count: 991
list:
- accessibility: Open access
  additionDate: '2019-11-14T18:08:10Z'
  biotoolsCURIE: biotools:purge_dups
  biotoolsID: purge_dups
  collectionID:
  - ONTeater
  confidence_flag: tool
  cost: Free of charge
  credit:
  - email: null
    fundrefid: null
    gridid: null
    name: Dengfeng Guan
    note: null
    orcidid: https://orcid.org/0000-0002-6376-3940
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: https://www.chatlink.com.cn
  description: 'Identifying and removing haplotypic duplication in primary genome
    assemblies | haplotypic duplication identification tool | scripts/pd_config.py:
    script to generate a configuration file used by run_purge_dups.py | purge haplotigs
    and overlaps in an assembly based on read depth | Given a primary assembly pri_asm
    and an alternative assembly hap_asm (optional, if you have one), follow the steps
    shown below to build your own purge_dups pipeline, steps with same number can
    be run simultaneously. Among all the steps, although step 4 is optional, we highly
    recommend our users to do so, because assemblers may produce overrepresented seqeuences.
    In such a case, The final step 4 can be applied to remove those seqeuences'
  documentation: []
  download: []
  editPermission:
    authors: []
    type: public
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Sequence set (nucleic acid)
        uri: http://edamontology.org/data_1234
      format:
      - term: FASTQ
        uri: http://edamontology.org/format_1930
    - data:
        term: Sequence set (nucleic acid)
        uri: http://edamontology.org/data_1234
      format:
      - term: FASTA
        uri: http://edamontology.org/format_1929
    note: null
    operation:
    - term: Genome assembly
      uri: http://edamontology.org/operation_0525
    - term: Read binning
      uri: http://edamontology.org/operation_3798
    - term: Scaffolding
      uri: http://edamontology.org/operation_3216
    output:
    - data:
        term: Sequence set (nucleic acid)
        uri: http://edamontology.org/data_1234
      format:
      - term: FASTA
        uri: http://edamontology.org/format_1929
  homepage: https://github.com/dfguan/purge_dups
  homepage_status: 0
  language:
  - Python
  - C
  lastUpdate: '2025-06-30T15:34:51.626796Z'
  license: MIT
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/dfguan/purge_dups
  - note: null
    type:
    - Issue tracker
    url: https://github.com/dfguan/purge_dups/issues
  maturity: null
  name: purge_dups
  operatingSystem:
  - Mac
  - Linux
  otherID: []
  owner: Pub2Tools
  publication:
  - doi: 10.1101/729962
    metadata: null
    note: null
    pmcid: null
    pmid: null
    type: []
    version: null
  relation: []
  toolType: []
  topic:
  - term: Sequence assembly
    uri: http://edamontology.org/topic_0196
  validated: 1
  version:
  - v.1.2.6
- accessibility: Open access
  additionDate: '2024-03-18T14:51:49.667412Z'
  biotoolsCURIE: biotools:compleasm
  biotoolsID: compleasm
  collectionID:
  - ONTeater
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: neng@ds.dfci.harvard.edu
    fundrefid: null
    gridid: null
    name: Neng Huang
    note: null
    orcidid: https://orcid.org/0000-0001-7187-0749
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: null
  description: 'Compleasm: a faster and more accurate reimplementation of BUSCO.

    It provides measures for quantitative assessment of genome assembly, gene set,
    and transcriptome completeness based on evolutionarily informed expectations of
    gene content from near-universal single-copy orthologs.'
  documentation:
  - note: null
    type:
    - General
    url: https://github.com/huangnengCSU/compleasm/blob/0.2.6/README.md
  download: []
  editPermission:
    authors: []
    type: public
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: compleasm run -l "$lineage" -a assembly.fa -o output_prefix
    input:
    - data:
        term: Sequence set (nucleic acid)
        uri: http://edamontology.org/data_1234
      format:
      - term: FASTA-like
        uri: http://edamontology.org/format_2546
    note: Runs compleasm using the BUSCO set corresponding to the lineage given.
    operation:
    - term: Sequence assembly validation
      uri: http://edamontology.org/operation_3180
    output:
    - data:
        term: Sequence report
        uri: http://edamontology.org/data_2955
      format: []
  homepage: https://github.com/huangnengCSU/compleasm
  homepage_status: 0
  language:
  - Python
  lastUpdate: '2025-06-30T15:30:41.266812Z'
  license: Apache-2.0
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/huangnengCSU/compleasm
  - note: null
    type:
    - Issue tracker
    url: https://github.com/huangnengCSU/compleasm/issues
  - note: List of accepted lineages (taxonomic groups with curated BUSCO sets)
    type:
    - Other
    url: https://busco.ezlab.org/list_of_lineages.html
  maturity: Mature
  name: Compleasm
  operatingSystem: []
  otherID: []
  owner: rlibouban
  publication:
  - doi: 10.1093/bioinformatics/btad595
    metadata:
      abstract: 'Motivation: Evaluating the gene completeness is critical to measuring
        the quality of a genome assembly. An incomplete assembly can lead to errors
        in gene predictions, annotation, and other downstream analyses. Benchmarking
        Universal Single-Copy Orthologs (BUSCO) is a widely used tool for assessing
        the completeness of genome assembly by testing the presence of a set of single-copy
        orthologs conserved across a wide range of taxa. However, BUSCO is slow particularly
        for large genome assemblies. It is cumbersome to apply BUSCO to a large number
        of assemblies. Results: Here, we present compleasm, an efficient tool for
        assessing the completeness of genome assemblies. Compleasm utilizes the miniprot
        protein-to-genome aligner and the conserved orthologous genes from BUSCO.
        It is 14 times faster than BUSCO for human assemblies and reports a more accurate
        completeness of 99.6% than BUSCO''s 95.7%, which is in close agreement with
        the annotation completeness of 99.5% for T2T-CHM13.'
      authors:
      - name: Huang N.
      - name: Li H.
      citationCount: 95
      date: '2023-10-01T00:00:00Z'
      journal: Bioinformatics
      title: 'compleasm: a faster and more accurate reimplementation of BUSCO'
    note: null
    pmcid: null
    pmid: null
    type: []
    version: null
  relation:
  - biotoolsID: busco
    type: isNewVersionOf
  toolType:
  - Command-line tool
  topic:
  - term: Sequence assembly
    uri: http://edamontology.org/topic_0196
  - term: Genomics
    uri: http://edamontology.org/topic_0622
  - term: Transcriptomics
    uri: http://edamontology.org/topic_3308
  - term: Sequence analysis
    uri: http://edamontology.org/topic_0080
  validated: 0
  version:
  - v.0.2.5
- accessibility: Open access
  additionDate: '2025-06-25T13:31:29.384393Z'
  biotoolsCURIE: biotools:fantasiav2
  biotoolsID: fantasiav2
  collectionID: []
  confidence_flag: tool
  cost: Free of charge
  credit:
  - email: fmpercan@upo.es
    fundrefid: null
    gridid: null
    name: Francisco Miguel Pérez Canales
    note: Programmer
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    - Developer
    - Documentor
    - Maintainer
    - Support
    - Provider
    url: http://www.bioinfocb.es/
  - email: a.rojas.m@csic.es
    fundrefid: null
    gridid: null
    name: Ana M Rojas Mendoza
    note: Scientific concept and functionalities
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    - Contributor
    - Documentor
    - Support
    url: http://www.bioinfocb.es/
  - email: rosa.fernandez@ibe.upf-csic.es
    fundrefid: null
    gridid: null
    name: Rosa Fernandez
    note: Scientific concept and functionalities
    orcidid: null
    rorid: null
    typeEntity: null
    typeRole:
    - Contributor
    - Documentor
    url: https://www.metazomics.com/
  - email: fraruimot@alum.us.es
    fundrefid: null
    gridid: null
    name: Francisco J. Ruiz Mota
    note: Junior developer
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: http://www.bioinfocb.es/
  - email: gemma.martinez@ibe.upf-csic.es
    fundrefid: null
    gridid: null
    name: Gemma Martinez Redondo
    note: Contributed  as developer of the first version of FANTASIA V1
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Contributor
    - Developer
    url: https://www.metazomics.com/
  description: FANTASIA (Functional ANnoTAtion based on embedding space SImilArity)
    is a pipeline for protein annotating via GO term transference using the embedding
    space. FANTASIA’s latest developments include additional protein language models
    and provide enhanced functionalities.
  documentation:
  - note: Full documetnation with user cases, benchmarking, and cluster implementations
    type:
    - General
    url: https://fantasia.readthedocs.io/en/latest/
  download: []
  editPermission:
    authors:
    - frapercan
    type: group
  elixirCommunity:
  - 3D-BioInfo
  - Proteomics
  elixirNode:
  - Spain
  elixirPlatform:
  - Tools
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Gene functional annotation
      uri: http://edamontology.org/operation_3672
    output: []
  homepage: https://github.com/CBBIO/FANTASIA
  homepage_status: 0
  language:
  - Python
  - SQL
  lastUpdate: '2025-06-25T14:34:50.629045Z'
  license: MIT
  link:
  - note: Main repository contains documentation  from latest version
    type:
    - Repository
    url: https://github.com/CBBIO/FANTASIA
  - note: Main repository contains documentation  from linitial version based on Bioembeddings
      implementation.
    type:
    - Repository
    url: https://github.com/MetazoaPhylogenomicsLab/FANTASIA
  - note: Recommended tool for the Earth Biogenome Project
    type:
    - Software catalogue
    url: https://www.earthbiogenome.org/report-on-annotation-recommended-tools
  maturity: Mature
  name: FANTASIAV2
  operatingSystem:
  - Linux
  otherID: []
  owner: arojas
  publication:
  - doi: 10.1093/nargab/lqae078
    metadata:
      abstract: Protein language models have been tested and proved to be reliable
        when used on curated datasets but have not yet been applied to full proteomes.
        Accordingly, we tested how two different machine learning-based methods performed
        when decoding functional information from the proteomes of selected model
        organisms. We found that protein language models are more precise and informative
        than deep learning methods for all the species tested and across the three
        gene ontologies studied, and that they better recover functional information
        from transcriptomic experiments. The results obtained indicate that these
        language models are likely to be suitable for large-scale annotation and downstream
        analyses, and we recommend a guide for their use.
      authors:
      - name: Barrios-Nunez I.
      - name: Martinez-Redondo G.I.
      - name: Medina-Burgos P.
      - name: Cases I.
      - name: Fernandez R.
      - name: Rojas A.M.
      citationCount: 1
      date: '2024-09-01T00:00:00Z'
      journal: NAR Genomics and Bioinformatics
      title: Decoding functional proteome information in model organisms using protein
        language models
    note: null
    pmcid: null
    pmid: null
    type:
    - Usage
    version: null
  - doi: 10.1101/2024.02.28.582465
    metadata: null
    note: null
    pmcid: null
    pmid: null
    type: []
    version: null
  relation: []
  toolType:
  - Command-line tool
  topic:
  - term: Molecular evolution
    uri: http://edamontology.org/topic_3945
  - term: Natural language processing
    uri: http://edamontology.org/topic_0218
  - term: Functional genomics
    uri: http://edamontology.org/topic_0085
  - term: Open science
    uri: http://edamontology.org/topic_4010
  validated: 0
  version:
  - 2.8.0
- accessibility: Open access
  additionDate: '2018-05-28T14:50:09Z'
  biotoolsCURIE: biotools:deepsig
  biotoolsID: deepsig
  collectionID:
  - Bologna Biocomputing Group
  confidence_flag: tool
  cost: Free of charge
  credit:
  - email: null
    fundrefid: null
    gridid: null
    name: ELIXIR-ITA-BOLOGNA
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
    - Provider
    url: http://biocomp.unibo.it
  - email: castrense.savojardo2@unibo.it
    fundrefid: null
    gridid: null
    name: Castrense Savojardo
    note: null
    orcidid: https://orcid.org/0000-0002-7359-0633
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    - Primary contact
    url: null
  - email: pierluigi.martelli@unibo.it
    fundrefid: null
    gridid: null
    name: Pier Luigi Martelli
    note: null
    orcidid: https://orcid.org/0000-0002-0274-5669
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: http://biocomp.unibo.it
  description: Prediction of secretory signal peptides in protein sequences
  documentation:
  - note: null
    type:
    - Command-line options
    url: https://github.com/BolognaBiocomp/deepsig
  download:
  - note: null
    type: Source code
    url: https://github.com/BolognaBiocomp/deepsig
    version: 1.2.5
  - note: null
    type: Container file
    url: https://hub.docker.com/r/bolognabiocomp/deepsig
    version: 1.2.5
  editPermission:
    authors:
    - savo
    - ELIXIR-ITA-BOLOGNA
    type: group
  elixirCommunity: []
  elixirNode:
  - Italy
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Protein sequence (raw)
        uri: http://edamontology.org/data_2974
      format:
      - term: FASTA
        uri: http://edamontology.org/format_1929
    - data:
        term: Taxonomy
        uri: http://edamontology.org/data_3028
      format:
      - term: Textual format
        uri: http://edamontology.org/format_2330
    note: null
    operation:
    - term: Protein signal peptide detection
      uri: http://edamontology.org/operation_0418
    output:
    - data:
        term: Protein report
        uri: http://edamontology.org/data_0896
      format:
      - term: HTML
        uri: http://edamontology.org/format_2331
  homepage: https://busca.biocomp.unibo.it/deepsig/
  homepage_status: 0
  language:
  - Python
  - C++
  lastUpdate: '2025-06-19T11:55:09.017105Z'
  license: GPL-3.0
  link: []
  maturity: Mature
  name: DeepSig
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: ELIXIR-ITA-BOLOGNA
  publication:
  - doi: 10.1093/bioinformatics/btx818
    metadata:
      abstract: Motivation The identification of signal peptides in protein sequences
        is an important step toward protein localization and function characterization.
