count: 392
list:
- accessibility: Open access
  additionDate: '2025-04-29T17:07:56.642694Z'
  biotoolsCURIE: biotools:biosurfdb
  biotoolsID: biosurfdb
  collectionID: []
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  cost: Free of charge
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    fundrefid: null
    gridid: null
    name: Jorge S. Oliveira
    note: null
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    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: https://web.tecnico.ulisboa.pt/jorge.oliveira/
  - email: ana.freitas@tecnico.ulisboa.pt
    fundrefid: null
    gridid: null
    name: Ana Teresa Freitas
    note: null
    orcidid: http://orcid.org/0000-0003-4638-2879
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  - email: atrv@lncc.br
    fundrefid: null
    gridid: null
    name: Ana Tereza Ribeiro de Vasconcelos
    note: null
    orcidid: http://orcid.org/0000-0002-4632-2086
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  - email: lucymara.agnez@ufrn.br
    fundrefid: null
    gridid: null
    name: Lucymara Fassarella Agnez-Lima
    note: null
    orcidid: http://orcid.org/0000-0003-0642-3162
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  - email: gpo@biodata.pt
    fundrefid: null
    gridid: null
    name: Gil Poiares-Oliveira
    note: null
    orcidid: https://orcid.org/0000-0003-4638-2879
    rorid: null
    typeEntity: Person
    typeRole:
    - Maintainer
    url: https://web.tecnico.ulisboa.pt/gil.oliveira
  description: BioSurfDB is a online database for biodegradation and biosurfactants.
  documentation: []
  download: []
  editPermission:
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    type: group
  elixirCommunity: []
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  function:
  - cmd: null
    input:
    - data:
        term: DNA sequence
        uri: http://edamontology.org/data_3494
      format: []
    - data:
        term: Protein sequence record
        uri: http://edamontology.org/data_2886
      format: []
    note: null
    operation:
    - term: Local alignment
      uri: http://edamontology.org/operation_0495
    output:
    - data:
        term: Nucleic acid sequence alignment
        uri: http://edamontology.org/data_1383
      format: []
    - data:
        term: Hybrid sequence alignment
        uri: http://edamontology.org/data_1385
      format: []
  - cmd: null
    input: []
    note: null
    operation:
    - term: Sequence database search (by property)
      uri: http://edamontology.org/operation_0349
    output:
    - data:
        term: Gene symbol
        uri: http://edamontology.org/data_1026
      format: []
    - data:
        term: Gene ID (NCBI)
        uri: http://edamontology.org/data_1027
      format: []
    - data:
        term: Gene name
        uri: http://edamontology.org/data_2299
      format: []
    - data:
        term: DNA sequence
        uri: http://edamontology.org/data_3494
      format: []
  homepage: https://www.biosurfdb.org
  homepage_status: 0
  language: []
  lastUpdate: '2025-04-29T17:35:41.655075Z'
  license: null
  link: []
  maturity: Mature
  name: BioSurfDB
  operatingSystem: []
  otherID: []
  owner: ELIXIR-PT
  publication:
  - doi: 10.1093/database/bav033
    metadata:
      abstract: 'Crude oil extraction, transportation and use provoke the contamination
        of countless ecosystems. Therefore, bioremediation through surfactants mobilization
        or biodegradation is an important subject, both economically and environmentally.
        Bioremediation research had a great boost with the recent advances in Metagenomics,
        as it enabled the sequencing of uncultured microorganisms providing new insights
        on surfactant-producing and/or oil-degrading bacteria. Many research studies
        are making available genomic data from unknown organisms obtained from metagenomics
        analysis of oil-contaminated environmental samples. These new datasets are
        presently demanding the development of new tools and data repositories tailored
        for the biological analysis in a context of bioremediation data analysis.
        This work presents BioSurfDB, www.biosurfdb.org, a curated relational information
        system integrating data from: (i) metagenomes; (ii) organisms; (iii) biodegradation
        relevant genes; proteins and their metabolic pathways; (iv) bioremediation
        experiments results, with specific pollutants treatment efficiencies by surfactant
        producing organisms; and (v) a biosurfactant-curated list, grouped by producing
        organism, surfactant name, class and reference. The main goal of this repository
        is to gather information on the characterization of biological compounds and
        mechanisms involved in biosurfactant production and/or biodegradation and
        make it available in a curated way and associated with a number of computational
        tools to support studies of genomic and metagenomic data.'
      authors:
      - name: Oliveira J.S.
      - name: Araujo W.
      - name: Sales A.I.L.
      - name: De Brito Guerra A.
      - name: Da Silva Araujo S.C.
      - name: De Vasconcelos A.T.R.
      - name: Agnez-Lima L.F.
      - name: Freitas A.T.
      citationCount: 30
      date: '2015-01-01T00:00:00Z'
      journal: Database
      title: 'BioSurfDB: Knowledge and algorithms to support biosurfactants and biodegradation
        studies'
    note: null
    pmcid: null
    pmid: null
    type:
    - Primary
    version: null
  relation: []
  toolType:
  - Database portal
  topic:
  - term: Biotechnology
    uri: http://edamontology.org/topic_3297
  - term: Microbiology
    uri: http://edamontology.org/topic_3301
  - term: Enzymes
    uri: http://edamontology.org/topic_0821
  validated: 0
  version: []
- accessibility: Open access
  additionDate: '2025-02-28T15:04:33.594183Z'
  biotoolsCURIE: biotools:prolfquapp
  biotoolsID: prolfquapp
  collectionID: []
  confidence_flag: null
  cost: Free of charge
  credit: []
  description: A command-line tool for differential expression analysis in quantitative
    proteomics
  documentation:
  - note: null
    type:
    - General
    url: https://github.com/prolfqua/prolfquapp/blob/master/README.md
  download:
  - note: null
    type: Downloads page
    url: https://github.com/prolfqua/prolfquapp/releases/tag/0.1.6
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  - cmd: './prolfqua_dea.sh -i data_dir/ -d annotation.xlsx -y config.yaml -w NameOfAnalysis
      -s DIANN

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

      # ./prolfquapp_docker.sh prolfqua_dea.sh -i data_dir/ -d annotation.xlsx -y
      config.yaml -w NameOfAnalysis -s DIANN'
    input:
    - data:
        term: Expression data
        uri: http://edamontology.org/data_2603
      format:
      - term: CSV
        uri: http://edamontology.org/format_3752
      - term: TSV
        uri: http://edamontology.org/format_3475
    - data:
        term: Sequence
        uri: http://edamontology.org/data_2044
      format:
      - term: FASTA
        uri: http://edamontology.org/format_1929
    note: null
    operation:
    - term: Differential protein expression profiling
      uri: http://edamontology.org/operation_3741
    output:
    - data:
        term: Expression data
        uri: http://edamontology.org/data_2603
      format:
      - term: xlsx
        uri: http://edamontology.org/format_3620
      - term: HTML
        uri: http://edamontology.org/format_2331
  - cmd: null
    input:
    - data:
        term: Expression data
        uri: http://edamontology.org/data_2603
      format:
      - term: xlsx
        uri: http://edamontology.org/format_3620
    note: null
    operation:
    - term: Validation
      uri: http://edamontology.org/operation_2428
    output:
    - data:
        term: Quality control report
        uri: http://edamontology.org/data_3914
      format:
      - term: HTML
        uri: http://edamontology.org/format_2331
  - cmd: null
    input:
    - data:
        term: Expression data
        uri: http://edamontology.org/data_2603
      format:
      - term: CSV
        uri: http://edamontology.org/format_3752
      - term: TSV
        uri: http://edamontology.org/format_3475
    - data:
        term: Protein sequence
        uri: http://edamontology.org/data_2976
      format:
      - term: FASTA
        uri: http://edamontology.org/format_1929
    note: null
    operation:
    - term: Expression data visualisation
      uri: http://edamontology.org/operation_0571
    output:
    - data:
        term: Expression data
        uri: http://edamontology.org/data_2603
      format:
      - term: PDF
        uri: http://edamontology.org/format_3508
      - term: HTML
        uri: http://edamontology.org/format_2331
  homepage: https://github.com/prolfqua/prolfquapp
  homepage_status: 0
  language:
  - R
  lastUpdate: '2025-03-28T10:18:25.715685Z'
  license: MIT
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/prolfqua/prolfquapp
  - note: null
    type:
    - Issue tracker
    url: https://github.com/prolfqua/prolfquapp/issues
  maturity: Emerging
  name: prolfquapp
  operatingSystem:
  - Mac
  - Linux
  otherID: []
  owner: n.m.palmblad@lumc.nl
  publication:
  - doi: 10.1021/acs.jproteome.4c00911
    metadata:
      abstract: Mass spectrometry is a cornerstone of quantitative proteomics, enabling
        relative protein quantification and differential expression analysis (DEA)
        of proteins. As experiments grow in complexity, involving more samples, groups,
        and identified proteins, interactive differential expression analysis tools
        become impractical. The prolfquapp addresses this challenge by providing a
        command-line interface that simplifies DEA, making it accessible to nonprogrammers
        and seamlessly integrating it into workflow management systems. Prolfquapp
        streamlines data processing and result visualization by generating dynamic
        HTML reports that facilitate the exploration of differential expression results.
        These reports allow for investigating complex experiments, such as those involving
        repeated measurements or multiple explanatory variables. Additionally, prolfquapp
        supports various output formats, including XLSX files, SummarizedExperiment
        objects and rank files, for further interactive analysis using spreadsheet
        software, the exploreDE Shiny application, or gene set enrichment analysis
        software, respectively. By leveraging advanced statistical models from the
        prolfqua R package, prolfquapp offers a user-friendly, integrated solution
        for large-scale quantitative proteomics studies, combining efficient data
        processing with insightful, publication-ready outputs.
      authors:
      - name: Wolski W.E.
      - name: Grossmann J.
      - name: Schwarz L.
      - name: Leary P.
      - name: Turker C.
      - name: Nanni P.
      - name: Schlapbach R.
      - name: Panse C.
      citationCount: 0
      date: '2025-02-07T00:00:00Z'
      journal: Journal of Proteome Research
      title: prolfquapp ─ A User-Friendly Command-Line Tool Simplifying Differential
        Expression Analysis in Quantitative Proteomics
    note: null
    pmcid: null
    pmid: null
    type: []
    version: 0.0.6
  relation: []
  toolType:
  - Command-line tool
  topic:
  - term: Proteomics
    uri: http://edamontology.org/topic_0121
  validated: 0
  version:
  - 0.1.6
- accessibility: Open access
  additionDate: '2016-05-04T15:36:53Z'
  biotoolsCURIE: biotools:inps-md
  biotoolsID: inps-md
  collectionID: []
  confidence_flag: null
  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: https://www.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
    url: null
  - email: piero.fariselli@unito.it
    fundrefid: null
    gridid: null
    name: Piero Fariselli
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  - email: savojard@biocomp.unibo.it
    fundrefid: null
    gridid: null
    name: Castrense Savojardo
    note: null
    orcidid: https://orcid.org/0000-0002-7359-0633
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: http://biocomp.unibo.it/savojard/
  description: Predicting the impact of mutations on protein stability from sequence
    and structure.
  documentation:
  - note: null
    type:
    - General
    url: https://inpsmd.biocomp.unibo.it/help
  download: []
  editPermission:
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    - ELIXIR-ITA-BOLOGNA
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  - Italy
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  - Tools
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  function:
  - cmd: null
    input:
    - data:
        term: Protein sequence (raw)
        uri: http://edamontology.org/data_2974
      format: []
    - data:
        term: Sequence variations
        uri: http://edamontology.org/data_3498
      format: []
    note: Prediction of the impact of non-synonymous polymorphisms on protein stability
      from sequence.
    operation: []
    output:
    - data:
        term: Protein report
        uri: http://edamontology.org/data_0896
      format: []
  - cmd: null
    input:
    - data:
        term: Protein structure
        uri: http://edamontology.org/data_1460
      format: []
    - data:
        term: Polypeptide chain ID
        uri: http://edamontology.org/data_1008
      format: []
    - data:
        term: Sequence variations
        uri: http://edamontology.org/data_3498
      format: []
    note: Prediction of the impact of non-synonymous polymorphisms on protein stability
      from structure.
    operation: []
    output:
    - data:
        term: Protein report
        uri: http://edamontology.org/data_0896
      format: []
    - data:
        term: Protein structure
        uri: http://edamontology.org/data_1460
      format: []
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  homepage_status: 0
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  license: null
  link: []
  maturity: Mature
  name: INPS-MD
  operatingSystem: []
  otherID: []
  owner: ELIXIR-ITA-BOLOGNA
  publication:
  - doi: 10.1093/bioinformatics/btv291
    metadata:
      abstract: 'Motivation: A tool for reliably predicting the impact of variations
        on protein stability is extremely important for both protein engineering and
        for understanding the effects of Mendelian and somatic mutations in the genome.
