisation
      uri: http://edamontology.org/operation_0571
    output: []
  homepage: https://minerva.uni.lu
  homepage_status: 0
  language: []
  lastUpdate: '2025-04-14T09:01:54.711218Z'
  license: AGPL-3.0
  link:
  - note: GiLab repository for core functionalities (data and format handling, service
      stability, API access)
    type:
    - Repository
    url: https://gitlab.lcsb.uni.lu/minerva/core/
  - note: Issue tracker for core functionalities (data and format handling, service
      stability, API access)
    type:
    - Issue tracker
    url: https://gitlab.lcsb.uni.lu/minerva/core/-/issues
  - note: GiLab repository for frontend functionalities
    type:
    - Repository
    url: https://gitlab.lcsb.uni.lu/minerva/frontend
  - note: Issue tracker for frontend functionalities
    type:
    - Issue tracker
    url: https://gitlab.lcsb.uni.lu/minerva/frontend/-/issues
  maturity: Mature
  name: The MINERVA Platform
  operatingSystem: []
  otherID: []
  owner: mjostaszewski
  publication:
  - doi: 10.1038/npjsba.2016.20
    metadata:
      abstract: Our growing knowledge about various molecular mechanisms is becoming
        increasingly more structured and accessible. Different repositories of molecular
        interactions and available literature enable construction of focused and high-quality
        molecular interaction networks. Novel tools for curation and exploration of
        such networks are needed, in order to foster the development of a systems
        biology environment. In particular, solutions for visualization, annotation
        and data cross-linking will facilitate usage of network-encoded knowledge
        in biomedical research. To this end we developed the MINERVA (Molecular Interaction
        NEtwoRks VisuAlization) platform, a standalone webservice supporting curation,
        annotation and visualization of molecular interaction networks in Systems
        Biology Graphical Notation (SBGN)-compliant format. MINERVA provides automated
        content annotation and verification for improved quality control. The end
        users can explore and interact with hosted networks, and provide direct feedback
        to content curators. MINERVA enables mapping drug targets or overlaying experimental
        data on the visualized networks. Extensive export functions enable downloading
        areas of the visualized networks as SBGN-compliant models for efficient reuse
        of hosted networks. The software is available under Affero GPL 3.0 as a Virtual
        Machine snapshot, Debian package and Docker instance at http://r3lab.uni.lu/web/minerva-website/.
        We believe that MINERVA is an important contribution to systems biology community,
        as its architecture enables set-up of locally or globally accessible SBGN-oriented
        repositories of molecular interaction networks. Its functionalities allow
        overlay of multiple information layers, facilitating exploration of content
        and interpretation of data. Moreover, annotation and verification workflows
        of MINERVA improve the efficiency of curation of networks, allowing life-science
        researchers to better engage in development and use of biomedical knowledge
        repositories.
      authors:
      - name: Gawron P.
      - name: Ostaszewski M.
      - name: Satagopam V.
      - name: Gebel S.
      - name: Mazein A.
      - name: Kuzma M.
      - name: Zorzan S.
      - name: McGee F.
      - name: Otjacques B.
      - name: Balling R.
      - name: Schneider R.
      citationCount: 60
      date: '2016-01-01T00:00:00Z'
      journal: npj Systems Biology and Applications
      title: MINERVA—A platform for visualization and curation of molecular interaction
        networks
    note: null
    pmcid: PMC5516855
    pmid: '28725475'
    type:
    - Primary
    version: '10.0'
  - doi: 10.1093/bioinformatics/btz286
    metadata:
      abstract: 'Summary: The complexity of molecular networks makes them difficult
        to navigate and interpret, creating a need for specialized software. MINERVA
        is a web platform for visualization, exploration and management of molecular
        networks. Here, we introduce an extension to MINERVA architecture that greatly
        facilitates the access and use of the stored molecular network data. It allows
        to incorporate such data in analytical pipelines via a programmatic access
        interface, and to extend the platform''s visual exploration and analytics
        functionality via plugin architecture. This is possible for any molecular
        network hosted by the MINERVA platform encoded in well-recognized systems
        biology formats. To showcase the possibilities of the plugin architecture,
        we have developed several plugins extending the MINERVA core functionalities.