        Results Here, we present DeepSig, an improved approach for signal peptide
        detection and cleavage-site prediction based on deep learning methods. Comparative
        benchmarks performed on an updated independent dataset of proteins show that
        DeepSig is the current best performing method, scoring better than other available
        state-of-the-art approaches on both signal peptide detection and precise cleavage-site
        identification. Availability and implementation DeepSig is available as both
        standalone program and web server at https://deepsig.biocomp.unibo.it. All
        datasets used in this study can be obtained from the same website.
      authors:
      - name: Savojardo C.
      - name: Martelli P.L.
      - name: Fariselli P.
      - name: Casadio R.
      citationCount: 96
      date: '2018-05-15T00:00:00Z'
      journal: Bioinformatics
      title: 'DeepSig: Deep learning improves signal peptide detection in proteins'
    note: null
    pmcid: PMC5946842
    pmid: '29280997'
    type:
    - Primary
    version: '1.0'
  relation: []
  toolType:
  - Web application
  - Command-line tool
  topic:
  - term: Computational biology
    uri: http://edamontology.org/topic_3307
  - term: Protein sites, features and motifs
    uri: http://edamontology.org/topic_3510
  - term: Protein properties
    uri: http://edamontology.org/topic_0123
  validated: 1
  version:
  - 1.2.5
- accessibility: Open access
  additionDate: '2025-06-17T20:53:54.551980Z'
  biotoolsCURIE: biotools:metasbt
  biotoolsID: metasbt
  collectionID: []
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: fabio.cumbo@gmail.com
    fundrefid: null
    gridid: null
    name: Fabio Cumbo
    note: null
    orcidid: https://orcid.org/0000-0003-2920-5838
    rorid: null
    typeEntity: null
    typeRole:
    - Primary contact
    - Developer
    - Maintainer
    - Support
    url: https://cumbof.github.io
  description: MetaSBT is a scalable framework designed to automatically index microbial
    genomes and accurately characterize metagenome-assembled genomes using Sequence
    Bloom Trees.
  documentation:
  - note: Official MetaSBT Wiki
    type:
    - General
    url: https://github.com/cumbof/MetaSBT/wiki
  download:
  - note: null
    type: Software package
    url: https://pypi.io/packages/source/m/metasbt/metasbt-0.1.4.post1.tar.gz
    version: 0.1.4
  editPermission:
    authors: []
    type: private
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  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function: []
  homepage: https://github.com/cumbof/MetaSBT
  homepage_status: 0
  language:
  - Python
  lastUpdate: '2025-06-18T17:12:50.842659Z'
  license: MIT
  link:
  - note: Framework Repository
    type:
    - Repository
    url: https://github.com/cumbof/MetaSBT
  - note: Repository with Public MetaSBT Databases
    type:
    - Repository
    url: https://github.com/cumbof/MetaSBT-DBs
  maturity: Mature
  name: MetaSBT
  operatingSystem:
  - Linux
  otherID: []
  owner: fabiocumbo
  publication: []
  relation: []
  toolType:
  - Command-line tool
  topic:
  - term: Metagenomics
    uri: http://edamontology.org/topic_3174
  validated: 0
  version:
  - 0.1.4.post1
- accessibility: Open access (with restrictions)
  additionDate: '2021-07-06T20:27:27Z'
  biotoolsCURIE: biotools:nanoplot
  biotoolsID: nanoplot
  collectionID:
  - ONTeater
  confidence_flag: null
  cost: Free of charge (with restrictions)
  credit:
  - email: null
    fundrefid: null
    gridid: null
    name: Wouter De Coster
    note: null
    orcidid: https://orcid.org/0000-0002-5248-8197
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: https://gigabaseorgigabyte.wordpress.com/
  description: NanoPlot is a tool with various visualizations of sequencing data in
    bam, cram, fastq, fasta or platform-specific TSV summaries, mainly intended for
    long-read sequencing from Oxford Nanopore Technologies and Pacific Biosciences
  documentation:
  - note: null
    type:
    - Command-line options
    url: https://github.com/wdecoster/NanoPlot
  download:
  - note: null
    type: Command-line specification
    url: https://anaconda.org/bioconda/nanoplot
    version: null
  - note: null
    type: Command-line specification
    url: https://pypi.org/project/NanoPlot/
    version: null
  editPermission:
    authors: []
    type: public
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: DNA sequence
        uri: http://edamontology.org/data_3494
      format:
      - term: FASTA-like
        uri: http://edamontology.org/format_2546
      - term: nucleotide
        uri: http://edamontology.org/format_1207
    note: null
    operation:
    - term: Scatter plot plotting
      uri: http://edamontology.org/operation_2940
    - term: Box-Whisker plot plotting
      uri: http://edamontology.org/operation_2943
    output: []
  homepage: https://github.com/wdecoster/NanoPlot
  homepage_status: 0
  language:
  - Python
  lastUpdate: '2025-06-18T12:31:48.762608Z'
  license: GPL-3.0
  link:
  - note: Issue tracker and most up to date software version
    type:
    - Repository
    url: https://github.com/wdecoster/NanoPlot
  - note: Web service with more limited options compared to the command line tool
    type:
    - Service
    url: http://nanoplot.bioinf.be/
  maturity: Mature
  name: NanoPlot
  operatingSystem:
  - Mac
  - Linux
  - Windows
  otherID: []
  owner: wdecoster
  publication:
  - doi: 10.1093/bioinformatics/bty149
    metadata:
      abstract: 'Summary: Here we describe NanoPack, a set of tools developed for
        visualization and processing of long-read sequencing data from Oxford Nanopore
        Technologies and Pacific Biosciences. Availability and implementation: The
        NanoPack tools are written in Python3 and released under the GNU GPL3.0 License.
        The source code can be found at https://github.com/wdecoster/nanopack, together
        with links to separate scripts and their documentation. The scripts are compatible
        with Linux, Mac OS and the MS Windows 10 subsystem for Linux and are available
        as a graphical user interface, a web service at http://nanoplot.bioinf.be
        and command line tools.'
      authors:
      - name: De Coster W.
      - name: D'Hert S.
      - name: Schultz D.T.
      - name: Cruts M.
      - name: Van Broeckhoven C.
      citationCount: 1840
      date: '2018-08-01T00:00:00Z'
      journal: Bioinformatics
      title: 'NanoPack: Visualizing and processing long-read sequencing data'
    note: null
    pmcid: PMC6061794
    pmid: '29547981'
    type:
    - Method
    version: null
  relation:
  - biotoolsID: nanopack
    type: includedIn
  toolType:
  - Command-line tool
  - Web application
  topic:
  - term: Genomics
    uri: http://edamontology.org/topic_0622
  validated: 0
  version:
  - v.1.42.0
- accessibility: Open access
  additionDate: '2022-05-16T13:26:15.720803Z'
  biotoolsCURIE: biotools:skm
  biotoolsID: skm
  collectionID:
  - ELIXIR-SI
  - Plant Systems Biology
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: null
    fundrefid: null
    gridid: null
    name: National Institute of Biology, Department of Biotechnology and Systems Biology
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
    - Provider
    url: http://www.nib.si/
  - email: carissarobyn.bleker@nib.si
    fundrefid: null
    gridid: null
    name: Carissa Bleker
    note: null
    orcidid: https://orcid.org/0000-0003-1617-7145
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    - Maintainer
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Kristina Gruden
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Contributor
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Živa Ramšak
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Contributor
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Vid Podpečan
    note: null
    orcidid: null
    rorid: null
    typeEntity: null
    typeRole:
    - Developer
    url: null
  description: 'Stress Knowledge Map:  A compilation of knowledge on mechanisms underlying
    responses of plants to stress, the so called stress signalling network.'
  documentation:
  - note: null
    type:
    - General
    url: https://skm.nib.si/documentation
  download: []
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  - Slovenia
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  function:
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    input:
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        term: Gene name
        uri: http://edamontology.org/data_2299
      format: []
    note: null
    operation:
    - term: Database search
      uri: http://edamontology.org/operation_2421
    output:
    - data:
        term: Database search results
        uri: http://edamontology.org/data_2080
      format:
      - term: JSON
        uri: http://edamontology.org/format_3464
      - term: sif
        uri: http://edamontology.org/format_3619
  - cmd: null
    input: []
    note: null
    operation:
    - term: Data retrieval
      uri: http://edamontology.org/operation_2422
    output:
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        term: Mathematical model
        uri: http://edamontology.org/data_0950
      format:
      - term: SBML
        uri: http://edamontology.org/format_2585
      - term: SBGN-ML
        uri: http://edamontology.org/format_3692
      - term: sif
        uri: http://edamontology.org/format_3619
  homepage: https://skm.nib.si/
  homepage_status: 0
  language: []
  lastUpdate: '2025-06-18T12:10:26.465410Z'
  license: null
  link:
  - note: null
    type:
    - Other
    url: https://skm.nib.si/contact
  maturity: Emerging
  name: SKM
  operatingSystem: []
  otherID: []
  owner: carissa
  publication:
  - doi: 10.1016/j.xplc.2024.100920
    metadata:
      abstract: 'Stress Knowledge Map (SKM; https://skm.nib.si) is a publicly available
        resource containing two complementary knowledge graphs that describe the current
        knowledge of biochemical, signaling, and regulatory molecular interactions
        in plants: a highly curated model of plant stress signaling (PSS; 543 reactions)
        and a large comprehensive knowledge network (488 390 interactions). Both were
        constructed by domain experts through systematic curation of diverse literature
        and database resources. SKM provides a single entry point for investigations
        of plant stress response and related growth trade-offs, as well as interactive
        explorations of current knowledge. PSS is also formulated as a qualitative
        and quantitative model for systems biology and thus represents a starting
        point for a plant digital twin. Here, we describe the features of SKM and
        show, through two case studies, how it can be used for complex analyses, including
        systematic hypothesis generation and design of validation experiments, or
        to gain new insights into experimental observations in plant biology.'
      authors:
      - name: Bleker C.
      - name: Ramsak
      - name: Bittner A.
      - name: Podpecan V.
      - name: Zagorscak M.
      - name: Wurzinger B.
      - name: Baebler
      - name: Petek M.
      - name: Kriznik M.
      - name: van Dieren A.
      - name: Gruber J.
      - name: Afjehi-Sadat L.
      - name: Weckwerth W.
      - name: Zupanic A.
      - name: Teige M.
      - name: Vothknecht U.C.