        Next Generation Sequencing studies are constantly increasing the number of
        protein sequences. Given the huge disproportion between protein sequences
        and structures, there is a need for tools suited to annotate the effect of
        mutations starting from protein sequence without relying on the structure.
        Here, we describe INPS, a novel approach for annotating the effect of non-synonymous
        mutations on the protein stability from its sequence. INPS is based on SVM
        regression and it is trained to predict the thermodynamic free energy change
        upon single-point variations in protein sequences. Results: We show that INPS
        performs similarly to the state-of-the-art methods based on protein structure
        when tested in cross-validation on a non-redundant dataset. INPS performs
        very well also on a newly generated dataset consisting of a number of variations
        occurring in the tumor suppressor protein p53. Our results suggest that INPS
        is a tool suited for computing the effect of non-synonymous polymorphisms
        on protein stability when the protein structure is not available. We also
        show that INPS predictions are complementary to those of the state-of-the-art,
        structure-based method mCSM. When the two methods are combined, the overall
        prediction on the p53 set scores significantly higher than those of the single
        methods.'
      authors:
      - name: Fariselli P.
      - name: Martelli P.L.
      - name: Savojardo C.
      - name: Casadio R.
      citationCount: 111
      date: '2015-02-06T00:00:00Z'
      journal: Bioinformatics
      title: 'INPS: Predicting the impact of non-synonymous variations on protein
        stability from sequence'
    note: null
    pmcid: null
    pmid: '25957347'
    type:
    - Primary
    version: null
  - doi: 10.1093/bioinformatics/btw192
    metadata:
      abstract: 'Motivation: Protein function depends on its structural stability.
        The effects of single point variations on protein stability can elucidate
        the molecular mechanisms of human diseases and help in developing new drugs.
        Recently, we introduced INPS, a method suited to predict the effect of variations
        on protein stability from protein sequence and whose performance is competitive
        with the available state-of-the-art tools. Results: In this article, we describe
        INPS-MD (Impact of Non synonymous variations on Protein Stability-Multi-Dimension),
        a web server for the prediction of protein stability changes upon single point
        variation from protein sequence and/or structure. Here, we complement INPS
        with a new predictor (INPS3D) that exploits features derived from protein
        3D structure. INPS3D scores with Pearson''s correlation to experimental ΔΔG
        values of 0.58 in cross validation and of 0.72 on a blind test set. The sequence-based
        INPS scores slightly lower than the structure-based INPS3D and both on the
        same blind test sets well compare with the state-of-the-art methods.'
      authors:
      - name: Savojardo C.
      - name: Fariselli P.
      - name: Martelli P.L.
      - name: Casadio R.
      citationCount: 189
      date: '2016-08-15T00:00:00Z'
      journal: Bioinformatics
      title: 'INPS-MD: A web server to predict stability of protein variants from
        sequence and structure'
    note: null
    pmcid: null
    pmid: '27153629'
    type:
    - Primary
    version: null
  relation: []
  toolType: []
  topic:
  - term: Protein folding, stability and design
    uri: http://edamontology.org/topic_0130
  - term: Genetic variation
    uri: http://edamontology.org/topic_0199
  - term: Rare diseases
    uri: http://edamontology.org/topic_3325
  validated: 1
  version:
  - '2.0'
- accessibility: Open access
  additionDate: '2025-03-17T14:56:35.753220Z'
  biotoolsCURIE: biotools:ddgemb
  biotoolsID: ddgemb
  collectionID: []
  confidence_flag: tool
  cost: Free of charge
  credit:
  - email: null
    fundrefid: null
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    name: ELIXIR-ITA-BOLOGNA
    note: null
    orcidid: null
    rorid: null
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    typeRole:
    - Provider
    url: https://www.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:
    - Maintainer
    - Developer
    - Primary contact
    url: null
  description: Predicting the impact of mutations on protein stability from sequence
    using protein language models
  documentation:
  - note: null
    type:
    - General
    url: https://ddgemb.biocomp.unibo.it/help/
  download: []
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  - Rare Diseases
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    input:
    - data:
        term: Protein sequence
        uri: http://edamontology.org/data_2976
      format: []
    - data:
        term: Sequence variations
        uri: http://edamontology.org/data_3498
      format: []
    note: null
    operation: []
    output:
    - data:
        term: Protein report
        uri: http://edamontology.org/data_0896
      format: []
  homepage: https://ddgemb.biocomp.unibo.it
  homepage_status: 0
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  owner: ELIXIR-ITA-BOLOGNA
  publication:
  - doi: 10.1093/bioinformatics/btaf019
    metadata:
      abstract: 'Motivation: The knowledge of protein stability upon residue variation
        is an important step for functional protein design and for understanding how
        protein variants can promote disease onset. Computational methods are important
        to complement experimental approaches and allow a fast screening of large
        datasets of variations. Results: In this work, we present DDGemb, a novel
        method combining protein language model embeddings and transformer architectures
        to predict protein ΔΔG upon both single- and multi-point variations. DDGemb
        has been trained on a high-quality dataset derived from literature and tested
        on available benchmark datasets of single- and multi-point variations. DDGemb
        performs at the state of the art in both single- and multi-point variations.'
      authors:
      - name: Savojardo C.
      - name: Manfredi M.
      - name: Martelli P.L.
      - name: Casadio R.
      citationCount: 0
      date: '2025-01-01T00:00:00Z'
      journal: Bioinformatics
      title: 'DDGemb: predicting protein stability change upon single- and multi-point
        variations with embeddings and deep learning'
    note: null
    pmcid: PMC11783275
    pmid: '39799516'
    type:
    - Primary
    version: null
  relation: []
  toolType: []
  topic:
  - term: Protein folding, stability and design
    uri: http://edamontology.org/topic_0130
  - term: Genetic variation
    uri: http://edamontology.org/topic_0199
  - term: Rare diseases
    uri: http://edamontology.org/topic_3325
  validated: 0
  version:
  - '1'
- accessibility: Open access
  additionDate: '2016-05-04T15:36:53Z'
  biotoolsCURIE: biotools:inps
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    url: http://www.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:
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    - Primary contact
    url: null
  - email: piero.fariselli@unito.it
    fundrefid: null
    gridid: null
    name: Piero Fariselli
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  description: Predicting the impact of mutations on protein stability from sequence
  documentation:
  - note: null
    type:
    - General
    url: https://inpsmd.biocomp.unibo.it/help
  download: []
  editPermission:
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    - ELIXIR-ITA-BOLOGNA
    - savo
    type: group
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  elixirNode:
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  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Protein sequence (raw)
        uri: http://edamontology.org/data_2974
      format: []
    note: Prediction of the impact of non-synonymous polymorphisms on protein stability
    operation: []
    output:
    - data:
        term: Protein report
        uri: http://edamontology.org/data_0896
      format: []
  homepage: https://inpsmd.biocomp.unibo.it
  homepage_status: 0
  language: []
  lastUpdate: '2025-03-17T14:54:19.762674Z'
  license: null
  link: []
  maturity: Mature
  name: INPS
  operatingSystem: []
  otherID: []
  owner: ELIXIR-ITA-BOLOGNA
  publication:
  - doi: 10.1093/bioinformatics/btv291
    metadata:
      abstract: 'Motivation: A tool for reliably predicting the impact of variations
        on protein stability is extremely important for both protein engineering and
        for understanding the effects of Mendelian and somatic mutations in the genome.
        Next Generation Sequencing studies are constantly increasing the number of
        protein sequences. Given the huge disproportion between protein sequences
        and structures, there is a need for tools suited to annotate the effect of
        mutations starting from protein sequence without relying on the structure.
        Here, we describe INPS, a novel approach for annotating the effect of non-synonymous
        mutations on the protein stability from its sequence. INPS is based on SVM
        regression and it is trained to predict the thermodynamic free energy change
        upon single-point variations in protein sequences. Results: We show that INPS
        performs similarly to the state-of-the-art methods based on protein structure
        when tested in cross-validation on a non-redundant dataset. INPS performs
        very well also on a newly generated dataset consisting of a number of variations
        occurring in the tumor suppressor protein p53. Our results suggest that INPS
        is a tool suited for computing the effect of non-synonymous polymorphisms
        on protein stability when the protein structure is not available. We also
        show that INPS predictions are complementary to those of the state-of-the-art,
        structure-based method mCSM. When the two methods are combined, the overall
        prediction on the p53 set scores significantly higher than those of the single
        methods.'
      authors:
      - name: Fariselli P.
      - name: Martelli P.L.
      - name: Savojardo C.
      - name: Casadio R.
      citationCount: 111
      date: '2015-02-06T00:00:00Z'
      journal: Bioinformatics
      title: 'INPS: Predicting the impact of non-synonymous variations on protein
        stability from sequence'
    note: null
    pmcid: null
    pmid: '25957347'
    type:
    - Primary
    version: null
  - doi: 10.1093/bioinformatics/btw192
    metadata:
      abstract: 'Motivation: Protein function depends on its structural stability.
        The effects of single point variations on protein stability can elucidate
        the molecular mechanisms of human diseases and help in developing new drugs.
        Recently, we introduced INPS, a method suited to predict the effect of variations
        on protein stability from protein sequence and whose performance is competitive
        with the available state-of-the-art tools. Results: In this article, we describe
        INPS-MD (Impact of Non synonymous variations on Protein Stability-Multi-Dimension),
        a web server for the prediction of protein stability changes upon single point
        variation from protein sequence and/or structure. Here, we complement INPS
        with a new predictor (INPS3D) that exploits features derived from protein
        3D structure. INPS3D scores with Pearson''s correlation to experimental ΔΔG
        values of 0.58 in cross validation and of 0.72 on a blind test set. The sequence-based
        INPS scores slightly lower than the structure-based INPS3D and both on the
        same blind test sets well compare with the state-of-the-art methods.'
      authors:
      - name: Savojardo C.
      - name: Fariselli P.
      - name: Martelli P.L.