        In the article, we demonstrate the plugins for interactive tree traversal
        of molecular networks, for enrichment analysis and for mapping and visualization
        of known disease variants or known adverse drug reactions to molecules in
        the network. Availability and implementation: Plugins developed and maintained
        by the MINERVA team are available under the AGPL v3 license at https://git-r3lab.uni.lu/minerva/plugins/.
        The MINERVA API and plugin documentation is available at https://minerva-web.lcsb.uni.lu.'
      authors:
      - name: Hoksza D.
      - name: Gawron P.
      - name: Ostaszewski M.
      - name: Smula E.
      - name: Schneider R.
      citationCount: 24
      date: '2019-11-01T00:00:00Z'
      journal: Bioinformatics
      title: 'MINERVA API and plugins: Opening molecular network analysis and visualization
        to the community'
    note: null
    pmcid: PMC6821317
    pmid: '31074494'
    type:
    - Primary
    version: 12.2.3
  - doi: 10.1093/bib/bbz067
    metadata:
      abstract: The understanding of complex biological networks often relies on both
        a dedicated layout and a topology. Currently, there are three major competing
        layout-aware systems biology formats, but there are no software tools or software
        libraries supporting all of them. This complicates the management of molecular
        network layouts and hinders their reuse and extension. In this paper, we present
        a high-level overview of the layout formats in systems biology, focusing on
        their commonalities and differences, review their support in existing software
        tools, libraries and repositories and finally introduce a new conversion module
        within the MINERVA platform. The module is available via a REST API and offers,
        besides the ability to convert between layout-aware systems biology formats,
        the possibility to export layouts into several graphical formats. The module
        enables conversion of very large networks with thousands of elements, such
        as disease maps or metabolic reconstructions, rendering it widely applicable
        in systems biology.
      authors:
      - name: Hoksza D.
      - name: Gawron P.
      - name: Ostaszewski M.
      - name: Hasenauer J.
      - name: Schneider R.
      citationCount: 15
      date: '2019-07-10T00:00:00Z'
      journal: Briefings in Bioinformatics
      title: Closing the gap between formats for storing layout information in systems
        biology
    note: null
    pmcid: PMC7373180
    pmid: '31273380'
    type:
    - Primary
    version: 13.1.1
  - doi: 10.1089/big.2015.0057
    metadata:
      abstract: Translational medicine is a domain turning results of basic life science
        research into new tools and methods in a clinical environment, for example,
        as new diagnostics or therapies. Nowadays, the process of translation is supported
        by large amounts of heterogeneous data ranging from medical data to a whole
        range of -omics data. It is not only a great opportunity but also a great
        challenge, as translational medicine big data is difficult to integrate and
        analyze, and requires the involvement of biomedical experts for the data processing.
        We show here that visualization and interoperable workflows, combining multiple
        complex steps, can address at least parts of the challenge. In this article,
        we present an integrated workflow for exploring, analysis, and interpretation
        of translational medicine data in the context of human health. Three Web services
        - tranSMART, a Galaxy Server, and a MINERVA platform - are combined into one
        big data pipeline. Native visualization capabilities enable the biomedical
        experts to get a comprehensive overview and control over separate steps of
        the workflow. The capabilities of tranSMART enable a flexible filtering of
        multidimensional integrated data sets to create subsets suitable for downstream
        processing. A Galaxy Server offers visually aided construction of analytical
        pipelines, with the use of existing or custom components. A MINERVA platform
        supports the exploration of health and disease-related mechanisms in a contextualized
        analytical visualization system. We demonstrate the utility of our workflow
        by illustrating its subsequent steps using an existing data set, for which
        we propose a filtering scheme, an analytical pipeline, and a corresponding
        visualization of analytical results. The workflow is available as a sandbox
        environment, where readers can work with the described setup themselves. Overall,
        our work shows how visualization and interfacing of big data processing services
        facilitate exploration, analysis, and interpretation of translational medicine
        data.
      authors:
      - name: Satagopam V.
      - name: Gu W.
      - name: Eifes S.
      - name: Gawron P.
      - name: Ostaszewski M.
      - name: Gebel S.