      - name: Gruden K.
      citationCount: 8
      date: '2024-06-10T00:00:00Z'
      journal: Plant Communications
      title: 'Stress Knowledge Map: A knowledge graph resource for systems biology
        analysis of plant stress responses'
    note: 'Stress Knowledge Map: A knowledge graph resource for systems biology analysis
      of plant stress responses'
    pmcid: null
    pmid: '38616489'
    type:
    - Primary
    version: null
  relation:
  - biotoolsID: gomapman
    type: uses
  - biotoolsID: newt-ve
    type: uses
  toolType:
  - Web application
  - Database portal
  topic:
  - term: Systems biology
    uri: http://edamontology.org/topic_2259
  - term: Molecular interactions, pathways and networks
    uri: http://edamontology.org/topic_0602
  - term: Plant biology
    uri: http://edamontology.org/topic_0780
  validated: 0
  version: []
- accessibility: Open access
  additionDate: '2019-11-14T20:08:20Z'
  biotoolsCURIE: biotools:Flye
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  collectionID:
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    fundrefid: null
    gridid: null
    name: Mikhail Kolmogorov
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    - Support
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Yu Lin
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Jeffrey Yuan
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: null
  description: 'Flye is a de novo assembler for single molecule sequencing reads,
    such as those produced by PacBio and Oxford Nanopore Technologies. It is designed
    for a wide range of datasets, from small bacterial projects to large mammalian-scale
    assemblies. The package represents a complete pipeline: it takes raw PB / ONT
    reads as input and outputs polished contigs.'
  documentation: []
  download: []
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    type: public
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  function:
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    input:
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        term: Sequence set (nucleic acid)
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      format:
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        uri: http://edamontology.org/format_1930
    note: null
    operation:
    - term: Genome assembly
      uri: http://edamontology.org/operation_0525
    - term: De-novo assembly
      uri: http://edamontology.org/operation_0524
    - term: Mapping assembly
      uri: http://edamontology.org/operation_0523
    - term: Cross-assembly
      uri: http://edamontology.org/operation_3730
    output:
    - data:
        term: Sequence set (nucleic acid)
        uri: http://edamontology.org/data_1234
      format:
      - term: FASTA
        uri: http://edamontology.org/format_1929
  homepage: https://github.com/fenderglass/Flye
  homepage_status: 0
  language:
  - C++
  - Python
  - C
  lastUpdate: '2025-06-18T10:20:03.775603Z'
  license: BSD-3-Clause
  link:
  - note: null
    type:
    - Issue tracker
    url: https://github.com/fenderglass/Flye/issues
  - note: null
    type:
    - Repository
    url: https://github.com/mikolmogorov/Flye
  maturity: null
  name: Flye
  operatingSystem:
  - Mac
  - Linux
  otherID: []
  owner: Pub2Tools
  publication:
  - doi: 10.1099/mgen.0.000294
    metadata:
      abstract: Illumina sequencing allows rapid, cheap and accurate whole genome
        bacterial analyses, but short reads (<300 bp) do not usually enable complete
        genome assembly. Long-read sequencing greatly assists with resolving complex
        bacterial genomes, particularly when combined with short-read Illumina data
        (hybrid assembly). However, it is not clear how different long-read sequencing
        methods affect hybrid assembly accuracy. Relative automation of the assembly
        process is also crucial to facilitating high-throughput complete bacterial
        genome reconstruction, avoiding multiple bespoke filtering and data manipulation
        steps. In this study, we compared hybrid assemblies for 20 bacterial isolates,
        including two reference strains, using Illumina sequencing and long reads
        from either Oxford Nanopore Technologies (ONT) or SMRT Pacific Biosciences
        (PacBio) sequencing platforms. We chose isolates from the family Enterobacteriaceae,
        as these frequently have highly plastic, repetitive genetic structures, and
        complete genome reconstruction for these species is relevant for a precise
        understanding of the epidemiology of antimicrobial resistance. We de novo
        assembled genomes using the hybrid assembler Unicycler and compared different
        read processing strategies, as well as comparing to long-read-only assembly
        with Flye followed by short-read polishing with Pilon. Hybrid assembly with
        either PacBio or ONT reads facilitated high-quality genome reconstruction,
        and was superior to the longread assembly and polishing approach evaluated
        with respect to accuracy and completeness. Combining ONT and Illumina reads
        fully resolved most genomes without additional manual steps, and at a lower
        consumables cost per isolate in our setting. Automated hybrid assembly is
        a powerful tool for complete and accurate bacterial genome assembly.
      authors:
      - name: De Maio N.
      - name: Shaw L.P.
      - name: Hubbard A.
      - name: George S.
      - name: Sanderson N.D.
      - name: Swann J.
      - name: Wick R.
      - name: Oun M.A.
      - name: Stubberfield E.
      - name: Hoosdally S.J.
      - name: Crook D.W.
      - name: Peto T.E.A.
      - name: Sheppard A.E.
      - name: Bailey M.J.
      - name: Read D.S.
      - name: Anjum M.F.
      - name: Sarah Walker A.
      - name: Stoesser N.
      citationCount: 166
      date: '2019-01-01T00:00:00Z'
      journal: Microbial Genomics
      title: Comparison of long-read sequencing technologies in the hybrid assembly
        of complex bacterial genomes
    note: null
    pmcid: PMC6807382
    pmid: '31483244'
    type:
    - Usage
    version: null
  - doi: 10.1038/s41587-019-0072-8
    metadata:
      abstract: Accurate genome assembly is hampered by repetitive regions. Although
        long single molecule sequencing reads are better able to resolve genomic repeats
        than short-read data, most long-read assembly algorithms do not provide the
        repeat characterization necessary for producing optimal assemblies. Here,
        we present Flye, a long-read assembly algorithm that generates arbitrary paths
        in an unknown repeat graph, called disjointigs, and constructs an accurate
        repeat graph from these error-riddled disjointigs. We benchmark Flye against
        five state-of-the-art assemblers and show that it generates better or comparable
        assemblies, while being an order of magnitude faster. Flye nearly doubled
        the contiguity of the human genome assembly (as measured by the NGA50 assembly
        quality metric) compared with existing assemblers.
      authors:
      - name: Kolmogorov M.
      - name: Yuan J.
      - name: Lin Y.
      - name: Pevzner P.A.
      citationCount: 3077
      date: '2019-05-01T00:00:00Z'
      journal: Nature Biotechnology
      title: Assembly of long, error-prone reads using repeat graphs
    note: null
    pmcid: null
    pmid: '30936562'
    type:
    - Primary
    version: null
  - doi: 10.1038/s41592-020-00971-x
    metadata:
      abstract: Long-read sequencing technologies have substantially improved the
        assemblies of many isolate bacterial genomes as compared to fragmented short-read
        assemblies. However, assembling complex metagenomic datasets remains difficult
        even for state-of-the-art long-read assemblers. Here we present metaFlye,
        which addresses important long-read metagenomic assembly challenges, such
        as uneven bacterial composition and intra-species heterogeneity. First, we
        benchmarked metaFlye using simulated and mock bacterial communities and show
        that it consistently produces assemblies with better completeness and contiguity
        than state-of-the-art long-read assemblers. Second, we performed long-read
        sequencing of the sheep microbiome and applied metaFlye to reconstruct 63
        complete or nearly complete bacterial genomes within single contigs. Finally,
        we show that long-read assembly of human microbiomes enables the discovery
        of full-length biosynthetic gene clusters that encode biomedically important
        natural products.
      authors:
      - name: Kolmogorov M.
      - name: Bickhart D.M.
      - name: Behsaz B.
      - name: Gurevich A.
      - name: Rayko M.
      - name: Shin S.B.
      - name: Kuhn K.
      - name: Yuan J.
      - name: Polevikov E.
      - name: Smith T.P.L.
      - name: Pevzner P.A.
      citationCount: 511
      date: '2020-11-01T00:00:00Z'
      journal: Nature Methods
      title: 'metaFlye: scalable long-read metagenome assembly using repeat graphs'
    note: null
    pmcid: PMC10699202
    pmid: '33020656'
    type:
    - Primary
    version: null
  relation: []
  toolType:
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  - Workflow
  topic:
  - term: Sequence assembly
    uri: http://edamontology.org/topic_0196
  - term: Metagenomics
    uri: http://edamontology.org/topic_3174
  - term: Whole genome sequencing
    uri: http://edamontology.org/topic_3673
  - term: Genomics
    uri: http://edamontology.org/topic_0622
  validated: 1
  version:
  - 2.9.6
- accessibility: Open access
  additionDate: '2020-06-18T05:28:02Z'
  biotoolsCURIE: biotools:biosimulations
  biotoolsID: biosimulations
  collectionID: []
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: karr@mssm.edu
    fundrefid: null
    gridid: null
    name: Jonathan Karr
    note: null
    orcidid: https://orcid.org/0000-0002-2605-5080
    rorid: null
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    typeRole:
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    url: https://www.karrlab.org
  - email: null
    fundrefid: null
    gridid: null
    name: Bilal Shaikh
    note: null
    orcidid: https://orcid.org/0000-0001-5801-5510
    rorid: null
    typeEntity: Person
    typeRole:
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    url: null
  description: BioSimulations is a web application for sharing and re-using biomodels,
    simulations, and visualizations of simulations results. BioSimulations supports
    a wide range of modeling frameworks (e.g., kinetic, constraint-based, and logical
    modeling), model formats (e.g., BNGL, CellML, SBML), and simulation tools (e.g.,
    COPASI, libRoadRunner/tellurium, NFSim, VCell). BioSimulations aims to help researchers
    discover published models that might be useful for their research and quickly
    try them via a simple web-based interface.
  documentation:
  - note: null
    type:
    - General
    url: https://docs.biosimulations.org
  - note: null
    type:
    - API documentation
    url: https://api.biosimulations.org/
  - note: null
    type:
    - Code of conduct
    url: https://docs.biosimulations.org/developers/conduct/
  - note: null
    type:
    - Terms of use
    url: https://docs.biosimulations.org/about/terms/
  download: []
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  function:
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        uri: http://edamontology.org/format_2585
      - term: CellML
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    note: null
    operation:
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    - term: Modelling and simulation
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    output:
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        term: Trajectory data
        uri: http://edamontology.org/data_3870
      format:
      - term: CSV
        uri: http://edamontology.org/format_3752
      - term: SVG
        uri: http://edamontology.org/format_3604
  homepage: https://www.biosimulations.org/
  homepage_status: 0
  language:
  - JavaScript
  - Python
  lastUpdate: '2025-06-17T16:32:28.548746Z'
  license: MIT
  link:
  - note: null
    type:
    - Issue tracker
    url: https://github.com/reproducible-biomedical-modeling/Biosimulations/issues
  - note: null
    type:
    - Repository
    url: https://github.com/reproducible-biomedical-modeling/Biosimulations
  - note: null
    type:
    - Service
    url: https://api.biosimulations.org/
  maturity: Emerging
  name: BioSimulations
  operatingSystem: []
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    value: RRID:SCR_018733
    version: null
  owner: Bioinfo
  publication: []
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    type: uses
  - biotoolsID: biomodels
    type: uses
  - biotoolsID: sbml
    type: uses
  - biotoolsID: bionetgen
    type: uses
  - biotoolsID: cobrapy
    type: uses
  - biotoolsID: copasi
    type: uses
  - biotoolsID: libroadrunner
    type: uses
  toolType:
  - Command-line tool
  - Web API
  - Web application
  - Web service
  topic:
  - term: Systems biology
    uri: http://edamontology.org/topic_2259
  - term: Molecular interactions, pathways and networks
    uri: http://edamontology.org/topic_0602
  validated: 1
  version: []
- accessibility: null
  additionDate: '2017-12-12T17:28:02Z'
  biotoolsCURIE: biotools:askomics
  biotoolsID: askomics
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  confidence_flag: null
  cost: Free of charge
  credit:
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    fundrefid: null
    gridid: null
    name: Olivier Dameron
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
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    url: null
  - email: olivier.filangi@inra.fr
    fundrefid: null
    gridid: null
    name: Olivier Filangi
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: null
  - email: anthony.bretaudeau@irisa.fr
    fundrefid: null
    gridid: null
    name: Anthony Bretaudeau
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
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    url: null
  description: AskOmics is a visual SPARQL query interface supporting both intuitive
    data integration and querying while shielding the user from most of the technical
    difficulties underlying RDF and SPARQL
  documentation:
  - note: null
    type:
    - General
    url: https://github.com/askomics/askomics
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    type: Software package
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    version: null
  - note: null
    type: Container file
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    - data:
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      - term: DSV
        uri: http://edamontology.org/format_3751
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    - term: Data retrieval
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    - term: Query and retrieval
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    - data:
        term: Data
        uri: http://edamontology.org/data_0006
      format:
      - term: DSV
        uri: http://edamontology.org/format_3751
      - term: RDF format
        uri: http://edamontology.org/format_2376
  homepage: https://github.com/askomics
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  language:
  - Python
  lastUpdate: '2025-06-09T11:52:30.706337Z'
  license: AGPL-3.0
  link: []
  maturity: Mature
  name: Askomics
  operatingSystem:
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  - Mac
  otherID: []
  owner: mboudet
  publication: []
  relation: []
  toolType:
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  - term: Data integration and warehousing
    uri: http://edamontology.org/topic_3366
  validated: 1
  version: []
- accessibility: Open access
  additionDate: '2021-05-26T20:42:18Z'
  biotoolsCURIE: biotools:maldi_quant
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  collectionID: []
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: mail@sebastiangibb.de
    fundrefid: null
    gridid: null
    name: Sebastian Gibb
    note: null
    orcidid: https://orcid.org/0000-0001-7406-4443
    rorid: null
    typeEntity: Person
    typeRole:
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    - Developer
    - Maintainer
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Korbinian Strimmer
    note: null
    orcidid: https://orcid.org/0000-0001-7917-2056
    rorid: null
    typeEntity: Person
    typeRole:
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    url: null
  description: MALDIquant is a complete analysis pipeline for matrix-assisted laser
    desorption/ionization-time-of-flight (MALDI-TOF) and other two-dimensional mass
    spectrometry data. In addition to commonly used plotting and processing methods
    it includes distinctive features, namely baseline subtraction methods such as
    morphological filters (TopHat) or the statistics-sensitive non-linear iterative
    peak-clipping algorithm (SNIP), peak alignment using warping functions, handling
    of replicated measurements as well as allowing spectra with different resolutions.
  documentation:
  - note: null
    type:
    - General
    url: https://cran.r-project.org/web/packages/MALDIquant/MALDIquant.pdf
  download: []
  editPermission:
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  function:
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    input:
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        term: Mass spectrometry data
        uri: http://edamontology.org/data_2536
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        uri: http://edamontology.org/format_3682
    - data:
        term: Mass spectrometry data
        uri: http://edamontology.org/data_2536
      format:
      - term: ibd
        uri: http://edamontology.org/format_3839
    note: null
    operation:
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      uri: http://edamontology.org/operation_3215
    output:
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        term: Report
        uri: http://edamontology.org/data_2048
      format:
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        uri: http://edamontology.org/format_3752
  - cmd: null
    input:
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        uri: http://edamontology.org/format_3682
    - data:
        term: Mass spectrometry data
        uri: http://edamontology.org/data_2536
      format:
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        uri: http://edamontology.org/format_3839
    note: null
    operation:
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      uri: http://edamontology.org/operation_0337
    output:
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      format:
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  - cmd: null
    input:
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    - data:
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    note: null
    operation:
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    output:
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  description: Package that allows to explore the exposome and to perform association
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      samples classification after performing a clustering based on the variables,
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    metadata:
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        the molecular origins of certain human diseases. Nonetheless, our health is
        also influenced by the cumulative impact of exposures experienced across the
        life course (termed ''exposome''). The study of the high-dimensional exposome
        offers a new paradigm for investigating environmental contributions to disease
        etiology. However, there is a lack of bioinformatics tools for managing, visualizing
        and analyzing the exposome. The analysis data should include both association
        with health outcomes and integration with omic layers. We provide a generic
        framework called rexposome project, developed in the R/Bioconductor architecture
        that includes object-oriented classes and methods to leverage high-dimensional
        exposome data in disease association studies including its integration with
        a variety of high-throughput data types. The usefulness of the package is
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        and methylome.'
      authors:
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      - name: Wellenius G.A.