      - name: Casadio R.
      citationCount: 189
      date: '2016-08-15T00:00:00Z'
      journal: Bioinformatics
      title: 'INPS-MD: A web server to predict stability of protein variants from
        sequence and structure'
    note: null
    pmcid: null
    pmid: '27153629'
    type:
    - Primary
    version: null
  relation: []
  toolType: []
  topic:
  - term: Protein folding, stability and design
    uri: http://edamontology.org/topic_0130
  - term: Genetic variation
    uri: http://edamontology.org/topic_0199
  validated: 1
  version:
  - '1.0'
- accessibility: Open access
  additionDate: '2025-03-04T16:25:28.372680Z'
  biotoolsCURIE: biotools:pep-fold4
  biotoolsID: pep-fold4
  collectionID: []
  confidence_flag: tool
  cost: Free of charge
  credit:
  - email: julien.rey@u-paris.fr
    fundrefid: null
    gridid: null
    name: Julien Rey
    note: null
    orcidid: https://orcid.org/0000-0002-3050-511X
    rorid: null
    typeEntity: Person
    typeRole:
    - Support
    - Developer
    - Primary contact
    url: null
  - email: samuel.muriail@u-paris.fr
    fundrefid: null
    gridid: null
    name: Samuel Murail
    note: null
    orcidid: https://orcid.org/0000-0002-3842-5333
    rorid: null
    typeEntity: Person
    typeRole:
    - Contributor
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Sjoerd de Vries
    note: null
    orcidid: https://orcid.org/0000-0002-7701-3454
    rorid: null
    typeEntity: Person
    typeRole:
    - Contributor
    url: null
  - email: philippe.derreumaux@ibpc.fr
    fundrefid: null
    gridid: null
    name: Philippe Derreumaux
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Contributor
    url: null
  - email: pierre.tuffery@inserm.fr
    fundrefid: null
    gridid: null
    name: Pierre Tufféry
    note: null
    orcidid: https://orcid.org/0000-0003-1033-9895
    rorid: null
    typeEntity: Person
    typeRole:
    - Contributor
    url: null
  description: PEP-FOLD4 is a fast and accurate structure prediction tool for peptides
    of up to 40 amino acids in aqueous solutions. Unlike many machine-learning approaches
    (e.g., AlphaFold2, TrRosetta, RaptorX), it integrates the Debye-Hückel formalism
    for charged side-chain interactions with a Mie potential for intramolecular forces.
    Based on a coarse-grained representation, PEP-FOLD4 performs competitively on
    well-structured peptides and shows significant improvements for poly-charged peptides,
    making it particularly useful for studying pH- and salt-dependent conformations.
  documentation:
  - note: null
    type:
    - User manual
    url: https://bioserv.rpbs.univ-paris-diderot.fr/services/PEP-FOLD4/
  download:
  - note: Source code and recipe for docker images allowing to run PEP-FOLD4 locally.
      All repository content is covered by a non-commercial license agreement and
      may be used for non-commercial and internal research purposes only.
    type: Source code
    url: https://owncloud.rpbs.univ-paris-diderot.fr/owncloud/index.php/s/7NHDSJXiQA0V2zy
    version: null
  editPermission:
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    type: private
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  - 3D-BioInfo
  elixirNode:
  - France
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Protein sequence
        uri: http://edamontology.org/data_2976
      format: []
    note: null
    operation:
    - term: Modelling and simulation
      uri: http://edamontology.org/operation_2426
    - term: Ab initio structure prediction
      uri: http://edamontology.org/operation_0476
    output:
    - data:
        term: Plot
        uri: http://edamontology.org/data_2884
      format:
      - term: PDB database entry format
        uri: http://edamontology.org/format_1475
    - data:
        term: Report
        uri: http://edamontology.org/data_2048
      format: []
  homepage: https://bioserv.rpbs.univ-paris-diderot.fr/services/PEP-FOLD4
  homepage_status: 0
  language:
  - Python
  lastUpdate: '2025-03-05T16:21:19.399517Z'
  license: null
  link:
  - note: Link to the PEP-FOLD4 web page service
    type:
    - Service
    url: https://mobyle2.rpbs.univ-paris-diderot.fr/cgi-bin/portal.py#forms::PEP-FOLD4
  maturity: Mature
  name: PEP-FOLD4
  operatingSystem: []
  otherID: []
  owner: nchevrollier
  publication:
  - doi: 10.1093/nar/gkad376
    metadata:
      abstract: Accurate and fast structure prediction of peptides of less 40 amino
        acids in aqueous solution has many biological applications, but their conformations
        are pH-and salt concentration-dependent. In this work, we present PEP-FOLD4
        which goes one step beyond many machine-learning approaches, such as AlphaFold2,
        TrRosetta and RaptorX. Adding the Debye-Hueckel formalism for charged-charged
        side chain interactions to a Mie formalism for all intramolecular (backbone
        and side chain) interactions, PEP-FOLD4, based on a coarse-grained representation
        of the peptides, performs as well as machine-learning methods on well-structured
        peptides, but displays significant improvements for poly-charged peptides.
        PEP-FOLD4 is available at http://bioserv.rpbs.univ-paris-diderot.fr/services/PEP-FOLD4.
        This server is free and there is no login requirement.
      authors:
      - name: Rey J.
      - name: Murail S.
      - name: De Vries S.
      - name: Derreumaux P.
      - name: Tuffery P.
      citationCount: 39
      date: '2023-07-05T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'PEP-FOLD4: A pH-dependent force field for peptide structure prediction
        in aqueous solution'
    note: null
    pmcid: PMC10320157
    pmid: '37166962'
    type:
    - Primary
    version: null
  relation: []
  toolType:
  - Web application
  topic:
  - term: Molecular modelling
    uri: http://edamontology.org/topic_2275
  - term: Computational chemistry
    uri: http://edamontology.org/topic_3332
  validated: 0
  version: []
- accessibility: Open access
  additionDate: '2025-01-31T17:19:47.094256Z'
  biotoolsCURIE: biotools:proteomaker
  biotoolsID: proteomaker
  collectionID:
  - Proteomics
  confidence_flag: null
  cost: Free of charge
  credit: []
  description: ProteoMaker is a platform for the generation of an in-silico bottom-up
    proteomics data set with a ground truth on the level of proteoforms.
  documentation: []
  download:
  - note: null
    type: Source code
    url: https://github.com/computproteomics/ProteoMaker
    version: null
  editPermission:
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    type: private
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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: null
    operation:
    - term: Simulated gene expression data generation
      uri: http://edamontology.org/operation_3566
    - term: Statistical calculation
      uri: http://edamontology.org/operation_2238
    output:
    - data:
        term: Gene expression matrix
        uri: http://edamontology.org/data_3112
      format:
      - term: CSV
        uri: http://edamontology.org/format_3752
    - data:
        term: Proteolytic digest
        uri: http://edamontology.org/data_1238
      format:
      - term: CSV
        uri: http://edamontology.org/format_3752
    - data:
        term: Quality control report
        uri: http://edamontology.org/data_3914
      format:
      - term: YAML
        uri: http://edamontology.org/format_3750
    - data:
        term: Statistical estimate score
        uri: http://edamontology.org/data_0951
      format:
      - term: CSV
        uri: http://edamontology.org/format_3752
  homepage: https://github.com/computproteomics/ProteoMaker
  homepage_status: 0
  language:
  - R
  lastUpdate: '2025-01-31T17:19:47.096981Z'
  license: MIT
  link:
  - note: Web application
    type:
    - Service
    url: https://computproteomics.bmb.sdu.dk/app_direct/ProteoMaker
  maturity: Mature
  name: ProteoMaker
  operatingSystem:
  - Mac
  - Linux
  - Windows
  otherID: []
  owner: veitveit11
  publication: []
  relation: []
  toolType:
  - Library
  - Web application
  topic:
  - term: Proteomics
    uri: http://edamontology.org/topic_0121
  - term: Proteomics experiment
    uri: http://edamontology.org/topic_3520
  - term: Simulation experiment
    uri: http://edamontology.org/topic_3524
  validated: 0
  version: []
- accessibility: Open access
  additionDate: '2023-08-30T13:03:57.407598Z'
  biotoolsCURIE: biotools:shic
  biotoolsID: shic
  collectionID: []
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: magnus.palmblad@gmail.com
    fundrefid: null
    gridid: null
    name: Magnus Palmblad
    note: null
    orcidid: https://orcid.org/0000-0002-5865-8994
    rorid: null
    typeEntity: null
    typeRole:
    - Primary contact
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Veit Schwämmle
    note: null
    orcidid: https://orcid.org/0000-0002-9708-6722
    rorid: null
    typeEntity: null
    typeRole: []
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Dirk Winkelhardt
    note: null
    orcidid: https://orcid.org/0000-0001-8770-2221
    rorid: null
    typeEntity: null
    typeRole: []
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Vedran Kasalica
    note: null
    orcidid: https://orcid.org/0000-0002-0097-1056
    rorid: null
    typeEntity: null
    typeRole: []
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Anna-Lena Lamprecht
    note: null
    orcidid: https://orcid.org/0000-0003-1953-5606
    rorid: null
    typeEntity: null
    typeRole: []
    url: null
  description: shic is a collection of shims for use in automated workflow composition
  documentation:
  - note: null
    type:
    - General
    url: https://github.com/magnuspalmblad/shic/README.md
  download: []
  editPermission:
    authors:
    - VKasalica
    - veits@bmb.sdu.dk
    type: group
  elixirCommunity:
  - Proteomics
  - Galaxy
  - Metabolomics
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Protein report
        uri: http://edamontology.org/data_0896
      format:
      - term: protXML
        uri: http://edamontology.org/format_3747
    note: null
    operation:
    - term: Conversion
      uri: http://edamontology.org/operation_3434
    output:
    - data:
        term: ID list
        uri: http://edamontology.org/data_2872
      format:
      - term: TSV
        uri: http://edamontology.org/format_3475
  - 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: Conversion
      uri: http://edamontology.org/operation_3434
    output:
    - data:
        term: Mass spectrometry data
        uri: http://edamontology.org/data_2536
      format:
      - term: MGF
        uri: http://edamontology.org/format_3651
  - cmd: null
    input:
    - data:
        term: Sequence distance matrix
        uri: http://edamontology.org/data_0870
      format:
      - term: Nexus format
        uri: http://edamontology.org/format_1912
    note: null
    operation:
    - term: Conversion
      uri: http://edamontology.org/operation_3434
    output:
    - data:
        term: Sequence distance matrix
        uri: http://edamontology.org/data_0870
      format:
      - term: mega
        uri: http://edamontology.org/format_1991
  - cmd: null
    input:
    - data:
        term: Protein sequence
        uri: http://edamontology.org/data_2976
      format:
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        uri: http://edamontology.org/format_1929
    note: null
    operation:
    - term: Conversion
      uri: http://edamontology.org/operation_3434
    output:
    - data:
        term: UniProt accession
        uri: http://edamontology.org/data_3021
      format:
      - term: TSV
        uri: http://edamontology.org/format_3475
  - cmd: null
    input:
    - data:
        term: Peptide identification
        uri: http://edamontology.org/data_0945
      format:
      - term: pepXML
        uri: http://edamontology.org/format_3655
    note: null
    operation:
    - term: Conversion
      uri: http://edamontology.org/operation_3434
    output:
    - data:
        term: Protein sequence
        uri: http://edamontology.org/data_2976
      format:
      - term: TSV
        uri: http://edamontology.org/format_3475
  - cmd: null
    input:
    - data:
        term: Peptide identification
        uri: http://edamontology.org/data_0945
      format:
      - term: mzIdentML
        uri: http://edamontology.org/format_3247
    note: null
    operation:
    - term: Conversion
      uri: http://edamontology.org/operation_3434
    output:
    - data:
        term: Protein sequence
        uri: http://edamontology.org/data_2976
      format:
      - term: TSV
        uri: http://edamontology.org/format_3475
  - cmd: null
    input:
    - data:
        term: Text mining report
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      format:
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        uri: http://edamontology.org/format_2332
    note: null
    operation:
    - term: Conversion
      uri: http://edamontology.org/operation_3434
    output:
    - data:
        term: ChEBI ID
        uri: http://edamontology.org/data_1174
      format:
      - term: TSV
        uri: http://edamontology.org/format_3475
  - cmd: null
    input:
    - data:
        term: Peptide identification
        uri: http://edamontology.org/data_0945
      format:
      - term: TSV
        uri: http://edamontology.org/format_3475
    note: null
    operation:
    - term: Conversion
      uri: http://edamontology.org/operation_3434
    output:
    - data:
        term: Peptide identification
        uri: http://edamontology.org/data_0945
      format:
      - term: mzIdentML
        uri: http://edamontology.org/format_3247
  - cmd: null
    input:
    - data:
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      format:
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        uri: http://edamontology.org/format_3475
    note: null
    operation:
    - term: Conversion
      uri: http://edamontology.org/operation_3434
    output:
    - data:
        term: ID list
        uri: http://edamontology.org/data_2872
      format:
      - term: TSV
        uri: http://edamontology.org/format_3475
  - cmd: null
    input:
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        term: Peptide identification
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      format:
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        uri: http://edamontology.org/format_3655
    note: null
    operation:
    - term: Conversion
      uri: http://edamontology.org/operation_3434
    output:
    - data:
        term: Protein name
        uri: http://edamontology.org/data_1009
      format:
      - term: Textual format
        uri: http://edamontology.org/format_2330
  - cmd: null
    input:
    - data:
        term: Peptide identification
        uri: http://edamontology.org/data_0945
      format:
      - term: pepXML
        uri: http://edamontology.org/format_3655
    note: null
    operation:
    - term: Conversion
      uri: http://edamontology.org/operation_3434
    output:
    - data:
        term: Protein name (UniProt)
        uri: http://edamontology.org/data_2764
      format:
      - term: Textual format
        uri: http://edamontology.org/format_2330
  homepage: https://github.com/magnuspalmblad/shic
  homepage_status: 0
  language: []
  lastUpdate: '2025-01-16T16:39:33.218764Z'
  license: MIT
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/magnuspalmblad/shic
  maturity: null
  name: shic
  operatingSystem: []
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  owner: n.m.palmblad@lumc.nl
  publication: []
  relation: []
  toolType:
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  topic: []
  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:
    - 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:
    - Contributor
    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:
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    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:
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    input:
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        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:
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        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: '2016-05-31T11:29:42Z'
  biotoolsCURIE: biotools:dynamine
  biotoolsID: dynamine
  collectionID: []
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  credit:
  - email: null
    fundrefid: null
    gridid: null
    name: vub.ac.be
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
    - Provider
    url: null
  - email: wvranken@vub.ac.be
    fundrefid: null
    gridid: null
    name: Wim Vranken
    note: null
    orcidid: null
    rorid: null
    typeEntity: null
    typeRole:
    - Support
    url: null
  - email: wvranken@vub.ac.be
    fundrefid: null
    gridid: null
    name: Wim Vranken
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  description: Protein backbone dynamics prediction from sequence.