      - name: Barbosa-Silva A.
      - name: Balling R.
      - name: Schneider R.
      citationCount: 38
      date: '2016-06-01T00:00:00Z'
      journal: Big Data
      title: Integration and Visualization of Translational Medicine Data for Better
        Understanding of Human Diseases
    note: null
    pmcid: PMC4932659
    pmid: '27441714'
    type:
    - Usage
    version: '10.0'
  - doi: 10.1016/j.envpol.2019.04.005
    metadata:
      abstract: 'Polychlorinated biphenyls (PCBs) are a class of widespread environmental
        pollutants, commonly found in human blood, that have been suggested to be
        linked to the occurrence of sporadic Parkinson''s disease (PD). It has been
        reported that some non-coplanar PCBs accumulate in the brains of female PD
        patients. To improve our understanding of the association between PCB exposure
        and PD risk we have applied whole transcriptome gene expression analysis in
        blood cells from 594 PCB-exposed subjects (369 female, 225 male). Interestingly,
        we observe that in females, blood levels of non-coplanar PCBs appear to be
        associated with expression levels of PD-specific genes. However, no such association
        was detected in males. Among the 131 PD-specific genes affected, 39 have been
        shown to display similar changes in expression levels in the substantia nigra
        of deceased PD patients. Especially among the down-regulated genes, transcripts
        of genes involved in neurotransmitter vesicle-related functions were predominant.
        Capsule: Plasma PCB levels are associated with gene expression changes in
        females only, resulting in brain-related genes changing in blood cells of
        healthy individuals exposed to PCBs.'
      authors:
      - name: Bohler S.
      - name: Krauskopf J.
      - name: Espin-Perez A.
      - name: Gebel S.
      - name: Palli D.
      - name: Rantakokko P.
      - name: Kiviranta H.
      - name: Kyrtopoulos S.A.
      - name: Balling R.
      - name: Kleinjans J.
      citationCount: 5
      date: '2019-07-01T00:00:00Z'
      journal: Environmental Pollution
      title: Genes associated with Parkinson's disease respond to increasing polychlorinated
        biphenyl levels in the blood of healthy females
    note: null
    pmcid: null
    pmid: '30991279'
    type: []
    version: 13.1.1
  relation:
  - biotoolsID: pathvisio
    type: uses
  - biotoolsID: sbgn
    type: uses
  - biotoolsID: libsbml
    type: uses
  toolType: []
  topic:
  - term: Molecular interactions, pathways and networks
    uri: http://edamontology.org/topic_0602
  - term: Omics
    uri: http://edamontology.org/topic_3391
  - term: Translational medicine
    uri: http://edamontology.org/topic_3342
  validated: 0
  version:
  - 13.1.3
  - 13.2.0
  - 14.0.13
  - 15.0.3
  - 16.4.0
  - 17.1.3
  - 18.1.1
- accessibility: Open access
  additionDate: '2025-04-11T20:52:47.895200Z'
  biotoolsCURIE: biotools:opencloning
  biotoolsID: opencloning
  collectionID: []
  confidence_flag: tool
  cost: Free of charge
  credit:
  - email: manulera14@gmail.com
    fundrefid: null
    gridid: null
    name: Manuel Lera-Ramirez
    note: null
    orcidid: https://orcid.org/0000-0002-8666-9746
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: https://github.com/manulera
  description: An Open-Source web application to plan and document cloning and genome
    engineering
  documentation:
  - note: null
    type:
    - General
    url: https://github.com/manulera/OpenCloning
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    note: null
    operation:
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  - cmd: null
    input: []
    note: null
    operation:
    - term: Pairwise sequence alignment
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    output: []
  - cmd: null
    input: []
    note: null
    operation:
    - term: Nucleic acid design
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    output: []
  - cmd: null
    input: []
    note: null
    operation:
    - term: Restriction digest
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  - cmd: null
    input: []
    note: null
    operation:
    - term: Sequence generation
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    output: []
  - cmd: null
    input: []
    note: null
    operation:
    - term: Sequence assembly validation
      uri: http://edamontology.org/operation_3180
    output: []
  - cmd: null
    input: []
    note: null
    operation:
    - term: Chromatogram visualisation
      uri: http://edamontology.org/operation_3203
    output: []
  - cmd: null
    input: []