      - name: Tamayo I.
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      abstract: Environmental exposures during early life play a critical role in
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        effects on health are poorly understood. In the Human Early Life Exposome
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        individual exposomes consisting of >100 chemical, outdoor, social and lifestyle
        exposures assessed in pregnancy and childhood, with multi-omics profiles (methylome,
        transcriptome, proteins and metabolites) in childhood. We identify 1170 associations,
        249 in pregnancy and 921 in childhood, which reveal potential biological responses
        and sources of exposure. Pregnancy exposures, including maternal smoking,
        cadmium and molybdenum, are predominantly associated with child DNA methylation
        changes. In contrast, childhood exposures are associated with features across
        all omics layers, most frequently the serum metabolome, revealing signatures
        for diet, toxic chemical compounds, essential trace elements, and weather
        conditions, among others. Our comprehensive and unique resource of all associations
        (https://helixomics.isglobal.org/) will serve to guide future investigation
        into the biological imprints of the early life exposome.
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      - name: Bustamante M.
      - name: Hernandez-Ferrer C.
      - name: Thiel D.
      - name: Lau C.-H.E.
      - name: Siskos A.P.
      - name: Vives-Usano M.
      - name: Ruiz-Arenas C.
      - name: Pelegri-Siso D.
      - name: Robinson O.
      - name: Mason D.
      - name: Wright J.
      - name: Cadiou S.
      - name: Slama R.
      - name: Heude B.
      - name: Casas M.
      - name: Sunyer J.
      - name: Papadopoulou E.Z.
      - name: Gutzkow K.B.
      - name: Andrusaityte S.
      - name: Grazuleviciene R.
      - name: Vafeiadi M.
      - name: Chatzi L.
      - name: Sakhi A.K.
      - name: Thomsen C.
      - name: Tamayo I.
      - name: Nieuwenhuijsen M.
      - name: Urquiza J.
      - name: Borras E.
      - name: Sabido E.
      - name: Quintela I.
      - name: Carracedo A.
      - name: Estivill X.
      - name: Coen M.
      - name: Gonzalez J.R.
      - name: Keun H.C.
      - name: Vrijheid M.
      citationCount: 81
      date: '2022-12-01T00:00:00Z'
      journal: Nature Communications
      title: Multi-omics signatures of the human early life exposome
    note: null
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      abstract: A key step in most viral infections is the binding of a viral protein
        to a host receptor, leading to the virus entering the host cell. Disrupting
        this protein-protein interaction is an effective strategy for preventing infection
        and subsequent disease. Building on recent advances in computational tools
        for structural biology, we introduce Virus Inhibition via Peptide Engineering
        and Receptor Mimicry (VIPER), a novel approach for the automatic derivation
        and optimization of biomimetic decoy peptides that mimic binding sites of
        human proteins. VIPER leverages structural data from human-pathogen protein
        complexes, yielding peptides that can competitively inhibit viral entry by
        mimicking the natural receptor. We computationally validated VIPER using molecular
        dynamics simulations and showcased its applicability on three clinically relevant
        viruses, highlighting its potential to accelerate therapeutic development.
        With a focus on reproducibility and extensibility, VIPER can facilitate the
        rapid development of antiviral inhibitors by automating the design and optimization
        of biomimetic compounds.
      authors:
      - name: Klingenberg A.S.
      - name: Ghersi D.
      citationCount: 0
      date: '2025-04-01T00:00:00Z'
      journal: 'Journal of computational biology : a journal of computational molecular
        cell biology'
      title: 'VIPER: Virus Inhibition Via Peptide Engineering and Receptor Mimicry'
    note: null
    pmcid: null
    pmid: null
    type: []
    version: null
  - doi: 10.5281/zenodo.10897858
    metadata: null
    note: null
    pmcid: null
    pmid: null
    type: []
    version: null
  relation: []
  toolType:
  - Command-line tool
  topic:
  - term: Protein structure analysis
    uri: http://edamontology.org/topic_2814
  - term: Virology
    uri: http://edamontology.org/topic_0781
  - term: Bioinformatics
    uri: http://edamontology.org/topic_0091
  validated: 0
  version:
  - 1.0.1
- accessibility: Open access
  additionDate: '2024-08-02T20:40:51.771278Z'
  biotoolsCURIE: biotools:kvfinder-web
  biotoolsID: kvfinder-web
  collectionID:
  - COVID-19
  - Rare Disease
  - KVFinder suite
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: joao.guerra@lnbio.cnpem.br
    fundrefid: null
    gridid: null
    name: João V. S. Guerra
    note: null
    orcidid: https://orcid.org/0000-0002-6800-4425
    rorid: null
    typeEntity: null
    typeRole:
    - Developer
    - Primary contact
    url: https://github.com/jvsguerra
  - email: null
    fundrefid: null
    gridid: null
    name: Helder V. Ribeiro-Filho
    note: null
    orcidid: null
    rorid: null
    typeEntity: null
    typeRole: []
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: José G. C. Pereira
    note: null
    orcidid: null
    rorid: null
    typeEntity: null
    typeRole: []
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Paulo S. Lopes-de-Oliveira
    note: null
    orcidid: null
    rorid: null
    typeEntity: null
    typeRole:
    - Primary contact
    url: null
  description: "KVFinder-web is an open-source web-based application of an updated\
    \ version of parKVFinder software (v1.2.0) for cavity detection and characterization\
    \ of any type of biomolecular structure, including but not limited to proteins\
    \ and nucleic acids. \n\nKVFinder-web employs a geometric grid-and-sphere-based\
    \ method with a dual-probe system for efficient cavity detection. The web-based\
    \ application provides comprehensive characterizations, including shape, volume,\
    \ area, depth, constitutional, and hydropathy information."
  documentation:
  - note: null
    type:
    - API documentation
    url: https://lbc-lnbio.github.io/KVFinder-web/
  download: []
  editPermission:
    authors: []
    type: private
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  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Structure
        uri: http://edamontology.org/data_0883
      format:
      - term: PDB
        uri: http://edamontology.org/format_1476
    note: null
    operation:
    - term: Binding site prediction
      uri: http://edamontology.org/operation_2575
    output:
    - data:
        term: Protein structural motif
        uri: http://edamontology.org/data_2878
      format:
      - term: Textual format
        uri: http://edamontology.org/format_2330
  homepage: https://kvfinder-web.cnpem.br/
  homepage_status: 0
  language:
  - R
  - C
  - Other
  lastUpdate: '2025-05-14T16:17:24.394544Z'
  license: Apache-2.0
  link:
  - note: null
    type:
    - Other
    url: https://github.com/LBC-LNBio/KVFinder-web
  - note: null
    type:
    - Repository
    url: https://github.com/LBC-LNBio/KVFinder-web-service
  - note: null
    type:
    - Repository
    url: https://github.com/LBC-LNBio/KVFinder-web-portal
  - note: null
    type:
    - Repository
    url: https://github.com/LBC-LNBio/PyMOL-KVFinder-web-Tools
  maturity: Mature
  name: KVFinder-web
  operatingSystem:
  - Mac
  - Linux
  - Windows
  otherID: []
  owner: jvsguerra
  publication:
  - doi: 10.1093/nar/gkad324
    metadata:
      abstract: 'Molecular interactions that modulate catalytic processes occur mainly
        in cavities throughout the molecular surface. Such interactions occur with
        specific small molecules due to geometric and physicochemical complementarity
        with the receptor. In this scenario, we present KVFinder-web, an open-source
        web-based application of parKVFinder software for cavity detection and characterization
        of biomolecular structures. The KVFinder-web has two independent components:
        A RESTful web service and a web graphical portal. Our web service, KVFinder-web
        service, handles client requests, manages accepted jobs, and performs cavity
        detection and characterization on accepted jobs. Our graphical web portal,
        KVFinder-web portal, provides a simple and straightforward page for cavity
        analysis, which customizes detection parameters, submits jobs to the web service
        component, and displays cavities and characterizations. We provide a publicly
        available KVFinder-web at https://kvfinder-web.cnpem.br, running in a cloud
        environment as docker containers. Further, this deployment type allows KVFinder-web
        components to be configured locally and customized according to user demand.
        Hence, users may run jobs on a locally configured service or our public KVFinder-web.'
      authors:
      - name: Guerra J.V.S.
      - name: Ribeiro-Filho H.V.
      - name: Pereira J.G.C.
      - name: Lopes-De-Oliveira P.S.
      citationCount: 13
      date: '2023-07-05T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'KVFinder-web: A web-based application for detecting and characterizing
        biomolecular cavities'
    note: null
    pmcid: PMC10320092
    pmid: '37140050'
    type:
    - Primary
    version: null
  - doi: 10.1021/acs.jcim.3c00328
    metadata:
      abstract: Confining molecular guests within artificial hosts has provided a
        major driving force in the rational design of supramolecular cages with tailored
        properties. Over the last 30 years, a set of design strategies have been developed
        that enabled the controlled synthesis of a myriad of cages. Recently, there
        has been a growing interest in involving in silico methods in this toolbox.
        Cavity shape and size are important parameters that can be easily accessed
        by inexpensive geometric algorithms. Although these algorithms are well developed
        for the detection of nonartificial cavities (e.g., enzymes), they are not
        routinely used for the rational design of supramolecular cages. In order to
        test the capabilities of this tool, we have evaluated the performance and
        characteristics of seven different cavity characterization software in the
        context of 22 analogues of well-known supramolecular cages. Among the tested
        software, KVFinder project and Fpocket proved to be the most software to characterize
        supramolecular cavities. With the results of this work, we aim to popularize
        this underused technique within the supramolecular community.
      authors:
      - name: Guerra J.V.S.
      - name: Alves L.F.G.
      - name: Bourissou D.
      - name: Lopes-De-Oliveira P.S.