  documentation:
  - note: null
    type:
    - General
    url: http://dynamine.ibsquare.be/help/
  download: []
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    - tanish
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  function:
  - cmd: null
    input:
    - data:
        term: Protein sequence (raw)
        uri: http://edamontology.org/data_2974
      format:
      - term: FASTA
        uri: http://edamontology.org/format_1929
    note: Protein backbone dynamics prediction from sequence File containing one value
      per amino acid in each protein sequence
    operation:
    - term: Prediction and recognition
      uri: http://edamontology.org/operation_2423
    output:
    - data:
        term: Protein features
        uri: http://edamontology.org/data_1277
      format: []
  homepage: http://dynamine.ibsquare.be/
  homepage_status: 0
  language: []
  lastUpdate: '2025-01-08T15:03:40.105084Z'
  license: null
  link: []
  maturity: null
  name: DynaMine
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: wvranken@vub.ac.be
  publication:
  - doi: 10.1038/ncomms3741
    metadata: null
    note: null
    pmcid: null
    pmid: '24225580'
    type:
    - Other
    version: null
  - doi: 10.1093/nar/gku270
    metadata: null
    note: null
    pmcid: PMC4086073
    pmid: '24728994'
    type:
    - Other
    version: null
  relation: []
  toolType:
  - Web API
  - Web application
  topic:
  - term: Biophysics
    uri: http://edamontology.org/topic_3306
  - term: Protein properties
    uri: http://edamontology.org/topic_0123
  - term: Protein disordered structure
    uri: http://edamontology.org/topic_3538
  validated: 1
  version:
  - '1'
- accessibility: Open access
  additionDate: '2021-05-08T17:25:21Z'
  biotoolsCURIE: biotools:bakta
  biotoolsID: bakta
  collectionID: []
  confidence_flag: tool
  cost: Free of charge
  credit:
  - email: oliver.schwengers@cb.jlug.de
    fundrefid: null
    gridid: null
    name: Oliver Schwengers
    note: null
    orcidid: https://orcid.org/0000-0003-4216-2721
    rorid: null
    typeEntity: Person
    typeRole:
    - 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
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  function:
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    input:
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        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
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      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'
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    type: uses
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    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: '2020-11-09T21:38:53Z'
  biotoolsCURIE: biotools:trend_protein_evolution_function
  biotoolsID: trend_protein_evolution_function
  collectionID: []
  confidence_flag: null
  cost: null
  credit:
  - email: gumerov.1@osu.edu
    fundrefid: null
    gridid: null
    name: Vadim Gumerov
    note: null
    orcidid: https://orcid.org/0000-0003-1670-7679
    rorid: null
    typeEntity: null
    typeRole: []
    url: null
  description: TREND is a platform that allows researchers to explore protein function
    and evolution identifying protein features, gene neighborhoods and operons, clustering
    neighboring genes, and integrating all these data into phylogenomic context and
    cross-referencing with RefSeq, Pfam, CDD and MiST databases. The platform provides
    ample opportunities for adjusting each step of the analysis.
  documentation:
  - note: null
    type:
    - User manual
    url: http://trend.evobionet.com/help
  download: []
  editPermission:
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  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Protein sequence alignment
        uri: http://edamontology.org/data_1384
      format:
      - term: FASTA
        uri: http://edamontology.org/format_1929
    - data:
        term: Sequence set (protein)
        uri: http://edamontology.org/data_1233
      format:
      - term: FASTA
        uri: http://edamontology.org/format_1929
    - data:
        term: Phylogenetic tree
        uri: http://edamontology.org/data_0872
      format:
      - term: newick
        uri: http://edamontology.org/format_1910
    - data:
        term: NCBI locus tag
        uri: http://edamontology.org/data_1900
      format:
      - term: Textual format
        uri: http://edamontology.org/format_2330
    - data:
        term: RefSeq accession (protein)
        uri: http://edamontology.org/data_2385
      format: []
    note: null
    operation:
    - term: Multiple sequence alignment
      uri: http://edamontology.org/operation_0492
    - term: Phylogenetic inference
      uri: http://edamontology.org/operation_0323
    - term: Sequence clustering
      uri: http://edamontology.org/operation_0291
    - term: Sequence classification
      uri: http://edamontology.org/operation_2995
    - term: Protein domain recognition
      uri: http://edamontology.org/operation_0246
    - term: Protein feature detection
      uri: http://edamontology.org/operation_3092
    output:
    - data:
        term: Protein sequence alignment
        uri: http://edamontology.org/data_1384
      format:
      - term: FASTA
        uri: http://edamontology.org/format_1929
    - data:
        term: Phylogenetic tree
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      format:
      - term: newick
        uri: http://edamontology.org/format_1910
    - data:
        term: Protein features
        uri: http://edamontology.org/data_1277
      format:
      - term: JSON
        uri: http://edamontology.org/format_3464
    - data:
        term: Image
        uri: http://edamontology.org/data_2968
      format:
      - term: SVG
        uri: http://edamontology.org/format_3604
    - data:
        term: Sequence cluster (protein)
        uri: http://edamontology.org/data_1245
      format:
      - term: JSON
        uri: http://edamontology.org/format_3464
  homepage: http://trend.evobionet.com/
  homepage_status: 0
  language: []
  lastUpdate: '2024-12-17T20:42:49.942166Z'
  license: null
  link: []
  maturity: null
  name: TREND Protein Evolution Function
  operatingSystem: []
  otherID: []
  owner: vadim
  publication:
  - doi: 10.1093/nar/gkaa243
    metadata:
      abstract: Key steps in a computational study of protein function involve analysis
        of (i) relationships between homologous proteins, (ii) protein domain architecture
        and (iii) gene neighborhoods the corresponding proteins are encoded in. Each
        of these steps requires a separate computational task and sets of tools. Currently
        in order to relate protein features and gene neighborhoods information to
        phylogeny, researchers need to prepare all the necessary data and combine
        them by hand, which is time-consuming and error-prone. Here, we present a
        new platform, TREND (tree-based exploration of neighborhoods and domains),
        which can perform all the necessary steps in automated fashion and put the
        derived information into phylogenomic context, thus making evolutionary based
        protein function analysis more efficient. A rich set of adjustable components
        allows a user to run the computational steps specific to his task. TREND is
        freely available at http://trend.zhulinlab.org.
      authors:
      - name: Gumerov V.M.
      - name: Zhulin I.B.
      citationCount: 33
      date: '2021-01-01T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'TREND: a platform for exploring protein function in prokaryotes based
        on phylogenetic, domain architecture and gene neighborhood analyses'
    note: null
    pmcid: PMC7319448
    pmid: '32282909'
    type:
    - Primary
    version: null
  - doi: 10.1093/nar/gkac034
    metadata:
      abstract: TheURL address of the web server published in this article has been
        changed fromhttp://trend.zhulinlab.org to http://trend. evobionet.com/.
      authors:
      - name: Gumerov V.M.
      - name: Zhulin I.B.
      citationCount: 6
      date: '2022-02-22T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'Erratum: TREND: A platform for exploring protein function in prokaryotes
        based on phylogenetic, domain architecture and gene neighborhood analyses
        (Nucleic Acids Research DOI: 10.1093/nar/gkaa243)'
    note: 'Can be also accessed at this URL: https://academic.oup.com/nar/advance-article/doi/10.1093/nar/gkac034/6517937'
    pmcid: PMC8860576
    pmid: '35100406'
    type:
    - Other
    version: null
  relation: []
  toolType:
  - Web service
  topic:
  - term: Evolutionary biology
    uri: http://edamontology.org/topic_3299
  - term: Phylogeny
    uri: http://edamontology.org/topic_0084
  - term: Microbiology
    uri: http://edamontology.org/topic_3301
  - term: Protein sites, features and motifs
    uri: http://edamontology.org/topic_3510
  - term: Functional genomics
    uri: http://edamontology.org/topic_0085
  - term: Phylogenomics
    uri: http://edamontology.org/topic_0194
  - term: Bioinformatics
    uri: http://edamontology.org/topic_0091
  validated: 0
  version: []
- accessibility: null
  additionDate: '2015-12-06T15:18:34Z'
  biotoolsCURIE: biotools:svmhc
  biotoolsID: svmhc
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    name: bils.se
    note: null
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    rorid: null
    typeEntity: Institute
    typeRole:
    - Provider
    url: null
  - email: arne@bioinfo.se
    fundrefid: null
    gridid: null
    name: null
    note: null
    orcidid: null
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    typeEntity: Person
    typeRole:
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    url: null
  description: Prediction of MHC class I binding peptides.
  documentation: []
  download: []
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  function:
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    input:
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        term: Protein sequence
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      format: []
    note: null
    operation:
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      uri: http://edamontology.org/operation_2423
    output:
    - data:
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      format: []
  homepage: http://www.sbc.su.se/%7Epierre/svmhc/
  homepage_status: 0
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  lastUpdate: '2024-11-25T16:22:00.301446Z'
  license: null
  link: []
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  name: SVMHC
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  owner: mikael.borg@bils.se
  publication:
  - doi: 10.1186/1471-2105-3-25
    metadata: null
    note: null
    pmcid: PMC129981
    pmid: '12225620'
    type:
    - Primary
    version: null
  relation: []
  toolType:
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  topic:
  - term: Sequence analysis
    uri: http://edamontology.org/topic_0080
  validated: 1
  version:
  - '1'
- accessibility: null
  additionDate: '2015-12-06T15:18:18Z'
  biotoolsCURIE: biotools:mdr
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  - email: yohell@ifm.liu.se
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    note: null
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    typeEntity: Person
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    url: null
  description: Medium-chain dehydrogenases/reductases database.