    note: null
    operation:
    - term: Map drawing
      uri: http://edamontology.org/operation_0573
    output: []
  - cmd: null
    input: []
    note: null
    operation:
    - term: Network visualisation
      uri: http://edamontology.org/operation_3925
    output: []
  - cmd: null
    input: []
    note: null
    operation:
    - term: Sequence visualisation
      uri: http://edamontology.org/operation_0564
    output: []
  homepage: https://opencloning.org/
  homepage_status: 0
  language:
  - Python
  - JavaScript
  lastUpdate: '2025-04-11T20:53:03.390161Z'
  license: MIT
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/manulera/OpenCloning
  - note: Hosted web app
    type:
    - Service
    url: https://opencloning.org/
  - note: Backend code
    type:
    - Repository
    url: https://github.com/manulera/OpenCloning_backend
  - note: null
    type:
    - Repository
    url: https://github.com/manulera/OpenCloning_frontend
  maturity: Emerging
  name: OpenCloning
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  owner: manulera
  publication: []
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    type: uses
  - biotoolsID: biopython
    type: uses
  - biotoolsID: primer3
    type: uses
  toolType:
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  - Web API
  - Library
  topic:
  - term: Genetic engineering
    uri: http://edamontology.org/topic_3912
  - term: Molecular biology
    uri: http://edamontology.org/topic_3047
  - term: Synthetic biology
    uri: http://edamontology.org/topic_3895
  validated: 0
  version: []
- accessibility: null
  additionDate: '2025-04-11T14:04:51.838757Z'
  biotoolsCURIE: biotools:metapr2
  biotoolsID: metapr2
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  confidence_flag: null
  cost: null
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  description: The metaPR2 database contains processed 18S rRNA metabarcodes that
    are annotated with the PR2 reference sequence database. Version 2.0 of the database
    contains 41 datasets corresponding to more than 6,000 samples and 90,000 ASVs.
    The database is accessible through both a web-based interface (https://app.metapr2.org)
    and an R package.
  documentation: []
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- accessibility: Open access
  additionDate: '2025-04-11T13:56:02.037873Z'
  biotoolsCURIE: biotools:pr2-reference
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  collectionID: []
  confidence_flag: null
  cost: Free of charge
  credit: []
  description: The PR2 reference sequence database was initiated in 2010 in the frame
    of the BioMarks project from work that had developed in the previous ten years
    in the Plankton Group of the Station Biologique of Roscoff. It aims to provide
    a reference database of carefully annotated 18S rRNA sequences using nine unique
    taxonomic fields (from domain to species). At present, it contains over 240,000
    sequences. Although it focuses on protists, it also contains sequences from metazoa,
    fungi and plants as well a limited set of 16S sequences from plastids and bacteria.
    Several metadata fields are available for many sequences, including geo-localisation,
    whether it originates from a culture or a natural sample, host type etc… The annotation
    of PR2 is performed by experts from each taxonomic groups.
  documentation:
  - note: null
    type:
    - User manual
    url: https://pr2database.github.io/pr2database/articles/pr2database.html
  download:
  - note: null
    type: Downloads page
    url: https://github.com/pr2database/pr2database/releases
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  homepage: https://app.pr2-database.org/
  homepage_status: 0
  language:
  - R
  lastUpdate: '2025-04-11T14:01:09.249274Z'
  license: null
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/pr2database/pr2database/releases
  - note: null
    type:
    - Issue tracker
    url: https://github.com/pr2database/pr2database/issues
  - note: null
    type:
    - Other
    url: https://pr2-database.org/
  maturity: Mature
  name: Protists Ribosomal Reference Database
  operatingSystem: []
  otherID: []
  owner: vaulot
  publication:
  - doi: 10.1093/nar/gks1160
    metadata:
      abstract: The interrogation of genetic markers in environmental meta-barcoding
        studies is currently seriously hindered by the lack of taxonomically curated
        reference data sets for the targeted genes. The Protist Ribosomal Reference
        database (PR2, http://ssu-rrna.org/) provides a unique access to eukaryotic
        small sub-unit (SSU) ribosomal RNA and DNA sequences, with curated taxonomy.