      - name: Szaloki G.
      citationCount: 3
      date: '2023-06-26T00:00:00Z'
      journal: Journal of Chemical Information and Modeling
      title: Cavity Characterization in Supramolecular Cages
    note: null
    pmcid: null
    pmid: '37129917'
    type:
    - Benchmarking study
    version: null
  relation:
  - biotoolsID: parKVFinder
    type: uses
  - biotoolsID: KVFinder
    type: isNewVersionOf
  toolType:
  - Web service
  - Web API
  topic:
  - term: Structural biology
    uri: http://edamontology.org/topic_1317
  - term: Computational biology
    uri: http://edamontology.org/topic_3307
  - term: Protein structural motifs and surfaces
    uri: http://edamontology.org/topic_0166
  validated: 0
  version:
  - v1.1.1
- accessibility: Open access
  additionDate: '2025-05-09T18:13:37.471507Z'
  biotoolsCURIE: biotools:fermo-core
  biotoolsID: fermo-core
  collectionID:
  - FERMO
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: zdoucmm@gmail.com
    fundrefid: null
    gridid: null
    name: Mitja M. Zdouc
    note: Lead Developer and Initiator
    orcidid: https://orcid.org/0000-0001-6534-6609
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: https://github.com/mmzdouc
  - email: null
    fundrefid: null
    gridid: null
    name: Fermo Metabolomics
    note: GitHub Community overseeing development of the project
    orcidid: null
    rorid: null
    typeEntity: Project
    typeRole:
    - Maintainer
    url: https://github.com/fermo-metabolomics
  description: fermo-core is the backend of the metabolomics dashboard FERMO. It can
    be used for large-scale processing of metabolomics data and integration of phenotypic
    and other orthogonal data.
  documentation:
  - note: null
    type:
    - User manual
    url: https://fermo-metabolomics.github.io/fermo_docs/
  download:
  - note: null
    type: Source code
    url: https://github.com/fermo-metabolomics/fermo_core/releases/tag/0.6.3
    version: 0.6.3
  - note: PyPI-deposited wheel and source code
    type: Source code
    url: https://pypi.org/project/fermo-core/0.6.3/
    version: 0.6.3
  editPermission:
    authors: []
    type: public
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function: []
  homepage: https://github.com/fermo-metabolomics/fermo_core
  homepage_status: 0
  language:
  - Python
  lastUpdate: '2025-05-09T18:46:02.403653Z'
  license: MIT
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/fermo-metabolomics/fermo_core
  - note: GitHub Community managing FERMO-related repositories
    type:
    - Repository
    url: https://github.com/fermo-metabolomics
  - note: null
    type:
    - Discussion forum
    url: https://github.com/orgs/fermo-metabolomics/discussions
  maturity: Emerging
  name: fermo-core
  operatingSystem:
  - Linux
  otherID: []
  owner: mmzdouc
  publication:
  - doi: 10.1101/2022.12.21.521422
    metadata: null
    note: Preprint released on bioRxiv
    pmcid: null
    pmid: null
    type: []
    version: null
  relation: []
  toolType:
  - Command-line tool
  - Library
  topic:
  - term: Metabolomics
    uri: http://edamontology.org/topic_3172
  validated: 0
  version:
  - 0.6.3
- accessibility: Open access
  additionDate: '2025-05-09T18:02:39.924632Z'
  biotoolsCURIE: biotools:fermo
  biotoolsID: fermo
  collectionID:
  - FERMO
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: zdoucmm@gmail.com
    fundrefid: null
    gridid: null
    name: Mitja M. Zdouc
    note: Initiator and lead developer
    orcidid: https://orcid.org/0000-0001-6534-6609
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Fermo Metabolomics
    note: Governing body overseeing development
    orcidid: null
    rorid: null
    typeEntity: Project
    typeRole:
    - Maintainer
    url: https://github.com/fermo-metabolomics
  description: FERMO is a metabolomics dashboard  designed to facilitate hypothesis-driven
    prioritization of molecules and samples, and integrates LC-MS metabolomics data
    with phenotype information, sample grouping, and genomic data. FERMO is applicable
    in a variety of biological sciences, including natural product drug discovery,
    microbiology, or agriculture.
  documentation:
  - note: null
    type:
    - User manual
    url: https://fermo-metabolomics.github.io/fermo_docs/
  download:
  - note: null
    type: Source code
    url: https://github.com/fermo-metabolomics/FERMO/releases/tag/1.1.0
    version: 1.1.0
  editPermission:
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  elixir_badge: 0
  function: []
  homepage: https://github.com/fermo-metabolomics/fermo
  homepage_status: 0
  language:
  - Python
  lastUpdate: '2025-05-09T18:14:33.071182Z'
  license: MIT
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/fermo-metabolomics/fermo
  - note: GitHub Organization page organizing repositories related to FERMO
    type:
    - Repository
    url: https://github.com/fermo-metabolomics
  - note: null
    type:
    - Discussion forum
    url: https://github.com/orgs/fermo-metabolomics/discussions
  maturity: Emerging
  name: fermo
  operatingSystem:
  - Mac
  - Linux
  - Windows
  otherID: []
  owner: mmzdouc
  publication:
  - doi: 10.1101/2022.12.21.521422
    metadata: null
    note: Preprint released on bioRxiv
    pmcid: null
    pmid: null
    type:
    - Primary
    version: null
  relation: []
  toolType:
  - Web application
  - Desktop application
  topic:
  - term: Metabolomics
    uri: http://edamontology.org/topic_3172
  validated: 0
  version:
  - 1.1.0
- 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: '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:
    - Primary contact
    - Developer
    - Maintainer
    url: null
  - email: cubimed@rub.de
    fundrefid: null
    gridid: null
    name: CUBiMed.RUB
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
    - Provider
    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:
  - '1.5'
- accessibility: null
  additionDate: '2023-02-07T14:25:10.924789Z'
  biotoolsCURIE: biotools:epimutacions
  biotoolsID: epimutacions
  collectionID: []
  confidence_flag: null
  cost: null
  credit:
  - email: carlos.ruiz@isglobal.org
    fundrefid: null
    gridid: null
    name: Carlos Ruiz-Arenas
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: null
  - email: leire.abarrategui@isglobal.org
    fundrefid: null
    gridid: null
    name: Leire Abarrategui
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: null
  - email: carles.hernandez@isglobal.org
    fundrefid: null
    gridid: null
    name: Carles Hernandez-Ferrer
    note: null
    orcidid: https://orcid.org/0000-0002-8029-7160
    rorid: null
    typeEntity: null
    typeRole: []
    url: http://www.carleshf.com
  - email: dolors.pelegri@isglobal.org
    fundrefid: null
    gridid: null
    name: Dolors Pelegri-Siso
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Maintainer
    url: null
  - email: juanr.gonzalez@isglobal.org
    fundrefid: null
    gridid: null
    name: Juan R. Gonzalez
    note: null
    orcidid: null
    rorid: null
    typeEntity: null
    typeRole: []
    url: https://brge.isglobal.org/
  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.
  documentation:
  - note: null
    type:
    - API documentation
    url: https://www.bioconductor.org/packages/release/bioc/manuals/epimutacions/man/epimutacions.pdf
  - note: null
    type:
    - User manual
    url: https://www.bioconductor.org/packages/release/bioc/vignettes/epimutacions/inst/doc/epimutacions.html
  download:
  - note: null
    type: Source code
    url: https://www.bioconductor.org/packages/release/bioc/src/contrib/epimutacions_1.2.0.tar.gz
    version: 1.2.0
  editPermission:
    authors: []
    type: public
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function: []
  homepage: https://www.bioconductor.org/packages/release/bioc/html/epimutacions.html
  homepage_status: 0
  language: []
  lastUpdate: '2025-05-01T22:27:05.714967Z'
  license: null
  link:
  - note: null
    type:
    - Mirror
    url: https://www.bioconductor.org/packages/epimutacions
  maturity: null
  name: epimutacions
  operatingSystem: []
  otherID: []
  owner: chernan3
  publication:
  - doi: 10.1080/15592294.2023.2230670
    metadata:
      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).
        epimutacions implements two previously reported methods and four new statistical
        approaches to detect epimutations, along with functions to annotate and visualize
        epimutations. Additionally, we have developed an user-friendly Shiny app to
        facilitate epimutations detection (https://github.com/isglobal-brge/epimutacionsShiny)
        to non-bioinformatician users. We first compared the performance of epimutacions
        and ramr packages using three public datasets with experimentally validated
        epimutations. Methods in epimutacions had a high performance at low sample
        sizes and outperformed methods in ramr. Second, we used two general population
        children cohorts (INMA and HELIX) to determine the technical and biological
        factors that affect epimutations detection, providing guidelines on how designing
        the experiments or preprocessing the data. In these cohorts, most epimutations
        did not correlate with detectable regional gene expression changes. Finally,
        we exemplified how epimutacions can be used in a clinical context. We run
        epimutacions in a cohort of children with autism disorder and identified novel
        recurrent epimutations in candidate genes for autism. Overall, we present
        epimutacions a new Bioconductor package for incorporating epimutations detection
        to rare disease diagnosis and provide guidelines for the design and data analyses.'
      authors:
      - name: Ruiz-Arenas C.
      - name: Abarrategui L.
      - name: Hernandez-Ferrer C.
      - name: Escriba-Montagut X.
      - name: Pelegri-Siso D.
      - name: Ryser-Welch P.
      - name: Vrijheid M.
      - name: Bustamante M.
      - name: Grazuleviciene R.
      - name: Lepeule J.
      - name: Mathai M.
      - name: Vafeiadi M.
      - name: Beltran S.
      - name: Perez-Jurado L.A.
      - name: Gonzalez J.R.
      citationCount: 0
      date: '2023-01-01T00:00:00Z'
      journal: Epigenetics
      title: 'Epimutation detection in the clinical context: guidelines and a use
        case from a new Bioconductor package'
    note: null
    pmcid: PMC10327521
    pmid: '37409354'
    type:
    - Primary
    version: null
  relation: []
  toolType: []
  topic:
  - term: Epigenetics
    uri: http://edamontology.org/topic_3295
  validated: 0
  version:
  - 1.2.0
- 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: 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
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  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:
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  owner: dgoebel
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    metadata: null
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    type:
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  relation:
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  topic:
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  validated: 0
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- accessibility: Open access
  additionDate: '2025-03-28T11:01:52.929561Z'
  biotoolsCURIE: biotools:chemfh
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    name: Jiacai Yi
    note: National University of Defense Technology, Changsha, Hunan
    orcidid: https://orcid.org/0000-0001-6823-1882
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  description: 'An integrated online platform developed for the screening and prediction
    of potential frequent drug hitters, thus improving the efficiency of drug R&D
    in colloidal aggregate, firefly luciferase reporter enzyme inhibition, fluorescence,
    chemical reactivity, and promiscuity. ChemFH: an integrated tool for screening
    frequent false positives in chemical biology and drug discovery.'
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    type:
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      format: []
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  language:
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  license: MIT
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    type:
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    metadata:
      abstract: High-throughput screening rapidly tests an extensive array of chemical
        compounds to identify hit compounds for specific biological targets in drug
        discovery. However, false-positive results disrupt hit compound screening,
        leading to wastage of time and resources. To address this, we propose ChemFH,
        an integrated online platform facilitating rapid virtual evaluation of potential
        false positives, including colloidal aggregators, spectroscopic interference
        compounds, firefly luciferase inhibitors, chemical reactive compounds, promiscuous
        compounds, and other assay interferences. By leveraging a dataset containing
        823 391 compounds, we constructed high-quality prediction models using multi-task
        directed message-passing network (DMPNN) architectures combining uncertainty
        estimation, yielding an average AUC value of 0.91. Furthermore, ChemFH incorporated
        1441 representative alert substructures derived from the collected data and
        ten commonly used frequent hitter screening rules. ChemFH was validated with
        an external set of 75 compounds. Subsequently, the virtual screening capability
        of ChemFH was successfully confirmed through its application to five virtual
        screening libraries. Furthermore, ChemFH underwent additional validation on
        two natural products and FDA-approved drugs, yielding reliable and accurate
        results. ChemFH is a comprehensive, reliable, and computationally efficient
        screening pipeline that facilitates the identification of true positive results
        in assays, contributing to enhanced efficiency and success rates in drug discovery.
        ChemFH is freely available via https://chemfh.scbdd.com/.
      authors:
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      - name: Fu L.
      - name: Yi J.
      - name: Yang Z.
      - name: Zhang X.
      - name: Deng Y.
      - name: Wang W.
      - name: Wu C.
      - name: Zhao W.
      - name: Hou T.
      - name: Zeng X.
      - name: Lyu A.
      - name: Cao D.
      citationCount: 0
      date: '2024-07-05T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'ChemFH: An integrated tool for screening frequent false positives in
        chemical biology and drug discovery'
    note: High-throughput screening rapidly tests an extensive array of chemical compounds
      to identify hit compounds for specific biological targets in drug discovery.
      However, false-positive results disrupt hit compound screening, leading to wastage
      of time and resources. To address this, we propose ChemFH, an integrated online
      platform facilitating rapid virtual evaluation of potential false positives,
      including colloidal aggregators, spectroscopic interference compounds, firefly
      luciferase inhibitors, chemical reactive compounds, promiscuous compounds, and
      other assay interferences. ChemFH is freely available via https://chemfh.scbdd.com/.
    pmcid: PMC11223804
    pmid: '38783035'
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  toolType:
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  description: 'WorkflowHub is a registry for describing, sharing and publishing scientific
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    The registry supports any workflow in its native repository.


    WorkflowHub aims to facilitate discovery and re-use of workflows in an accessible
    and interoperable way. This is achieved through extensive use of open standards
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    TRS, in accordance with the FAIR principles.'
  documentation:
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    type:
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    operation:
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  language:
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  lastUpdate: '2025-03-28T09:56:03.670536Z'
  license: BSD-3-Clause
  link:
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    type:
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    url: https://about.workflowhub.eu/community/
  maturity: Emerging
  name: WorkflowHub
  operatingSystem:
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  owner: fbacall
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  - Web application
  topic:
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  validated: 0
  version: []
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  additionDate: '2025-03-25T09:59:44.309666Z'
  biotoolsCURIE: biotools:rocrate-validator
  biotoolsID: rocrate-validator
  collectionID: []
  confidence_flag: null
  cost: Free of charge
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    fundrefid: null
    gridid: null
    name: Marco Enrico Piras
    note: null
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    typeEntity: Person
    typeRole:
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    url: null
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    typeEntity: Person
    typeRole:
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    url: null
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  description: rocrate-validator is a tool and Python package to validate RO-Crates
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  documentation:
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    type:
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    - Command-line options
    - Installation instructions
    - Quick start guide
    url: https://rocrate-validator.readthedocs.io/
  download:
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    url: https://github.com/crs4/rocrate-validator/releases
    version: null
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  function:
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    note: Validate compliance of RO-Crate objects with specifications
    operation:
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    output: []
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  homepage_status: 0
  language:
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  topic:
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    * test monitoring and notification;

    * automated checks and templates for workflow best practices.'