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  function:
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    input:
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        term: Protein sequence
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      format: []
    note: null
    operation:
    - term: Prediction and recognition
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    output:
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      format: []
  homepage: http://www.bioinfo.ifm.liu.se/services/mdr/
  homepage_status: 0
  language: []
  lastUpdate: '2024-11-25T16:21:59.226137Z'
  license: null
  link: []
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  name: MDR database
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  owner: mikael.borg@bils.se
  publication:
  - doi: 10.1110/ps.035428.108
    metadata: null
    note: null
    pmcid: PMC2548362
    pmid: '18614751'
    type:
    - Primary
    version: null
  relation: []
  toolType:
  - Database portal
  topic:
  - term: Sequence analysis
    uri: http://edamontology.org/topic_0080
  validated: 1
  version: []
- accessibility: null
  additionDate: '2015-12-06T15:18:13Z'
  biotoolsCURIE: biotools:drip-pred
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    note: null
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    typeEntity: Institute
    typeRole:
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    url: null
  - email: maccallr@sbc.su.se
    fundrefid: null
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    name: null
    note: null
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    typeEntity: Person
    typeRole:
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    url: null
  description: Disorder/order prediction for proteins.
  documentation: []
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  function:
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    input:
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  - term: Protein properties
    uri: http://edamontology.org/topic_0123
  validated: 1
  version: []
- accessibility: null
  additionDate: '2015-01-29T15:44:18Z'
  biotoolsCURIE: biotools:picr
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    fundrefid: null
    gridid: null
    name: Richard Cote
    note: null
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    rorid: null
    typeEntity: Person
    typeRole:
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    url: null
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    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: http://www.ebi.ac.uk/support/
  description: Protein Identifier Cross Reference service to map proteins by identifiers
    and sequence.
  documentation:
  - note: null
    type:
    - Terms of use
    url: http://www.ebi.ac.uk/about/terms-of-use
  - note: null
    type:
    - General
    url: http://www.ebi.ac.uk/Tools/picr/init.do#documentation
  - note: Map accession numbers between databases. It will also retrieve the UPI(UniProt
      Archive (UniParc) identifier of the given accession number.
    type:
    - API documentation
    url: http://www.ebi.ac.uk/Tools/picr/RESTDocumentation.do
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    input:
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      format: []
    note: null
    operation:
    - term: ID mapping
      uri: http://edamontology.org/operation_3282
    output:
    - data:
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      format: []
  homepage: http://www.ebi.ac.uk/Tools/picr/
  homepage_status: 0
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  name: PICR
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  - Windows
  - Mac
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  owner: EMBL-EBI
  publication:
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    metadata: null
    note: null
    pmcid: PMC2151082
    pmid: '17945017'
    type:
    - Primary
    version: null
  relation: []
  toolType:
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  topic:
  - term: Data identity and mapping
    uri: http://edamontology.org/topic_3345
  - term: Data management
    uri: http://edamontology.org/topic_3071
  validated: 1
  version:
  - '1'
- accessibility: null
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    gridid: null
    name: Xavier Watkins
    note: null
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    typeEntity: Person
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    url: null
  description: Multiple sequence alignment.
  documentation:
  - note: null
    type:
    - Terms of use
    url: http://www.ebi.ac.uk/about/terms-of-use
  - note: null
    type:
    - General
    url: http://www.uniprot.org/help/sequence-alignments
  - note: null
    type:
    - Terms of use
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    input:
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      format: []
    note: null
    operation:
    - term: Multiple sequence alignment
      uri: http://edamontology.org/operation_0492
    output:
    - data:
        term: Sequence alignment
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      format: []
  homepage: http://www.uniprot.org/align
  homepage_status: 0
  language: []
  lastUpdate: '2024-11-25T15:19:23.003433Z'
  license: CC-BY-ND-3.0
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  name: UniProt Align
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  - Windows
  - Mac
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  owner: EMBL-EBI
  publication:
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    metadata: null
    note: null
    pmcid: PMC4384041
    pmid: '25348405'
    type:
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    version: null
  relation: []
  toolType:
  - Web application
  topic:
  - term: Sequence analysis
    uri: http://edamontology.org/topic_0080
  validated: 1
  version:
  - '1'
- accessibility: null
  additionDate: '2015-01-22T11:49:01Z'
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    fundrefid: null
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    name: Jan Kosinski
    note: null
    orcidid: null
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    typeEntity: Person
    typeRole:
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    url: null
  description: 'At MODORAMA two applications can be run: MODexplorer, an integrated
    tool for exploring protein sequence, structure and function relationships, and
    MODalign, a rich alignment editor to improve target-template alignments'
  documentation:
  - note: null
    type:
    - General
    url: http://modorama.org/
  download: []
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  function:
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    input:
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        term: Protein sequence
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      format:
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        uri: http://edamontology.org/format_1929
    - data:
        term: Protein structure
        uri: http://edamontology.org/data_1460
      format:
      - term: PDB
        uri: http://edamontology.org/format_1476
    - data:
        term: Sequence-structure alignment
        uri: http://edamontology.org/data_0893
      format: []
    note: 'MODexplorer: Explores sequence, structure and function relationships in
      protein families and selects templates and perform homology modeling; MODalign:
      displays, evaluates and edits alignments for comparative (homology) modeling'
    operation:
    - term: Protein modelling
      uri: http://edamontology.org/operation_0477
    - term: Sequence alignment refinement
      uri: http://edamontology.org/operation_2089
    - term: Protein structure prediction
      uri: http://edamontology.org/operation_0474
    output: []
  homepage: http://modorama.org
  homepage_status: 0
  language: []
  lastUpdate: '2024-11-25T15:00:26.069732Z'
  license: null
  link: []
  maturity: null
  name: MODORAMA
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: ELIXIR-ITA-SAPIENZA
  publication:
  - doi: 10.1093/bioinformatics/btt062
    metadata: null
    note: null
    pmcid: PMC3605600
    pmid: '23396123'
    type:
    - Primary
    version: null
  - doi: 10.1093/bioinformatics/bts070
    metadata: null
    note: null
    pmcid: PMC3315710
    pmid: '22308148'
    type:
    - Other
    version: null
  relation: []
  toolType:
  - Web application
  topic:
  - term: Structure prediction
    uri: http://edamontology.org/topic_0082
  validated: 1
  version:
  - '1.0'
- accessibility: null
  additionDate: '2015-12-07T13:03:43Z'
  biotoolsCURIE: biotools:gpcrhmm
  biotoolsID: gpcrhmm
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  confidence_flag: null
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  credit:
  - email: null
    fundrefid: null
    gridid: null
    name: bils.se
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
    - Provider
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: null
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: http://www.sbc.su.se/~erison/
  description: A hidden Markov model for GPCR detection.
  documentation:
  - note: null
    type:
    - General
    url: http://gpcrhmm.sbc.su.se/instructions.html
  download: []
  editPermission:
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  function:
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    input:
    - data:
        term: Protein sequence
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      format: []
    note: null
    operation:
    - term: Prediction and recognition
      uri: http://edamontology.org/operation_2423
    output:
    - data:
        term: Protein features
        uri: http://edamontology.org/data_1277
      format: []
  homepage: http://gpcrhmm.sbc.su.se/
  homepage_status: 0
  language: []
  lastUpdate: '2024-11-25T14:55:26.899358Z'
  license: null
  link: []
  maturity: null
  name: GPCRHMM
  operatingSystem:
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  - Windows
  - Mac
  otherID: []
  owner: mikael.borg@bils.se
  publication:
  - doi: 10.1110/ps.051745906
    metadata: null
    note: null
    pmcid: PMC2249772
    pmid: '16452613'
    type:
    - Primary
    version: null
  relation: []
  toolType:
  - Command-line tool
  - Web application
  topic:
  - term: Sequence analysis
    uri: http://edamontology.org/topic_0080
  validated: 1
  version:
  - '1'
- accessibility: null
  additionDate: '2018-06-18T09:30:36Z'
  biotoolsCURIE: biotools:hsymdock
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  collectionID: []
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  credit:
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    fundrefid: null
    gridid: null
    name: null
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  description: Symmetric protein docking for oligomers with Cn or Dn symmetry from
    the structure or sequence of a subunit molecule.
  documentation:
  - note: null
    type:
    - General
    url: http://huanglab.phys.hust.edu.cn/hsymdock/help.html
  download: []
  editPermission:
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  function:
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    input:
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        term: Protein sequence
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      format:
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      - term: PDB
        uri: http://edamontology.org/format_1476
    note: null
    operation:
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      uri: http://edamontology.org/operation_0478
    output: []
  homepage: http://huanglab.phys.hust.edu.cn/hsymdock/
  homepage_status: 0
  language:
  - PHP
  lastUpdate: '2024-11-25T14:41:44.638481Z'
  license: null
  link: []
  maturity: null
  name: HSYMDOCK
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: aotamendi.1
  publication:
  - doi: 10.1093/nar/gky398
    metadata:
      abstract: A major subclass of protein-protein interactions is formed by homo-oligomers
        with certain symmetry. Therefore, computational modeling of the symmetric
        protein complexes is important for understanding the molecular mechanism of
        related biological processes. Although several symmetric docking algorithms
        have been developed for Cn symmetry, few docking servers have been proposed
        for Dn symmetry. Here, we present HSYMDOCK, a web server of our hierarchical
        symmetric docking algorithm that supports both Cn and Dn symmetry. The HSYMDOCK
        server was extensively evaluated on three benchmarks of symmetric protein
        complexes, including the 20 CASP11-CAPRI30 homo-oligomer targets, the symmetric
        docking benchmark of 213 Cn targets and 35 Dn targets, and a nonredundant
        test set of 55 transmembrane proteins. It was shown that HSYMDOCK obtained
        a significantly better performance than other similar docking algorithms.
        The server supports both sequence and structure inputs for the monomer/subunit.
        Users have an option to provide the symmetry type of the complex, or the server
        can predict the symmetry type automatically. The docking process is fast and
        on average consumes 101/420 min for a docking job. The HSYMDOCK web server
        is available at http://huanglab.phys.hust.edu.cn/hsymdock/.
      authors:
      - name: Yan Y.
      - name: Tao H.