        The database mainly consists of nuclear-encoded protistan sequences. However,
        metazoans, land plants, macrosporic fungi and eukaryotic organelles (mitochondrion,
        plastid and others) are also included because they are useful for the analysis
        of high-troughput sequencing data sets. Introns and putative chimeric sequences
        have been also carefully checked. Taxonomic assignation of sequences consists
        of eight unique taxonomic fields. In total, 136866 sequences are nuclear encoded,
        45708 (36 501 mitochondrial and 9657 chloroplastic) are from organelles, the
        remaining being putative chimeric sequences. The website allows the users
        to download sequences from the entire and partial databases (including representative
        sequences after clustering at a given level of similarity). Different web
        tools also allow searches by sequence similarity. The presence of both rRNA
        and rDNA sequences, taking into account introns (crucial for eukaryotic sequences),
        a normalized eight terms ranked-taxonomy and updates of new GenBank releases
        were made possible by a long-term collaboration between experts in taxonomy
        and computer scientists. © The Author(s) 2012.
      authors:
      - name: Guillou L.
      - name: Bachar D.
      - name: Audic S.
      - name: Bass D.
      - name: Berney C.
      - name: Bittner L.
      - name: Boutte C.
      - name: Burgaud G.
      - name: De Vargas C.
      - name: Decelle J.
      - name: Del Campo J.
      - name: Dolan J.R.
      - name: Dunthorn M.
      - name: Edvardsen B.
      - name: Holzmann M.
      - name: Kooistra W.H.C.F.
      - name: Lara E.
      - name: Le Bescot N.
      - name: Logares R.
      - name: Mahe F.
      - name: Massana R.
      - name: Montresor M.
      - name: Morard R.
      - name: Not F.
      - name: Pawlowski J.
      - name: Probert I.
      - name: Sauvadet A.-L.
      - name: Siano R.
      - name: Stoeck T.
      - name: Vaulot D.
      - name: Zimmermann P.
      - name: Christen R.
      citationCount: 1456
      date: '2013-01-01T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'The Protist Ribosomal Reference database (PR2): A catalog of unicellular
        eukaryote Small Sub-Unit rRNA sequences with curated taxonomy'
    note: null
    pmcid: null
    pmid: null
    type:
    - Primary
    version: null
  relation: []
  toolType:
  - Database portal
  - Web application
  topic:
  - term: Metabarcoding
    uri: http://edamontology.org/topic_4038
  validated: 0
  version:
  - 5.1.0
- accessibility: Open access
  additionDate: '2022-11-03T14:53:22.145643Z'
  biotoolsCURIE: biotools:rdmkit
  biotoolsID: rdmkit
  collectionID: []
  confidence_flag: tool
  cost: Free of charge
  credit: []
  description: RDMkit is the Research Data Management toolkit for Life Sciences, providing
    best practices and guidelines to for FAIR (Findable, Accessible, Interoperable
    and Reusable) data management.
  documentation: []
  download:
  - note: null
    type: Downloads page
    url: https://zenodo.org/record/5110061
    version: null
  editPermission:
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    type: private
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  elixirNode:
  - UK
  - Norway
  - Belgium
  - Germany
  - Finland
  - Spain
  elixirPlatform:
  - Data
  - Interoperability
  - Training
  elixir_badge: 0
  function: []
  homepage: https://rdmkit.elixir-europe.org
  homepage_status: 0
  language:
  - Python
  lastUpdate: '2025-04-11T13:03:16.201584Z'
  license: MIT
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/elixir-europe/rdmkit
  maturity: null
  name: RDMkit
  operatingSystem:
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  - Linux
  - Windows
  otherID: []
  owner: munazah
  publication: []
  relation: []
  toolType:
  - Web application
  topic: []
  validated: 0
  version: []
- accessibility: null
  additionDate: '2025-04-11T12:25:53.238464Z'
  biotoolsCURIE: biotools:avida
  biotoolsID: avida
  collectionID: []
  confidence_flag: null
  cost: null
  credit: []
  description: Avida is a software platform that mirrors key aspects of biological
    evolution, making it a useful twin for evolutionary studies.