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  relation:
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  topic:
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  - term: Workflows
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  - term: Open science
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  description: MatHeat transforms your gene expression data into stunning interactive
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  topic:
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  description: Predicting the impact of mutations on protein stability from sequence
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        mutations starting from protein sequence without relying on the structure.
        Here, we describe INPS, a novel approach for annotating the effect of non-synonymous
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  description: "BASICO, a simplified Python interface to COPASI. It provides a set\
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  publication:
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    metadata: null
    note: null
    pmcid: null
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    type: []
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    typeEntity: Division
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  description: Overture is a collection of open-source software used to create platforms
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    url: null
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  description: ENQUIRE (Expanding Networks by Querying Unexpectedly Inter-Related
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  - Python
  - R
  lastUpdate: '2025-02-12T11:17:06.811354Z'
  license: GPL-3.0
  link:
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    type:
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    url: https://github.com/Muszeb/ENQUIRE
  - note: SIF image (Apptainer/Singularity).
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  name: ENQUIRE
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  - term: Molecular interactions, pathways and networks
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  - term: Data mining
    uri: http://edamontology.org/topic_3473
  validated: 0
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  additionDate: '2023-12-20T08:57:24.041703Z'
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  - email: nils.paulhe@inrae.fr
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  description: Web portal to gather tools to improve metabolomic annotations through
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    note: Improve metabolite annotations.
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    metadata:
      abstract: Genome-scale metabolic models are of high interest in a number of
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        methods allow the prediction of the steady-state behavior of metabolic networks
        under different environmental conditions. However, many existing applications
        for flux optimizations do not provide a metabolite-centric view on fluxes.
        Metano is a standalone, open-source toolbox for the analysis and refinement
        of metabolic models. While flux distributions in metabolic networks are predominantly
        analyzed from a reaction-centric point of view, the Metano methods of split-ratio
        analysis and metabolite flux minimization also allow a metabolite-centric
        view on flux distributions. In addition, we present MMTB (mmtb.brendaenzymes.org),
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        models by integrating reaction and enzymatic annotation data from different
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        and offering novel visualizations. Additionally, MMTB allows users to upload
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        We introduce MMTB by two use cases, involving a published model of Corynebacterium
        glutamicum and a newly created model of Phaeobacter inhibens.
      authors:
      - name: Koblitz J.
      - name: Will S.E.
      - name: Riemer S.A.
      - name: Ulas T.
      - name: Neumann-Schaal M.
      - name: Schomburg D.
      citationCount: 2
      date: '2021-02-01T00:00:00Z'
      journal: Metabolites
      title: 'The metano modeling toolbox MMTB: An intuitive, web-based toolbox introduced
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    note: null
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  topic:
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  - term: Molecular interactions, pathways and networks
    uri: http://edamontology.org/topic_0602
  - term: Omics
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  validated: 0
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  additionDate: '2022-11-09T17:22:40.898557Z'
  biotoolsCURIE: biotools:mediadive
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  description: Comprehensive database on cultivation media and growth conditions for
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    - User manual
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    note: Medium Builder
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    note: SPARQL end point
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    metadata:
      abstract: We present MediaDive (https://mediadive.dsmz.de), a comprehensive
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        and molecular compositions of >3200 standardized cultivation media for >40
        000 microbial strains from all domains of life. MediaDive is designed to enable
        broad range applications from every-day-use in research and diagnostic laboratories
        to knowledge-driven support of new media design and artificial intelligence-driven
        data mining. It offers a number of intuitive search functions and comparison
        tools, for example to identify media for related taxonomic groups and to integrate
        strain-specific modifications. Besides classical PDF archiving and printing,
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        devices for convenient wet-lab use. In addition, data can be retrieved using
        a RESTful web service for large-scale data analyses. An internal editor interface
        ensures continuous extension and curation of media by cultivation experts
        from the Leibniz Institute DSMZ, which is interlinked with the growing microbial
        collections at DSMZ. External user engagement is covered by a dedicated media
        builder tool. The standardized and programmatically accessible data will foster
        new approaches for the design of cultivation media to target the vast majority
        of uncultured microorganisms.
      authors:
      - name: Koblitz J.
      - name: Halama P.
      - name: Spring S.
      - name: Thiel V.
      - name: Baschien C.
      - name: Hahnke R.L.
      - name: Pester M.
      - name: Overmann J.
      - name: Reimer L.C.
      citationCount: 22
      date: '2023-01-06T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'MediaDive: the expert-curated cultivation media database'
    note: null
    pmcid: null
    pmid: '36134710'
    type:
    - Primary
    version: null
  relation:
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  - term: Biochemistry
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  - term: Data curation and archival
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  - term: Experimental design and studies
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  - term: Laboratory information management
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  validated: 1
  version: []
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  - email: hub@dsmz.de
    fundrefid: null
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      GmbH
    note: null
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  description: SPARQL endpoint for the MediaDive cultivation media database.
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    note: null
    operation:
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        term: Database search results
        uri: http://edamontology.org/data_2080
      format:
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        uri: http://edamontology.org/format_2376
  homepage: https://sparql.dsmz.de/mediadive
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  name: MediaDive SPARQL
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  owner: JKoblitz
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  relation:
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    type: includes
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  topic:
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    uri: http://edamontology.org/topic_3292
  - term: FAIR data
    uri: http://edamontology.org/topic_4012
  validated: 0
  version: []
- accessibility: Open access
  additionDate: '2018-01-16T22:02:06Z'
  biotoolsCURIE: biotools:mmp
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  - Marine Metagenomics Portal
  confidence_flag: null
  cost: Free of charge
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    url: null
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    note: null
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    rorid: null
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    typeRole:
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    url: null
  description: The Marine Metagenomics Portal (MMP) hosts the marine databases MarRef,
    MarDB, MarFun, and SalDB. These databases provide the marine scientific community
    with openly accessible, comprehensive microbial genomics and metagenomics resources,
    including high-quality, manually curated sequences. The user-friendly web interface
    allows visitors to easily navigate and refine searches within the contextual databases
    and offers additional BLAST searches, visualizations, downloads, and workflows
    (via META-pipe).
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    type:
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    note: null
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    - term: Taxonomic classification
      uri: http://edamontology.org/operation_3460
    - term: Query and retrieval
      uri: http://edamontology.org/operation_0224
    - term: Sequence annotation
      uri: http://edamontology.org/operation_0361
    output: []
  homepage: https://sfb.mmp2.sigma2.no
  homepage_status: 0
  language: []
  lastUpdate: '2025-01-17T09:29:45.738020Z'
  license: CC-BY-ND-3.0
  link: []
  maturity: Mature
  name: Marine Metagenomics Portal
  operatingSystem:
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  - Windows
  - Mac
  otherID:
  - type: doi
    value: doi:10.25504/FAIRsharing.SnTbUa
    version: null
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  publication:
  - doi: 10.1093/nar/gkx1036
    metadata:
      abstract: We introduce the marine databases; MarRef, MarDB and MarCat (https://mmp.sfb.uit.no/databases/),
        which are publicly available resources that promote marine research and innovation.
        These data resources, which have been implemented in the Marine Metagenomics
        Portal (MMP) (https://mmp.sfb.uit.no/), are collections of richly annotated
        and manually curated contextual (metadata) and sequence databases representing
        three tiers of accuracy. While MarRef is a database for completely sequenced
        marine prokaryotic genomes, which represent a marine prokaryote reference
        genome database, MarDB includes all incomplete sequenced prokaryotic genomes
        regardless level of completeness. The last database, MarCat, represents a
        gene (protein) catalog of uncultivable (and cultivable) marine genes and proteins
        derived from marine metagenomics samples. The first versions of MarRef and
        MarDB contain 612 and 3726 records, respectively. Each record is built up
        of 106 metadata fields including attributes for sampling, sequencing, assembly
        and annotation in addition to the organism and taxonomic information. Currently,
        MarCat contains 1227 records with 55 metadata fields. Ontologies and controlled
        vocabularies are used in the contextual databases to enhance consistency.
        The user-friendly web interface lets the visitors browse, filter and search
        in the contextual databases and perform BLAST searches against the corresponding
        sequence databases. All contextual and sequence databases are freely accessible
        and downloadable from https://s1.sfb.uit.no/public/mar/.
      authors:
      - name: Klemetsen T.
      - name: Raknes I.A.
      - name: Fu J.
      - name: Agafonov A.
      - name: Balasundaram S.V.
      - name: Tartari G.
      - name: Robertsen E.
      - name: Willassen N.P.
      citationCount: 79
      date: '2018-01-01T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'The MAR databases: Development and implementation of databases specific
        for marine metagenomics'
    note: null
    pmcid: PMC5753341
    pmid: '29106641'
    type:
    - Primary
    version: null
  relation:
  - biotoolsID: marref
    type: includes
  - biotoolsID: mardb
    type: includes
  - biotoolsID: metapipe
    type: includes
  toolType:
  - Database portal
  topic:
  - term: Marine biology
    uri: http://edamontology.org/topic_3387
  - term: Metagenomics
    uri: http://edamontology.org/topic_3174
  - term: Genomics
    uri: http://edamontology.org/topic_0622
  - term: Bioinformatics
    uri: http://edamontology.org/topic_0091
  - term: Data integration and warehousing
    uri: http://edamontology.org/topic_3366
  - term: Data mining
    uri: http://edamontology.org/topic_3473
  - term: Microbial ecology
    uri: http://edamontology.org/topic_3697
  - term: Sequence analysis
    uri: http://edamontology.org/topic_0080
  - term: Taxonomy
    uri: http://edamontology.org/topic_0637
  - term: Function analysis
    uri: http://edamontology.org/topic_1775
  validated: 1
  version: []
- accessibility: null
  additionDate: '2020-03-19T13:08:18Z'
  biotoolsCURIE: biotools:marome
  biotoolsID: marome
  collectionID: []
  confidence_flag: null
  cost: null
  credit:
  - email: nitinnarwade1504@gmail.com
    fundrefid: null
    gridid: null
    name: Nitin Narwade
    note: null
    orcidid: https://orcid.org/0000-0002-1368-307X
    rorid: null
    typeEntity: Institute
    typeRole:
    - Developer
    url: http://bioinfo.net.in/
  description: 'MARome is a resource for annotation of Scaffold and Matrix Attachment
    Regions (S/MARs) in Human Genome such as associated genes, genomic region, associated
    S/MAR binding proteins, associated Retroviral Integration sites for HIV and HTLV
    (Source: RID) etc. MARome is interlinked to other genomic resources such as, UCSC
    Genome Browser (For visualization of S/MAR genomic location), ensemble, NCBI-Gene.'
  documentation:
  - note: null
    type:
    - User manual
    url: https://marome.bionivid.in/help
  download:
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    type: Biological data
    url: https://marome.bionivid.in/download
    version: null
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  lastUpdate: '2025-01-14T13:36:01.792295Z'
  license: null
  link: []
  maturity: null
  name: MARome
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  owner: nitinnarwade1504
  publication:
  - doi: 10.1093/nar/gkz562
    metadata:
      abstract: Scaffold/matrix attachment regions (S/MARs) are DNA elements that
        serve to compartmentalize the chromatin into structural and functional domains.
        These elements are involved in control of gene expression which governs the
        phenotype and also plays role in disease biology. Therefore, genome-wide understanding
        of these elements holds great therapeutic promise. Several attempts have been
        made toward identification of S/MARs in genomes of various organisms including
        human. However, a comprehensive genome-wide map of human S/MARs is yet not
        available. Toward this objective, ChIP-Seq data of 14 S/MAR binding proteins
        were analyzed and the binding site coordinates of these proteins were used
        to prepare a non-redundant S/MAR dataset of human genome. Along with co-ordinate
        (location) details of S/MARs, the dataset also revealed details of S/MAR features,
        namely, length, inter-SMAR length (the chromatin loop size), nucleotide repeats,
        motif abundance, chromosomal distribution and genomic context. S/MARs identified
        in present study and their subsequent analysis also suggests that these elements
        act as hotspots for integration of retroviruses. Therefore, these data will
        help toward better understanding of genome functioning and designing effective
        anti-viral therapeutics. In order to facilitate user friendly browsing and
        retrieval of the data obtained in present study, a web interface, MARome (http://bioinfo.net.in/MARome),
        has been developed.
      authors:
      - name: Narwade N.
      - name: Patel S.
      - name: Alam A.
      - name: Chattopadhyay S.
      - name: Mittal S.