      - name: Huang S.-Y.
      citationCount: 33
      date: '2018-07-02T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'HSYMDOCK: A docking web server for predicting the structure of protein
        homo-oligomers with Cn or Dn symmetry'
    note: null
    pmcid: PMC6030965
    pmid: '29846641'
    type:
    - Primary
    version: null
  relation: []
  toolType:
  - Web application
  topic:
  - term: Molecular modelling
    uri: http://edamontology.org/topic_2275
  validated: 1
  version:
  - '2018-06-02'
- accessibility: null
  additionDate: '2018-03-12T09:45:00Z'
  biotoolsCURIE: biotools:mobidb-lite
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  collectionID: []
  confidence_flag: null
  cost: null
  credit:
  - email: null
    fundrefid: null
    gridid: null
    name: University of Padua, Department of Biomedical Sciences, BioComputing UP
      lab
    note: null
    orcidid: null
    rorid: null
    typeEntity: null
    typeRole: []
    url: http://protein.bio.unipd.it/
  - email: null
    fundrefid: null
    gridid: null
    name: ELIXIR-ITA-PADOVA
    note: null
    orcidid: null
    rorid: null
    typeEntity: null
    typeRole: []
    url: http://elixir.bio.unipd.it/
  - email: silvio.tosatto@unipd.it
    fundrefid: null
    gridid: null
    name: Silvio C.E. Tosatto
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: http://protein.bio.unipd.it
  description: MobiDB-lite is an optimized method for highly specific predictions
    of long intrinsically disordered regions
  documentation:
  - note: null
    type:
    - General
    url: http://protein.bio.unipd.it/mobidblite/
  download:
  - note: null
    type: Software package
    url: http://protein.bio.unipd.it/download/
    version: null
  editPermission:
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  function:
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    input:
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        term: Protein sequence
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      format:
      - term: FASTA
        uri: http://edamontology.org/format_1929
    note: null
    operation:
    - term: Protein feature detection
      uri: http://edamontology.org/operation_3092
    - term: Structure analysis
      uri: http://edamontology.org/operation_2480
    output:
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        term: Protein features
        uri: http://edamontology.org/data_1277
      format:
      - term: JSON
        uri: http://edamontology.org/format_3464
      - term: Sequence feature table format
        uri: http://edamontology.org/format_2548
  homepage: http://protein.bio.unipd.it/mobidblite/
  homepage_status: 0
  language:
  - Python
  lastUpdate: '2024-11-25T14:39:51.264257Z'
  license: CC-BY-NC-ND-4.0
  link: []
  maturity: Mature
  name: MobiDB-lite
  operatingSystem:
  - Linux
  otherID: []
  owner: ELIXIR-ITA-PADOVA
  publication:
  - doi: 10.1093/bioinformatics/btx015
    metadata:
      abstract: 'Motivation: Intrinsic disorder (ID) is established as an important
        feature of protein sequences. Its use in proteome annotation is however hampered
        by the availability of many methods with similar performance at the single
        residue level, which have mostly not been optimized to predict long ID regions
        of size comparable to domains. Results: Here, we have focused on providing
        a single consensus-based prediction, MobiDB-lite, optimized for highly specific
        (i.e. few false positive) predictions of long disorder. The method uses eight
        different predictors to derive a consensus which is then filtered for spurious
        short predictions. Consensus prediction is shown to outperform the single
        methods when annotating long ID regions. MobiDB-lite can be useful in large-scale
        annotation scenarios and has indeed already been integrated in the MobiDB,
        DisProt and InterPro databases.'
      authors:
      - name: Necci M.
      - name: Piovesan D.
      - name: Dosztanyi Z.
      - name: Tosatto S.C.E.
      citationCount: 139
      date: '2017-05-01T00:00:00Z'
      journal: Bioinformatics
      title: 'MobiDB-lite: Fast and highly specific consensus prediction of intrinsic
        disorder in proteins'
    note: null
    pmcid: null
    pmid: '28453683'
    type: []
    version: null
  relation: []
  toolType:
  - Command-line tool
  topic:
  - term: Protein sites, features and motifs
    uri: http://edamontology.org/topic_3510
  validated: 1
  version:
  - '1.0'
- accessibility: null
  additionDate: '2018-06-04T16:46:37Z'
  biotoolsCURIE: biotools:rosettaes
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  collectionID: []
  confidence_flag: null
  cost: Free of charge (with restrictions)
  credit:
  - email: dimaio@u.washington.edu
    fundrefid: null
    gridid: null
    name: Frank Dimaio
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
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    url: null
  description: An automated tool that uses a fragment-based sampling strategy for
    de novo model completion of macromolecular structures from cryo-EM density maps
    at 3–5-Å resolution.
  documentation:
  - note: null
    type:
    - General
    url: https://media.nature.com/original/nature-assets/nmeth/journal/v14/n8/extref/nmeth.4340-S2.pdf
  download:
  - note: null
    type: API specification
    url: https://www.rosettacommons.org/docs/latest/release-notes
    version: null
  editPermission:
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  function:
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    input:
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        uri: http://edamontology.org/format_1476
    - data:
        term: Protein sequence
        uri: http://edamontology.org/data_2976
      format:
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    note: null
    operation:
    - term: Image analysis
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    - term: Structure analysis
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    output:
    - data:
        term: Structural profile
        uri: http://edamontology.org/data_0889
      format:
      - term: Workflow format
        uri: http://edamontology.org/format_2032
  homepage: https://www.rosettacommons.org/
  homepage_status: 0
  language: []
  lastUpdate: '2024-11-25T14:37:56.751132Z'
  license: Other
  link: []
  maturity: Mature
  name: RosettaES
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  - Linux
  - Windows
  - Mac
  otherID: []
  owner: ELIXIR-EE
  publication:
  - doi: 10.1038/nmeth.4340
    metadata:
      abstract: Accurate atomic modeling of macromolecular structures into cryo-electron
        microscopy (cryo-EM) maps is a major challenge, as the moderate resolution
        makes accurate placement of atoms difficult. We present Rosetta enumerative
        sampling (RosettaES), an automated tool that uses a fragment-based sampling
        strategy for de novo model completion of macromolecular structures from cryo-EM
        density maps at 3-5-Å resolution. On a benchmark set of nine proteins, RosettaES
        was able to identify near-native conformations in 85% of segments. RosettaES
        was also used to determine models for three challenging macromolecular structures.
      authors:
      - name: Frenz B.
      - name: Walls A.C.
      - name: Egelman E.H.
      - name: Veesler D.
      - name: Di Maio F.
      citationCount: 85
      date: '2017-07-28T00:00:00Z'
      journal: Nature Methods
      title: 'RosettaES: A sampling strategy enabling automated interpretation of
        difficult cryo-EMmaps'
    note: null
    pmcid: PMC6009829
    pmid: '28628127'
    type: []
    version: null
  relation: []
  toolType:
  - Plug-in
  topic:
  - term: Structure analysis
    uri: http://edamontology.org/topic_0081
  - term: Electron microscopy
    uri: http://edamontology.org/topic_0611
  - term: Structural biology
    uri: http://edamontology.org/topic_1317
  validated: 1
  version: []
- accessibility: null
  additionDate: '2018-07-11T10:55:58Z'
  biotoolsCURIE: biotools:unres
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  cost: null
  credit:
  - email: cezary.czaplewski@ug.edu.pl
    fundrefid: null
    gridid: null
    name: Cezary Czaplewski
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  - email: adam.liwo@ug.edu.pl
    fundrefid: null
    gridid: null
    name: Adam Liwo
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
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    url: null
  description: A server implementation of the UNRES package for coarse-grained simulations
    of protein structures with the physics-based UNRES model. It can be used in simulations,
    including those aimed at protein-structure prediction, without ancillary information
    from structural databases; however, the implementation includes the possibility
    of using restraints. Local energy minimization, canonical molecular dynamics simulations,
    replica exchange and multiplexed replica exchange molecular dynamics simulations
    can be run
  documentation:
  - note: null
    type:
    - Training material
    url: http://unres-server.chem.ug.edu.pl/tutorial
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    note: null
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      format:
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    - data:
        term: Protein sequence
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      format:
      - term: Textual format
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    note: null
    operation:
    - term: Ab initio structure prediction
      uri: http://edamontology.org/operation_0476
    output:
    - data:
        term: Protein structure report
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      format: []
  homepage: http://unres-server.chem.ug.edu.pl/
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  publication:
  - doi: 10.1093/nar/gky328
    metadata:
      abstract: A server implementation of the UNRES package (http://www.unres.pl)
        for coarse-grained simulations of protein structures with the physics-based
        UNRES model, coined a name UNRES server, is presented. In contrast to most
        of the protein coarsegrained models, owing to its physics-based origin, the
        UNRES force field can be used in simulations, including those aimed at protein-structure
        prediction, without ancillary information from structural databases; however,
        the implementation includes the possibility of using restraints. Local energy
        minimization, canonical molecular dynamics simulations, replica exchange and
        multiplexed replica exchange molecular dynamics simulations can be run with
        the current UNRES server; the latter are suitable for protein-structure prediction.
        The user-supplied input includes protein sequence and, optionally, restraints
        from secondary-structure prediction or small x-ray scattering data, and simulation
        type and parameters which are selected or typed in. Oligomeric proteins, as
        well as those containing D-amino-acid residues and disulfide links can be
        treated. The output is displayed graphically (minimized structures, trajectories,
        final models, analysis of trajectory/ensembles); however, all output files
        can be downloaded by the user.
      authors:
      - name: Czaplewski C.
      - name: Karczynska A.
      - name: Sieradzan A.K.
      - name: Liwo A.
      citationCount: 51
      date: '2018-07-02T00:00:00Z'
      journal: Nucleic Acids Research
      title: UNRES server for physics-based coarse-grained simulations and prediction
        of protein structure, dynamics and thermodynamics
    note: null
    pmcid: PMC6031057
    pmid: '29718313'
    type: []
    version: null
  relation: []
  toolType:
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  topic:
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  - term: Protein folds and structural domains
    uri: http://edamontology.org/topic_0736
  - term: NMR
    uri: http://edamontology.org/topic_0593
  validated: 1
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- accessibility: null
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    name: European Commission seventh Framework Programme FP7-HEALTH-2013-INNOVATION-1,
      PDE4NPD (no. 602666)
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  description: The database revolves around the protein structure of catalytic PDE
    domains and the way PDE inhibitors can interact with them. It contains a systematic
    analysis of all phosphodiesterase (PDE) catalytic domain crystal structures present
    in the Protein Data Bank (PDB) with a focus on PDE-ligand interactions.