  documentation: []
  download: []
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  homepage: https://github.com/devosoft/avida
  homepage_status: 0
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  lastUpdate: '2025-04-11T12:25:53.241076Z'
  license: null
  link: []
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  name: avida
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  owner: Miguel
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  validated: 0
  version: []
- accessibility: Open access
  additionDate: '2020-09-03T19:08:44Z'
  biotoolsCURIE: biotools:plaza_4.0
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  - VIB
  - UGent
  confidence_flag: tool
  cost: Free of charge
  credit:
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    fundrefid: null
    gridid: null
    name: Klaas Vandepoele
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
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    url: null
  description: 'Integrative resource for functional, evolutionary and comparative
    plant genomics.


    PLAZA is an access point for plant comparative genomics, centralizing genomic
    data produced by different genome sequencing initiatives.


    This intermediate update of the PLAZA platform, with a focus on the Monocots,
    became necessary due to substantial annotation updates to species present in the
    4.0 PLAZA instances.'
  documentation:
  - note: null
    type:
    - User manual
    url: https://bioinformatics.psb.ugent.be/plaza/documentation
  download: []
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  elixir_badge: 0
  function:
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    input: []
    note: null
    operation:
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      uri: http://edamontology.org/operation_0553
    - term: Phylogenetic tree annotation
      uri: http://edamontology.org/operation_0558
    - term: Phylogenetic tree visualisation
      uri: http://edamontology.org/operation_0567
    output: []
  homepage: https://bioinformatics.psb.ugent.be/plaza
  homepage_status: 0
  language: []
  lastUpdate: '2025-04-11T09:29:36.505334Z'
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  link: []
  maturity: null
  name: PLAZA 4.0
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  - Linux
  - Windows
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  publication:
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    metadata:
      abstract: PLAZA (https://bioinformatics.psb.ugent.be/plaza) is a plant-oriented
        online resource for comparative, evolutionary and functional genomics. The
        PLAZA platform consists of multiple independent instances focusing on different
        plant clades, while also providing access to a consistent set of reference
        species. Each PLAZA instance contains structural and functional gene annotations,
        gene family data and phylogenetic trees and detailed gene colinearity information.
        A user-friendly web interface makes the necessary tools and visualizations
        accessible, specific for each data type. Here we present PLAZA 4.0, the latest
        iteration of the PLAZA framework. This version consists of two new instances
        (Dicots 4.0 and Monocots 4.0) providing a large increase in newly available
        species, and offers access to updated and newly implemented tools and visualizations,
        helping users with the ever-increasing demands for complex and in-depth analyzes.
        The total number of species across both instances nearly doubles from 37 species
        in PLAZA 3.0 to 71 species in PLAZA 4.0, with a much broader coverage of crop
        species (e.g. wheat, palm oil) and species of evolutionary interest (e.g.
        spruce, Marchantia). The new PLAZA instances can also be accessed by a programming
        interface through a RESTful web service, thus allowing bioinformaticians to
        optimally leverage the power of the PLAZA platform.
      authors:
      - name: Van Bel M.
      - name: Diels T.
      - name: Vancaester E.
      - name: Kreft L.
      - name: Botzki A.
      - name: Van De Peer Y.
      - name: Coppens F.
      - name: Vandepoele K.
      citationCount: 338
      date: '2018-01-01T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'PLAZA 4.0: An integrative resource for functional, evolutionary and
        comparative plant genomics'
    note: null
    pmcid: PMC5753339
    pmid: '29069403'
    type: []
    version: null
  relation: []
  toolType: []
  topic:
  - term: Plant biology
    uri: http://edamontology.org/topic_0780
  - term: Phylogenetics
    uri: http://edamontology.org/topic_3293
  - term: Functional genomics
    uri: http://edamontology.org/topic_0085
  - term: Model organisms
    uri: http://edamontology.org/topic_0621
  - term: Microbial ecology
    uri: http://edamontology.org/topic_3697
  validated: 0
  version: []
- accessibility: null
  additionDate: '2025-04-10T03:18:36.031624Z'
  biotoolsCURIE: biotools:cellbindb
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  confidence_flag: null
  cost: null
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  description: We have released a large-scale, multimodal annotated dataset for cell
    segmentation, CellBinDB. Based on CellBinDB, we designed a benchmarking pipeline
    to benchmark eight of the most advanced and widely used cell segmentation techniques/methods,
    and further analyzed the impact of four cell morphology indicators and image gradients
    on the segmentation results.