      - name: Kulkarni A.
      citationCount: 28
      date: '2019-08-22T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'Mapping of scaffold/matrix attachment regions in human genome: a data
        mining exercise'
    note: null
    pmcid: PMC6698742
    pmid: '31265077'
    type:
    - Primary
    version: null
  relation: []
  toolType:
  - Web application
  topic:
  - term: Nucleic acids
    uri: http://edamontology.org/topic_0077
  validated: 1
  version: []
- accessibility: Open access
  additionDate: '2025-01-14T09:14:56.273060Z'
  biotoolsCURIE: biotools:phistruct
  biotoolsID: phistruct
  collectionID: []
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: gonzales.markedward@gmail.com
    fundrefid: null
    gridid: null
    name: Mark Edward M. Gonzales
    note: Research Assistant, Bioinformatics Lab, Advanced Research Institute for
      Informatics, Computing and Networking, De La Salle University, Manila, Philippines
    orcidid: https://orcid.org/0000-0001-5050-3157
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: https://github.com/memgonzales
  - email: jennifer.ureta@gmail.com
    fundrefid: null
    gridid: null
    name: Jennifer C. Ureta
    note: Faculty, Bioinformatics Lab, Advanced Research Institute for Informatics,
      Computing and Networking, De La Salle University, Manila, Philippines
    orcidid: https://orcid.org/0000-0003-0427-5311
    rorid: null
    typeEntity: Person
    typeRole:
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    url: https://scholar.google.com/citations?user=v0Tf_u4AAAAJ&hl=en
  - email: anish.shrestha@dlsu.edu.ph
    fundrefid: null
    gridid: null
    name: Anish M.S. Shrestha
    note: Head, Bioinformatics Lab, Advanced Research Institute for Informatics, Computing
      and Networking, De La Salle University, Manila, Philippines
    orcidid: https://orcid.org/0000-0002-9192-9709
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: https://a-transposable-element.com/
  description: "PHIStruct is a phage-host interaction prediction tool that uses structure-aware\
    \ protein embeddings to represent the receptor-binding proteins (RBPs) of phages.\
    \ \n\nBy incorporating structure information, it presents improvements over using\
    \ sequence-only protein embeddings and feature-engineered sequence properties\
    \ — especially for phages with RBPs that have low sequence similarity to those\
    \ of known phages."
  documentation:
  - note: null
    type:
    - Installation instructions
    - Quick start guide
    - Citation instructions
    - Command-line options
    url: https://github.com/bioinfodlsu/PHIStruct
  download:
  - note: null
    type: Source code
    url: https://github.com/bioinfodlsu/PHIStruct
    version: null
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  function:
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    input:
    - data:
        term: Protein structure
        uri: http://edamontology.org/data_1460
      format:
      - term: PDB
        uri: http://edamontology.org/format_1476
    note: Predicts the host genus of a phage given its receptor-binding protein sequences
    operation:
    - term: Prediction and recognition
      uri: http://edamontology.org/operation_2423
    output:
    - data:
        term: Report
        uri: http://edamontology.org/data_2048
      format:
      - term: CSV
        uri: http://edamontology.org/format_3752
  homepage: https://github.com/bioinfodlsu/PHIStruct
  homepage_status: 0
  language:
  - Python
  lastUpdate: '2025-01-14T09:14:56.275331Z'
  license: MIT
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/bioinfodlsu/PHIStruct
  - note: null
    type:
    - Service
    url: http://phistruct.bioinfodlsu.com/
  maturity: Emerging
  name: PHIStruct
  operatingSystem:
  - Mac
  - Linux
  - Windows
  otherID: []
  owner: memgonzales
  publication:
  - doi: 10.1093/bioinformatics/btaf016
    metadata: null
    note: null
    pmcid: null
    pmid: '39804673'
    type:
    - Primary
    version: null
  relation: []
  toolType:
  - Command-line tool
  topic:
  - term: Machine learning
    uri: http://edamontology.org/topic_3474
  - term: Protein structure analysis
    uri: http://edamontology.org/topic_2814
  - term: Proteins
    uri: http://edamontology.org/topic_0078
  - term: Proteomics
    uri: http://edamontology.org/topic_0121
  - term: Computational biology
    uri: http://edamontology.org/topic_3307
  - term: Bioinformatics
    uri: http://edamontology.org/topic_0091
  - term: Virology
    uri: http://edamontology.org/topic_0781
  validated: 0
  version: []
- accessibility: Open access
  additionDate: '2024-05-05T10:53:14.688391Z'
  biotoolsCURIE: biotools:phiembed
  biotoolsID: phiembed
  collectionID: []
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: gonzales.markedward@gmail.com
    fundrefid: null
    gridid: null
    name: Mark Edward M. Gonzales
    note: Research Assistant, Bioinformatics Lab, Advanced Research Institute for
      Informatics, Computing and Networking, De La Salle University, Manila, Philippines
    orcidid: https://orcid.org/0000-0001-5050-3157
    rorid: null
    typeEntity: Person
    typeRole:
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    url: https://github.com/memgonzales
  - email: jennifer.ureta@gmail.com
    fundrefid: null
    gridid: null
    name: Jennifer C. Ureta
    note: Faculty, Bioinformatics Lab, Advanced Research Institute for Informatics,
      Computing and Networking, De La Salle University, Manila, Philippines
    orcidid: https://orcid.org/0000-0003-0427-5311
    rorid: null
    typeEntity: Person
    typeRole:
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    url: https://scholar.google.com/citations?user=v0Tf_u4AAAAJ&hl=en
  - email: anish.shrestha@dlsu.edu.ph
    fundrefid: null
    gridid: null
    name: Anish M.S. Shrestha
    note: Head, Bioinformatics Lab, Advanced Research Institute for Informatics, Computing
      and Networking, De La Salle University, Manila, Philippines
    orcidid: https://orcid.org/0000-0002-9192-9709
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: https://a-transposable-element.com/
  description: PHIEmbed is a phage-host interaction prediction tool that uses protein
    language models to represent the receptor-binding proteins of phages. It presents
    improvements over using handcrafted (manually feature-engineered) sequence properties
    and eliminates the need to manually extract and select features from phage sequences.
  documentation:
  - note: null
    type:
    - Installation instructions
    - Quick start guide
    - Citation instructions
    - Command-line options
    url: https://github.com/bioinfodlsu/phage-host-prediction
  download:
  - note: null
    type: Source code
    url: https://github.com/bioinfodlsu/phage-host-prediction
    version: null
  editPermission:
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  function:
  - cmd: null
    input:
    - data:
        term: Protein sequence
        uri: http://edamontology.org/data_2976
      format:
      - term: FASTA
        uri: http://edamontology.org/format_1929
    note: Predicts the host genus of a phage given its receptor-binding protein sequences
    operation:
    - term: Prediction and recognition
      uri: http://edamontology.org/operation_2423
    output:
    - data:
        term: Report
        uri: http://edamontology.org/data_2048
      format:
      - term: CSV
        uri: http://edamontology.org/format_3752
  homepage: https://github.com/bioinfodlsu/phage-host-prediction
  homepage_status: 0
  language:
  - Python
  lastUpdate: '2025-01-14T09:13:55.932761Z'
  license: MIT
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/bioinfodlsu/phage-host-prediction
  - note: null
    type:
    - Service
    url: http://phiembed.bioinfodlsu.com/
  maturity: Emerging
  name: PHIEmbed
  operatingSystem:
  - Mac
  - Linux
  - Windows
  otherID: []
  owner: memgonzales
  publication:
  - doi: 10.1371/journal.pone.0289030
    metadata:
      abstract: With the growing interest in using phages to combat antimicrobial
        resistance, computational methods for predicting phage-host interactions have
        been explored to help shortlist candidate phages. Most existing models consider
        entire proteomes and rely on manual feature engineering, which poses difficulty
        in selecting the most informative sequence properties to serve as input to
        the model. In this paper, we framed phage-host interaction prediction as a
        multiclass classification problem that takes as input the embeddings of a
        phage’s receptor-binding proteins, which are known to be the key machinery
        for host recognition, and predicts the host genus. We explored different protein
        language models to automatically encode these protein sequences into dense
        embeddings without the need for additional alignment or structural information.
        We show that the use of embeddings of receptor-binding proteins presents improvements
        over handcrafted genomic and protein sequence features. The highest performance
        was obtained using the transformer-based protein language model ProtT5, resulting
        in a 3% to 4% increase in weighted F1 and recall scores across different prediction
        confidence thresholds, compared to using selected handcrafted sequence features.
      authors:
      - name: Gonzales M.E.M.
      - name: Ureta J.C.
      - name: Shrestha A.M.S.
      citationCount: 2
      date: '2023-07-01T00:00:00Z'
      journal: PLoS ONE
      title: Protein embeddings improve phage-host interaction prediction
    note: null
    pmcid: null
    pmid: '37486915'
    type:
    - Primary
    version: null
  relation: []
  toolType:
  - Command-line tool
  topic:
  - term: Machine learning
    uri: http://edamontology.org/topic_3474
  - term: Sequence analysis
    uri: http://edamontology.org/topic_0080
  - term: Proteins
    uri: http://edamontology.org/topic_0078
  - term: Proteomics
    uri: http://edamontology.org/topic_0121
  - term: Computational biology
    uri: http://edamontology.org/topic_3307
  - term: Bioinformatics
    uri: http://edamontology.org/topic_0091
  - term: Virology
    uri: http://edamontology.org/topic_0781
  validated: 0
  version: []
- accessibility: null
  additionDate: '2023-08-29T21:12:45.977710Z'
  biotoolsCURIE: biotools:sdm2
  biotoolsID: sdm2
  collectionID:
  - 3D-BioInfo
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: app41@cam.ac.uk
    fundrefid: null
    gridid: null
    name: ARUN PRASAD PANDURANGAN
    note: Computational Biologist at the University of Cambridge
    orcidid: https://orcid.org/0000-0001-7168-7143
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    - Primary contact
    - Maintainer
    url: https://www.infectiousdisease.cam.ac.uk/directory/apandura%40mrc-lmb.cam.ac.uk
  description: A server for predicting effects of mutations on protein stability
  documentation:
  - note: null
    type:
    - Quick start guide
    url: https://compbio.medschl.cam.ac.uk/sdm2/help
  download: []
  editPermission:
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    type: private
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  - 3D-BioInfo
  elixirNode:
  - UK
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  - Tools
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Variant effect prediction
      uri: http://edamontology.org/operation_0331
    output: []
  homepage: https://compbio.medschl.cam.ac.uk/sdm2/
  homepage_status: 0
  language: []
  lastUpdate: '2025-01-08T14:32:09.070558Z'
  license: null
  link: []
  maturity: null
  name: SDM
  operatingSystem:
  - Linux
  otherID: []
  owner: apandura
  publication:
  - doi: 10.1093/nar/gkx439
    metadata:
      abstract: Here, we report a webserver for the improved SDM, used for predicting
        the effects of mutations on protein stability. As a pioneering knowledge-based
        approach, SDM has been highlighted as the most appropriate method to use in
        combination with many other approaches. We have updated the environment-specific
        amino-acid substitution tables based on the current expanded PDB (a 5-fold
        increase in information), and introduced new residue-conformation and interaction
        parameters, including packing density and residue depth. The updated server
        has been extensively tested using a benchmark containing 2690 point mutations
        from 132 different protein structures. The revised method correlates well
        against the hypothetical reverse mutations, better than comparable methods
        built using machine-learning approaches, highlighting the strength of our
        knowledge-based approach for identifying stabilising mutations. Given a PDB
        file (a Protein Data Bank file format containing the 3D coordinates of the
        protein atoms), and a point mutation, the server calculates the stability
        difference score between the wildtype and mutant protein.
      authors:
      - name: Pandurangan A.P.
      - name: Ochoa-Montano B.
      - name: Ascher D.B.