  documentation:
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    type:
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    - General
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    - data:
        term: Protein sequence record
        uri: http://edamontology.org/data_2886
      format:
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        uri: http://edamontology.org/format_2554
    note: Structures of catalytic kinase domains Sequences of catalytic kinase domains
      (UniProt)
    operation:
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      uri: http://edamontology.org/operation_0570
    - term: Residue interaction calculation
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    - term: ID mapping
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    - term: Protein interaction prediction
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    - term: Protein property calculation
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    - term: 3D profile generation
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    - term: Structure alignment
      uri: http://edamontology.org/operation_0295
    - term: Structure analysis
      uri: http://edamontology.org/operation_2480
    - term: Protein flexibility and motion analysis
      uri: http://edamontology.org/operation_0244
    - term: Data retrieval
      uri: http://edamontology.org/operation_2422
    - term: Structure classification
      uri: http://edamontology.org/operation_2996
    - term: Sequence visualisation
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    - term: Protein-ligand docking
      uri: http://edamontology.org/operation_0482
    - term: Structure database search
      uri: http://edamontology.org/operation_0339
    - term: Structural similarity search
      uri: http://edamontology.org/operation_0360
    - term: Data handling
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    - term: Sequence alignment
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    - term: Protein structure comparison
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    output:
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      format: []
    - data:
        term: Chemical structure image
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      format: []
    - data:
        term: Database cross-mapping
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      format: []
    - data:
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      format: []
    - data:
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      format: []
    - data:
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      format: []
    - data:
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      format: []
    - data:
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      format: []
    - data:
        term: Protein-ligand complex
        uri: http://edamontology.org/data_1461
      format: []
    - data:
        term: Protein property
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      format: []
    - data:
        term: Protein structure image
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      format: []
    - data:
        term: Protein structure report
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      format: []
    - data:
        term: Sequence-structure alignment
        uri: http://edamontology.org/data_0893
      format: []
    - data:
        term: Small molecule structure
        uri: http://edamontology.org/data_1463
      format: []
    - data:
        term: Structure alignment (protein)
        uri: http://edamontology.org/data_1481
      format: []
    - data:
        term: Structural (3D) profile alignment
        uri: http://edamontology.org/data_0890
      format: []
    - data:
        term: Structural profile
        uri: http://edamontology.org/data_0889
      format: []
    - data:
        term: Structure similarity score
        uri: http://edamontology.org/data_0888
      format: []
    - data:
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        uri: http://edamontology.org/data_1498
      format: []
  homepage: http://pdestrian.vu-compmedchem.nl
  homepage_status: 0
  language: []
  lastUpdate: '2024-11-25T14:26:17.670147Z'
  license: null
  link: []
  maturity: Mature
  name: PDEStrIAn
  operatingSystem:
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  - Windows
  - Mac
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  owner: a.j.kooistra@vu.nl
  publication:
  - doi: 10.1021/acs.jmedchem.5b01813
    metadata:
      abstract: A systematic analysis is presented of the 220 phosphodiesterase (PDE)
        catalytic domain crystal structures present in the Protein Data Bank (PDB)
        with a focus on PDE-ligand interactions. The consistent structural alignment
        of 57 PDE ligand binding site residues enables the systematic analysis of
        PDE-ligand interaction fingerprints (IFPs), the identification of subtype-specific
        PDE-ligand interaction features, and the classification of ligands according
        to their binding modes. We illustrate how systematic mining of this phosphodiesterase
        structure and ligand interaction annotated (PDEStrIAn) database provides new
        insights into how conserved and selective PDE interaction hot spots can accommodate
        the large diversity of chemical scaffolds in PDE ligands. A substructure analysis
        of the cocrystallized PDE ligands in combination with those in the ChEMBL
        database provides a toolbox for scaffold hopping and ligand design. These
        analyses lead to an improved understanding of the structural requirements
        of PDE binding that will be useful in future drug discovery studies.
      authors:
      - name: Jansen C.
      - name: Kooistra A.J.
      - name: Kanev G.K.
      - name: Leurs R.
      - name: De Esch I.J.P.
      - name: De Graaf C.
      citationCount: 56
      date: '2016-08-11T00:00:00Z'
      journal: Journal of Medicinal Chemistry
      title: 'PDEStrIAn: A Phosphodiesterase Structure and Ligand Interaction Annotated
        Database As a Tool for Structure-Based Drug Design'
    note: null
    pmcid: null
    pmid: '26908025'
    type:
    - Primary
    version: null
  relation: []
  toolType:
  - Command-line tool
  - Web application
  - Web API
  - Database portal
  topic:
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    uri: http://edamontology.org/topic_3369
  - term: Cheminformatics
    uri: http://edamontology.org/topic_2258
  - term: Computational chemistry
    uri: http://edamontology.org/topic_3332
  - term: Drug discovery
    uri: http://edamontology.org/topic_3336
  - term: Medicinal chemistry
    uri: http://edamontology.org/topic_0209
  - term: Medicine
    uri: http://edamontology.org/topic_3303
  - term: Molecular interactions, pathways and networks
    uri: http://edamontology.org/topic_0602
  - term: Protein binding sites
    uri: http://edamontology.org/topic_3534
  - term: Protein interactions
    uri: http://edamontology.org/topic_0128
  - term: Protein sites, features and motifs
    uri: http://edamontology.org/topic_3510
  - term: Protein structure analysis
    uri: http://edamontology.org/topic_2814
  - term: Small molecules
    uri: http://edamontology.org/topic_0154
  - term: Structural biology
    uri: http://edamontology.org/topic_1317
  - term: Structural genomics
    uri: http://edamontology.org/topic_0122
  validated: 1
  version: []
- accessibility: null
  additionDate: '2015-01-22T11:49:01Z'
  biotoolsCURIE: biotools:proabc
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    name: ELIXIR-ITA-SAPIENZA
    note: null
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  - email: pierpaolo.olimpieri@gmail.com
    fundrefid: null
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    name: Pier Paolo Olimpieri
    note: null
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    typeEntity: Person
    typeRole:
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    url: null
  description: Predictor of Antibody-Antigen interactions based on the Random Forest
    Algorithm. User submitted sequences are automatically aligned and annotated according
    to their source organism and germline families.
  documentation:
  - note: null
    type:
    - General
    url: http://circe.med.uniroma1.it/proABC/help_proABC.php
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  function:
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    input:
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    note: 'proABC estimates the residue-based probability for three different kind
      of interactions: Non-bonded Interactions, Hydrogen Bonds and Hydrophobic Interactions.'
    operation:
    - term: Protein interaction prediction
      uri: http://edamontology.org/operation_2492
    - term: Protein structure prediction
      uri: http://edamontology.org/operation_0474
    output:
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        term: Protein interaction data
        uri: http://edamontology.org/data_0906
      format: []
  homepage: http://www.biocomputing.it/proABC
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  name: proABC
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  owner: ELIXIR-ITA-SAPIENZA
  publication:
  - doi: 10.1093/bioinformatics/btt369
    metadata:
      abstract: 'Motivation: Antibodies or immunoglobulins are proteins of paramount
        importance in the immune system. They are extremely relevant as diagnostic,
        biotechnological and therapeutic tools. Their modular structure makes it easy
        to re-engineer them for specific purposes. Short of undergoing a trial and
        error process, these experiments, as well as others, need to rely on an understanding
        of the specific determinants of the antibody binding mode. Results: In this
        article, we present a method to identify, on the basis of the antibody sequence
        alone, which residues of an antibody directly interact with its cognate antigen.
        The method, based on the random forest automatic learning techniques, reaches
        a recall and specificity as high as 80% and is implemented as a free and easy-to-use
        server, named prediction of Antibody Contacts. We believe that it can be of
        great help in re-design experiments as well as a guide for molecular docking
        experiments. The results that we obtained also allowed us to dissect which
        features of the antibody sequence contribute most to the involvement of specific
        residues in binding to the antigen. © The Author 2013.'
      authors:
      - name: Olimpieri P.P.
      - name: Chailyan A.
      - name: Tramontano A.
      - name: Marcatili P.
      citationCount: 77
      date: '2013-09-15T00:00:00Z'
      journal: Bioinformatics
      title: 'Prediction of site-specific interactions in antibody-antigen complexes:
        The proABC method and server'
    note: null
    pmcid: PMC3753563
    pmid: '23803466'
    type:
    - Primary
    version: null
  relation: []
  toolType:
  - Web application
  topic:
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    uri: http://edamontology.org/topic_0081
  validated: 1
  version:
  - '1.0'
- accessibility: null
  additionDate: '2016-02-17T09:43:56Z'
  biotoolsCURIE: biotools:stitch
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    name: SUND-KU
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    url: http://healthsciences.ku.dk/
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    url: http://ec.europa.eu/research/index.cfm
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    url: http://www.biotec.tu-dresden.de/
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    note: null
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    name: Michael Kuhn
    note: null
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    typeRole:
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    url: http://stitch1.embl.de/cgi/show_info_page.pl
  - email: null
    fundrefid: null
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    url: http://stitch1.embl.de/cgi/show_info_page.pl
  description: Resource to explore known and predicted interactions of chemicals and
    proteins. Chemicals are linked to other chemicals and proteins by evidence derived
    from experiments, databases and the literature.
  documentation:
  - note: null
    type:
    - General
    url: http://stitch.embl.de/cgi/show_info_page.pl?UserId=pRfi11Qlkhnx&sessionId=sEfmbh_T7QLq
  download: []
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  function:
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    input:
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        uri: http://edamontology.org/data_2299
      format:
      - term: Textual format
        uri: http://edamontology.org/format_2330
    - data:
        term: Small molecule structure
        uri: http://edamontology.org/data_1463
      format:
      - term: InChIKey
        uri: http://edamontology.org/format_1199
      - term: SMILES
        uri: http://edamontology.org/format_1196
      - term: xls
        uri: http://edamontology.org/format_3468
    - data:
        term: Protein name
        uri: http://edamontology.org/data_1009
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        uri: http://edamontology.org/format_2330
    - data:
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      format:
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        uri: http://edamontology.org/format_2330
    - data:
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        uri: http://edamontology.org/data_2976
      format:
      - term: FASTA-like
        uri: http://edamontology.org/format_2546
    note: STITCH is a database of protein – chemical interactions that integrates
      many sources of experimental and manually curated evidence with text-mining
      information and interaction predictions. Its key function is to provide users
      with predictions about the interactions that their entities of interest (proteins
      or small molecules) may be making with other such entities, and to visualise
      where a set of entities of interest can be found within the STITCH network.
      Direct traceable links to the original sources on which interactions are described
      in the network, make it easy for users to trace the provenance of the data.
    operation:
    - term: Database search
      uri: http://edamontology.org/operation_2421
    - term: Pathway or network visualisation
      uri: http://edamontology.org/operation_3083
    - term: Pathway or network analysis
      uri: http://edamontology.org/operation_2497
    - term: Prediction and recognition
      uri: http://edamontology.org/operation_2423
    output:
    - data:
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        uri: http://edamontology.org/data_2600
      format:
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        uri: http://edamontology.org/format_2330
      - term: Image format
        uri: http://edamontology.org/format_3547
    - data:
        term: Database cross-mapping
        uri: http://edamontology.org/data_0954
      format:
      - term: Textual format
        uri: http://edamontology.org/format_2330
    - data:
        term: Evidence
        uri: http://edamontology.org/data_2042
      format:
      - term: Textual format
        uri: http://edamontology.org/format_2330
  homepage: http://stitch.embl.de/
  homepage_status: 0
  language: []
  lastUpdate: '2024-11-25T14:25:13.779770Z'
  license: null
  link: []
  maturity: null
  name: STITCH
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: hdhub
  publication:
  - doi: 10.1093/nar/gkm795
    metadata:
      abstract: The knowledge about interactions between proteins and small molecules
        is essential for the understanding of molecular and cellular functions. However,
        information on such interactions is widely dispersed across numerous databases
        and the literature. To facilitate access to this data, STITCH ('search tool
        for interactions of chemicals') integrates information about interactions
        from metabolic pathways, crystal structures, binding experiments and drug-target
        relationships. Inferred information from phenotypic effects, text mining and
        chemical structure similarity is used to predict relations between chemicals.
        STITCH further allows exploring the network of chemical relations, also in
        the context of associated binding proteins. Each proposed interaction can
        be traced back to the original data sources. Our database contains interaction
        information for over 68 000 different chemicals, including 2200 drugs, and
        connects them to 1.5 million genes across 373 genomes and their interactions
        contained in the STRING database. STITCH is available at http://stitch.embl.de/.