  documentation: []
  download: []
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  homepage_status: 0
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  lastUpdate: '2025-04-10T03:18:59.657512Z'
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  link: []
  maturity: null
  name: CellBinDB
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  owner: shican
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  validated: 0
  version: []
- accessibility: Open access (with restrictions)
  additionDate: '2025-04-09T13:19:17.715967Z'
  biotoolsCURIE: biotools:clowm
  biotoolsID: clowm
  collectionID: []
  confidence_flag: tool
  cost: Free of charge
  credit:
  - email: dgoebel@techfak.uni-bielefeld.de
    fundrefid: null
    gridid: null
    name: Daniel Göbel
    note: null
    orcidid: https://orcid.org/0009-0009-9985-3823
    rorid: null
    typeEntity: Person
    typeRole:
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    - Developer
    - Primary contact
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  - email: mbeckste@cebitec.uni-bielefeld.de
    fundrefid: null
    gridid: null
    name: Michael Beckstette
    note: null
    orcidid: https://orcid.org/0000-0002-3707-1692
    rorid: null
    typeEntity: Person
    typeRole:
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    - Documentor
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Bielefeld University
    note: null
    orcidid: null
    rorid: 02hpadn98
    typeEntity: Institute
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  - email: null
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    name: Genome Informatics
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
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    url: https://gi.cebitec.uni-bielefeld.de
  - email: null
    fundrefid: null
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    name: NFDI4Microbiota
    note: null
    orcidid: null
    rorid: null
    typeEntity: Consortium
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    url: https://nfdi4microbiota.de
  description: Data analysis in the life sciences often suffers from reproducibility,
    standardization and accessibility issues and these problems become even more severe
    with the escalating volume and complexity of data. While best-practice data analysis
    workflows try to tackle these challenges, many existing workflows still grapple
    with scalability issues, limited portability due to tight coupling with the execution
    environment and accessibility constraints arising from the absence of user-friendly
    interfaces. To overcome these issues, we created CloWM, a comprehensive cloud-based
    workflow management platform that allows the generic transformation of command-line
    driven workflows into user-friendly web-based services. CloWM offers the seamless
    integration of (1) scientific workflows written in the Nextflow DSL, (2) robust
    data storage, (3) a highly scalable compute layer for data-intensive analysis
    tasks and (4) a user-friendly interface.
  documentation:
  - note: null
    type:
    - API documentation
    url: https://clowm.bi.denbi.de/api/v1/docs
  - note: null
    type:
    - Terms of use
    url: https://clowm.bi.denbi.de/terms
  download:
  - note: null
    type: API specification
    url: https://clowm.bi.denbi.de/api/v1/openapi.json
    version: null
  - note: null
    type: Source code
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    version: null
  editPermission:
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    type: private
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  elixirNode:
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  elixirPlatform: []
  elixir_badge: 0
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  homepage: https://clowm.bi.denbi.de
  homepage_status: 0
  language:
  - Python
  - JavaScript
  lastUpdate: '2025-04-09T14:21:50.981521Z'
  license: Apache-2.0
  link:
  - note: null
    type:
    - Repository
    url: https://gitlab.ub.uni-bielefeld.de/cmg/clowm
  maturity: Mature
  name: Cloud-based Workflow Manager (CloWM)
  operatingSystem: []
  otherID: []
  owner: dgoebel
  publication:
  - doi: 10.5281/zenodo.14039069
    metadata: null
    note: null
    pmcid: null
    pmid: null
    type:
    - Other
    version: null
  relation:
  - biotoolsID: sans
    type: includes
  toolType:
  - Web API
  - Web service
  - Bioinformatics portal
  topic:
  - term: Bioinformatics
    uri: http://edamontology.org/topic_0091
  validated: 0
  version: []
next: ?page=2
previous: null