      - name: Blundell T.L.
      citationCount: 374
      date: '2017-07-03T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'SDM: A server for predicting effects of mutations on protein stability'
    note: 'SDM: a server for predicting effects of mutations on protein stability'
    pmcid: PMC5793720
    pmid: '28525590'
    type:
    - Method
    version: '2.0'
  relation:
  - biotoolsID: sdm
    type: isNewVersionOf
  toolType: []
  topic: []
  validated: 0
  version:
  - '2.0'
- accessibility: Open access
  additionDate: '2021-05-08T17:25:21Z'
  biotoolsCURIE: biotools:bakta
  biotoolsID: bakta
  collectionID: []
  confidence_flag: tool
  cost: Free of charge
  credit:
  - email: oliver.schwengers@cb.jlug.de
    fundrefid: null
    gridid: null
    name: Oliver Schwengers
    note: null
    orcidid: https://orcid.org/0000-0003-4216-2721
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    - Developer
    - Maintainer
    url: https://github.com/oschwengers
  - email: null
    fundrefid: null
    gridid: null
    name: Justus Liebig University Giessen
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
    - Provider
    url: https://www.uni-giessen.de
  description: Rapid & standardized annotation of bacterial genomes, MAGs & plasmids
  documentation:
  - note: null
    type:
    - General
    url: https://github.com/oschwengers/bakta/blob/main/README.md
  - note: null
    type:
    - Contributions policy
    url: https://github.com/oschwengers/bakta/blob/main/CONTRIBUTION.md
  - note: null
    type:
    - Code of conduct
    url: https://github.com/oschwengers/bakta/blob/main/CODE_OF_CONDUCT.md
  - note: null
    type:
    - User manual
    url: https://bakta.readthedocs.io/
  download:
  - note: Mandatory annotation database
    type: Other
    url: https://zenodo.org/records/7669534
    version: v5.1
  editPermission:
    authors:
    - ELIXIR-CZ
    - bebatut
    type: group
  elixirCommunity: []
  elixirNode:
  - Germany
  elixirPlatform:
  - Tools
  elixir_badge: 0
  function:
  - cmd: bakta --db <db-path> --prefix <prefix> --output <output-path> genome.fasta
    input:
    - data:
        term: Sequence assembly
        uri: http://edamontology.org/data_0925
      format:
      - term: FASTA
        uri: http://edamontology.org/format_1929
    - data:
        term: Sequence features metadata
        uri: http://edamontology.org/data_2914
      format:
      - term: TSV
        uri: http://edamontology.org/format_3475
    - data:
        term: Sequence coordinates
        uri: http://edamontology.org/data_2012
      format:
      - term: GFF3
        uri: http://edamontology.org/format_1975
    - data:
        term: Protein sequence record
        uri: http://edamontology.org/data_2886
      format:
      - term: FASTA
        uri: http://edamontology.org/format_1929
    - data:
        term: Hidden Markov model
        uri: http://edamontology.org/data_1364
      format:
      - term: HMMER3
        uri: http://edamontology.org/format_3329
    note: null
    operation:
    - term: Genome annotation
      uri: http://edamontology.org/operation_0362
    output:
    - data:
        term: Feature table
        uri: http://edamontology.org/data_1270
      format:
      - term: GenBank format
        uri: http://edamontology.org/format_1936
      - term: EMBL format
        uri: http://edamontology.org/format_1927
      - term: GFF3
        uri: http://edamontology.org/format_1975
      - term: JSON
        uri: http://edamontology.org/format_3464
      - term: TSV
        uri: http://edamontology.org/format_3475
    - data:
        term: Protein sequence record
        uri: http://edamontology.org/data_2886
      format:
      - term: FASTA
        uri: http://edamontology.org/format_1929
    - data:
        term: Nucleic acid sequence record
        uri: http://edamontology.org/data_2887
      format:
      - term: FASTA
        uri: http://edamontology.org/format_1929
    - data:
        term: Plot
        uri: http://edamontology.org/data_2884
      format:
      - term: PNG
        uri: http://edamontology.org/format_3603
      - term: SVG
        uri: http://edamontology.org/format_3604
    - data:
        term: Score
        uri: http://edamontology.org/data_1772
      format:
      - term: TSV
        uri: http://edamontology.org/format_3475
  homepage: https://github.com/oschwengers/bakta
  homepage_status: 0
  language:
  - Python
  lastUpdate: '2024-12-23T21:48:50.049892Z'
  license: GPL-3.0
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/oschwengers/bakta
  - note: null
    type:
    - Issue tracker
    url: https://github.com/oschwengers/bakta/issues
  - note: null
    type:
    - Other
    url: https://bioconda.github.io/recipes/bakta/README.html
  - note: null
    type:
    - Service
    url: https://bakta.computational.bio
  maturity: Mature
  name: Bakta
  operatingSystem:
  - Linux
  - Mac
  otherID: []
  owner: oschwengers
  publication:
  - doi: 10.1099/mgen.0.000685
    metadata:
      abstract: Command-line annotation software tools have continuously gained popularity
        compared to centralized online services due to the worldwide increase of sequenced
        bacterial genomes. However, results of existing command-line software pipelines
        heavily depend on taxon-specific databases or sufficiently well annotated
        reference genomes. Here, we introduce Bakta, a new command-line software tool
        for the robust, taxon-independent, thorough and, nonetheless, fast annotation
        of bacterial genomes. Bakta conducts a comprehensive annotation workflow including
        the detection of small proteins taking into account replicon metadata. The
        annotation of coding sequences is accelerated via an alignment-free sequence
        identification approach that in addition facilitates the precise assignment
        of public database cross-references. Annotation results are exported in GFF3
        and International Nucleotide Sequence Database Collaboration (INSDC)-compliant
        flat files, as well as comprehensive JSON files, facilitating automated downstream
        analysis. We compared Bakta to other rapid contemporary command-line annotation
        software tools in both targeted and taxonomically broad benchmarks including
        isolates and metagenomic-assembled genomes. We demonstrated that Bakta outperforms
        other tools in terms of functional annotations, the assignment of functional
        categories and database cross-references, whilst providing comparable wall-clock
        runtimes. Bakta is implemented in Python 3 and runs on MacOS and Linux systems.
        It is freely available under a GPLv3 license at https://​github.​com/​oschwengers/​bakta.
        An accompanying web version is available at https://​bakta.​computational.​bio.
      authors:
      - name: Schwengers O.
      - name: Jelonek L.
      - name: Dieckmann M.A.
      - name: Beyvers S.
      - name: Blom J.
      - name: Goesmann A.
      citationCount: 323
      date: '2021-01-01T00:00:00Z'
      journal: Microbial Genomics
      title: 'Bakta: Rapid and standardized annotation of bacterial genomes via alignment-free
        sequence identification'
    note: null
    pmcid: PMC8743544
    pmid: '34739369'
    type:
    - Primary
    version: '1.1'
  relation:
  - biotoolsID: diamond
    type: uses
  - biotoolsID: hmmer3
    type: uses
  - biotoolsID: infernal
    type: uses
  - biotoolsID: trnascan-se
    type: uses
  - biotoolsID: blast
    type: uses
  - biotoolsID: aragorn
    type: uses
  - biotoolsID: pilercr
    type: uses
  - biotoolsID: deepsig
    type: uses
  toolType:
  - Command-line tool
  - Web application
  topic:
  - term: Genomics
    uri: http://edamontology.org/topic_0622
  - term: Sequence analysis
    uri: http://edamontology.org/topic_0080
  - term: Bioinformatics
    uri: http://edamontology.org/topic_0091
  validated: 0
  version:
  - v1.10.3
- accessibility: null
  additionDate: '2016-10-05T07:15:57Z'
  biotoolsCURIE: biotools:eurisco
  biotoolsID: eurisco
  collectionID: []
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: null
    fundrefid: null
    gridid: null
    name: European Cooperative Programme for Plant Genetic Resources (ECPGR)
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
    - Provider
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
    - Provider
    url: null
  - email: weise@ipk-gatersleben.de
    fundrefid: null
    gridid: null
    name: Stephan Weise
    note: null
    orcidid: http://orcid.org/0000-0003-4031-9131
    rorid: null
    typeEntity: null
    typeRole:
    - Developer
    url: null
  - email: weise@ipk-gatersleben.de
    fundrefid: null
    gridid: null
    name: Stephan Weise
    note: null
    orcidid: http://orcid.org/0000-0003-4031-9131
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  description: Search catalogue providing information about plant genetic resources
    collections maintained in Europe. It is based on a European network of ex situ
    and in situ National Inventories (NIs). Currently, it comprises information about
    2.1 million germplasm accessions from more than 400 holding institutions from
    43 countries. It contains both passport data and phenotypic data.
  documentation:
  - note: null
    type:
    - Terms of use
    - Citation instructions
    - General
    url: http://eurisco.ecpgr.org/
  download: []
  editPermission:
    authors: []
    type: private
  elixirCommunity:
  - Plant Sciences
  elixirNode:
  - Germany
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Keyword
        uri: http://edamontology.org/data_0968
      format:
      - term: Textual format
        uri: http://edamontology.org/format_2330
    note: Based on the Multi Crop Passport Descriptors (MCPD) format
    operation:
    - term: Database search
      uri: http://edamontology.org/operation_2421
    output:
    - data:
        term: Database search results
        uri: http://edamontology.org/data_2080
      format:
      - term: HTML
        uri: http://edamontology.org/format_2331
  homepage: http://eurisco.ecpgr.org
  homepage_status: 0
  language:
  - SQL
  lastUpdate: '2024-12-18T16:46:20.716446Z'
  license: null
  link:
  - note: null
    type:
    - Repository
    url: http://eurisco.ecpgr.org/
  maturity: Mature
  name: EURISCO
  operatingSystem:
  - Linux
  otherID: []
  owner: ipk
  publication:
  - doi: 10.1093/nar/gkw755
    metadata:
      abstract: The European Search Catalogue for Plant Genetic Resources, EURISCO,
        provides information about 1.8 million crop plant accessions preserved by
        almost 400 institutes in Europe and beyond. EURISCO is being maintained on
        behalf of the European Cooperative Programme for Plant Genetic Resources.
        It is based on a network of National Inventories of 43 member countries and
        represents an important effort for the preservation of world's agrobiological
        diversity by providing information about the large genetic diversity kept
        by the collaborating collections. Moreover, EURISCO also assists its member
        countries in fulfilling legal obligations and commitments, e.g. with respect
        to the International Treaty on Plant Genetic Resources, the Second Global
        Plan of Action for Plant Genetic Resources for Food and Agriculture of the
        United Nation's Food and Agriculture Organization, or the Convention on Biological
        Diversity. EURISCO is accessible at http://eurisco.ecpgr.org.
      authors:
      - name: Weise S.
      - name: Oppermann M.
      - name: Maggioni L.
      - name: Van Hintum T.
      - name: Knupffer H.
      citationCount: 47
      date: '2017-01-01T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'EURISCO: The European search catalogue for plant genetic resources'
    note: null
    pmcid: PMC5210606
    pmid: '27580718'
    type:
    - Primary
    version: null
  - doi: 10.1093/nar/gkac852
    metadata:
      abstract: The European Search Catalogue for Plant Genetic Resources (EURISCO)
        is a central entry point for information on crop plant germplasm accessions
        from institutions in Europe and beyond. In total, it provides data on more
        than two million accessions, making an important contribution to unlocking
        the vast genetic diversity that lies deposited in >400 germplasm collections
        in 43 countries. EURISCO serves as the reference system for the Plant Genetic
        Resources Strategy for Europe and represents a significant approach for documenting
        and making available the world's agrobiological diversity. EURISCO is well
        established as a resource in this field and forms the basis for a wide range
        of research projects. In this paper, we present current developments of EURISCO,
        which is accessible at http://eurisco.ecpgr.org.
      authors:
      - name: Kotni P.
      - name: Van Hintum T.
      - name: Maggioni L.
      - name: Oppermann M.
      - name: Weise S.
      citationCount: 6
      date: '2023-01-06T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'EURISCO update 2023: the European Search Catalogue for Plant Genetic
        Resources, a pillar for documentation of genebank material'
    note: null
    pmcid: PMC9825528
    pmid: '36189883'
    type:
    - Primary
    version: null
  relation: []
  toolType:
  - Web application
  topic:
  - term: Data management
    uri: http://edamontology.org/topic_3071
  validated: 1
  version:
  - 2.1.1
- accessibility: Open access
  additionDate: '2024-12-13T14:30:56.437646Z'
  biotoolsCURIE: biotools:orchamp
  biotoolsID: orchamp
  collectionID: []
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: julien.renaud@univ-grenoble-alpes.fr
    fundrefid: null
    gridid: null
    name: Julien Renaud
    note: null
    orcidid: https://orcid.org/0000-0001-5991-4657
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    - Maintainer
    - Support
    url: null
  - email: wilfried.thuiller@univ-grenoble-alpes.fr
    fundrefid: null
    gridid: null
    name: Wilfried Thuiller
    note: null
    orcidid: https://orcid.org/0000-0002-5388-5274
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  - email: amelie.saillard@univ-grenoble-alpes.fr
    fundrefid: null
    gridid: null
    name: Amélie Saillard
    note: null
    orcidid: https://orcid.org/0000-0002-7777-8211
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  description: API to download the datasets collected by the program
  documentation: []
  download:
  - note: REST service
    type: Downloads page
    url: https://orchamp.osug.fr/api/general
    version: null
  editPermission:
    authors: []
    type: private
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Biodiversity data
        uri: http://edamontology.org/data_3707
      format: []
    note: null
    operation:
    - term: Query and retrieval
      uri: http://edamontology.org/operation_0224
    output:
    - data:
        term: Biodiversity data
        uri: http://edamontology.org/data_3707
      format:
      - term: JSON
        uri: http://edamontology.org/format_3464
  homepage: https://orchamp.osug.fr/
  homepage_status: 0
  language:
  - PHP
  - SQL
  lastUpdate: '2024-12-13T15:09:14.424622Z'
  license: Freeware
  link: []
  maturity: Mature
  name: orchamp
  operatingSystem: []
  otherID: []
  owner: renaudj
  publication:
  - doi: 10.5802/crbiol.165
    metadata: null
    note: null
    pmcid: null
    pmid: null
    type:
    - Usage
    version: null
  relation: []
  toolType:
  - Web API
  topic:
  - term: Plant biology
    uri: http://edamontology.org/topic_0780
  - term: Ecology
    uri: http://edamontology.org/topic_0610
  - term: Metabarcoding
    uri: http://edamontology.org/topic_4038
  validated: 0
  version: []
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