        © 2007 The Author(s).
      authors:
      - name: Kuhn M.
      - name: von Mering C.
      - name: Campillos M.
      - name: Jensen L.J.
      - name: Bork P.
      citationCount: 754
      date: '2008-01-01T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'STITCH: Interaction networks of chemicals and proteins'
    note: null
    pmcid: PMC2238848
    pmid: '18084021'
    type:
    - Primary
    version: null
  - doi: 10.1093/nar/gkp937
    metadata:
      abstract: Over the last years, the publicly available knowledge on interactions
        between small molecules and proteins has been steadily increasing. To create
        a network of interactions, STITCH aims to integrate the data dispersed over
        the literature and various databases of biological pathways, drug-target relationships
        and binding affinities. In STITCH 2, the number of relevant interactions is
        increased by incorporation of BindingDB, PharmGKB and the Comparative Toxicogenomics
        Database. The resulting network can be explored interactively or used as the
        basis for large-scale analyses. To facilitate links to other chemical databases,
        we adopt InChIKeys that allow identification of chemicals with a short, checksum-like
        string. STITCH 2.0 connects proteins from 630 organisms to over 74 000 different
        chemicals, including 2200 drugs. STITCH can be accessed at http://stitch.embl.de/.
        © The Author(s) 2009. Published by Oxford University Press.
      authors:
      - name: Kuhn M.
      - name: Szklarczyk D.
      - name: Franceschini A.
      - name: Campillos M.
      - name: Von Mering C.
      - name: Jensen L.J.
      - name: Beyer A.
      - name: Bork P.
      citationCount: 231
      date: '2009-11-06T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'STITCH 2: An interaction network database for small molecules and proteins'
    note: null
    pmcid: PMC2808890
    pmid: '19897548'
    type:
    - Other
    version: null
  - doi: 10.1093/nar/gkt1207
    metadata:
      abstract: STITCH is a database of protein-chemical interactions that integrates
        many sources of experimental and manually curated evidence with text-mining
        information and interaction predictions. Available at http://stitch.embl.de,
        the resulting interaction network includes 390 000 chemicals and 3.6 million
        proteins from 1133 organisms. Compared with the previous version, the number
        of high-confidence protein-chemical interactions in human has increased by
        45%, to 367 000. In this version, we added features for users to upload their
        own data to STITCH in the form of internal identifiers, chemical structures
        or quantitative data. For example, a user can now upload a spreadsheet with
        screening hits to easily check which interactions are already known. To increase
        the coverage of STITCH, we expanded the text mining to include full-text articles
        and added a prediction method based on chemical structures. We further changed
        our scheme for transferring interactions between species to rely on orthology
        rather than protein similarity. This improves the performance within protein
        families, where scores are now transferred only to orthologous proteins, but
        not to paralogous proteins. STITCH can be accessed with a web-interface, an
        API and downloadable files. © 2013 The Author(s). Published by Oxford University
        Press.
      authors:
      - name: Kuhn M.
      - name: Szklarczyk D.
      - name: Pletscher-Frankild S.
      - name: Blicher T.H.
      - name: Von Mering C.
      - name: Jensen L.J.
      - name: Bork P.
      citationCount: 413
      date: '2014-01-01T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'STITCH 4: Integration of protein-chemical interactions with user data'
    note: null
    pmcid: PMC3964996
    pmid: '24293645'
    type:
    - Other
    version: null
  - doi: 10.1093/nar/gkr1011
    metadata:
      abstract: To facilitate the study of interactions between proteins and chemicals,
        we have created STITCH, an aggregated database of interactions connecting
        over 300 000 chemicals and 2.6 million proteins from 1133 organisms. Compared
        to the previous version, the number of chemicals with interactions and the
        number of high-confidence interactions both increase 4-fold. The database
        can be accessed interactively through a web interface, displaying interactions
        in an integrated network view. It is also available for computational studies
        through downloadable files and an API. As an extension in the current version,
        we offer the option to switch between two levels of detail, namely whether
        stereoisomers of a given compound are shown as a merged entity or as separate
        entities. Separate display of stereoisomers is necessary, for example, for
        carbohydrates and chiral drugs. Combining the isomers increases the coverage,
        as interaction databases and publications found through text mining will often
        refer to compounds without specifying the stereoisomer. The database is accessible
        at http://stitch.embl.de/. © The Author(s) 2011.
      authors:
      - name: Kuhn M.
      - name: Szklarczyk D.
      - name: Franceschini A.
      - name: Von Mering C.
      - name: Jensen L.J.
      - name: Bork P.
      citationCount: 250
      date: '2012-01-01T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'STITCH 3: Zooming in on protein-chemical interactions'
    note: null
    pmcid: PMC3245073
    pmid: '22075997'
    type:
    - Other
    version: null
  relation: []
  toolType:
  - Command-line tool
  - Web application
  - Database portal
  topic:
  - term: Chemistry
    uri: http://edamontology.org/topic_3314
  - term: Biomedical science
    uri: http://edamontology.org/topic_3344
  - term: Molecular interactions, pathways and networks
    uri: http://edamontology.org/topic_0602
  validated: 1
  version: []
- accessibility: null
  additionDate: '2016-04-22T12:06:06Z'
  biotoolsCURIE: biotools:modlink
  biotoolsID: modlink
  collectionID: []
  confidence_flag: null
  cost: null
  credit:
  - email: null
    fundrefid: null
    gridid: null
    name: Jordi Espadaler
    note: null
    orcidid: http://orcid.org/0000-0002-0128-8363
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Oriol Fornes
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Developer
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: upf.edu
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
    - Provider
    url: null
  - email: baldo.oliva@upf.edu
    fundrefid: null
    gridid: null
    name: null
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  description: A tool predicts protein fold domain and family by means of sequence
    similarity and a relevant number of similar interactions (the same partners or
    is potential homologs).
  documentation:
  - note: null
    type:
    - General
    url: http://sbi.imim.es/modlink/modlinkhelp.html
  download: []
  editPermission:
    authors: []
    type: private
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Protein sequence (raw)
        uri: http://edamontology.org/data_2974
      format:
      - term: unambiguous pure protein
        uri: http://edamontology.org/format_1218
    note: null
    operation:
    - term: Protein structure prediction
      uri: http://edamontology.org/operation_0474
    output: []
  homepage: http://sbi.imim.es/modlink/
  homepage_status: 0
  language: []
  lastUpdate: '2024-11-25T14:24:59.636711Z'
  license: null
  link: []
  maturity: null
  name: ModLink+
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: baldo.oliva@upf.edu
  publication:
  - doi: 10.1093/bioinformatics/btp238
    metadata:
      abstract: 'Motivation: Several strategies have been developed to predict the
        fold of a target protein sequence, most of which are based on aligning the
        target sequence to other sequences of known structure. Previously, we demonstrated
        that the consideration of protein-protein interactions significantly increases
        the accuracy of fold assignment compared with PSI-BLAST sequence comparisons.
        A drawback of our method was the low number of proteins to which a fold could
        be assigned. Here, we present an improved version of the method that addresses
        this limitation. We also compare our method to other state-of-the-art fold
        assignment methodologies. Results: Our approach (ModLink+) has been tested
        on 3716 proteins with domain folds classified in the Structural Classification
        Of Proteins (SCOP) as well as known interacting partners in the Database of
        Interacting Proteins (DIP). For this test set, the ratio of success [positive
        predictive value (PPV)] on fold assignment increases from 75% for PSI-BLAST,
        83% for HHSearch and 81% for PRC to >90% for ModLink+at the e-value cutoff
        of 10-3. Under this e-value, ModLink+can assign a fold to 30-45% of the proteins
        in the test set, while our previous method could cover <25%. When applied
        to 6384 proteins with unknown fold in the yeast proteome, ModLink+combined
        with PSI-BLAST assigns a fold for domains in 3738 proteins, while PSI-BLAST
        alone covers only 2122 proteins, HHSearch 2969 and PRC 2826 proteins, using
        a threshold e-value that would represent a PPV >82% for each method in the
        test set. © The Author 2009. Published by Oxford University Press. All rights
        reserved.'
      authors:
      - name: Fornes O.
      - name: Aragues R.
      - name: Espadaler J.
      - name: Marti-Renom M.A.
      - name: Sali A.
      - name: Oliva B.
      citationCount: 14
      date: '2009-06-09T00:00:00Z'
      journal: Bioinformatics
      title: 'ModLink+: Improving fold recognition by using protein-protein interactions'
    note: null
    pmcid: PMC2687990
    pmid: '19357100'
    type:
    - Primary
    version: null
  - doi: 10.1073/pnas.0500831102
    metadata:
      abstract: The function of an uncharacterized protein is usually inferred either
        from its homology to, or its interactions with, characterized proteins. Here,
        we use both sequence similarity and protein interactions to identify relationships
        between remotely related protein sequences. We rely on the fact that homologous
        sequences share similar interactions, and, therefore, the set of interacting
        partners of the partners of a given protein is enriched by its homologs. The
        approach was benchmarked by assigning the fold and functional family to test
        sequences of known structure. Specifically, we relied on 1,434 proteins with
        known folds, as defined in the Structural Classification of Proteins (SCOP)
        database, and with known interacting partners, as defined in the Database
        of Interacting Proteins (DIP). For this subset, the specificity of fold assignment
        was increased from 54% for position-specific iterative BLAST to 75% for our
        approach, with a concomitant increase in sensitivity for a few percentage
        points. Similarly, the specificity of family assignment at the e-value threshold
        of 10-8 was increased from 70% to 87%. The proposed method would be a useful
        tool for large-scale automated discovery of remote relationships between protein
        sequences, given its unique reliance on sequence similarity and protein-protein
        interactions. © 2005 by The National Academy of Sciences of the USA.
      authors:
      - name: Espadaler J.
      - name: Aragues R.
      - name: Eswar N.
      - name: Marti-Renom M.A.
      - name: Querol E.
      - name: Aviles F.X.
      - name: Sali A.
      - name: Oliva B.
      citationCount: 24
      date: '2005-05-17T00:00:00Z'
      journal: Proceedings of the National Academy of Sciences of the United States
        of America
      title: Detecting remotely related proteins by their interactions and sequence
        similarity
    note: null
    pmcid: PMC1129109
    pmid: '15883372'
    type:
    - Other
    version: null
  relation: []
  toolType:
  - Web API
  topic:
  - term: Protein folds and structural domains
    uri: http://edamontology.org/topic_0736
  validated: 1
  version:
  - '1'
- accessibility: null
  additionDate: '2018-03-12T09:31:50Z'
  biotoolsCURIE: biotools:soda-solubility
  biotoolsID: soda-solubility
  collectionID: []
  confidence_flag: null
  cost: null
  credit:
  - email: null
    fundrefid: null
    gridid: null
    name: University of Padua, Department of Biomedical Sciences, BioComputing UP
      lab
    note: null
    orcidid: null
    rorid: null
    typeEntity: null
    typeRole: []
    url: http://protein.bio.unipd.it/
  - email: null
    fundrefid: null
    gridid: null
    name: ELIXIR-ITA-PADOVA
    note: null
    orcidid: null
    rorid: null
    typeEntity: null
    typeRole: []
    url: http://elixir.bio.unipd.it/
  - email: silvio.tosatto@unipd.it
    fundrefid: null
    gridid: null
    name: Silvio C.E. Tosatto
    note: null
    orcidid: http://orcid.org/0000-0003-4525-7793
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: http://protein.bio.unipd.it
  description: Protein SOlubility based on Disorder and Aggregation
  documentation:
  - note: null
    type:
    - General
    url: http://protein.bio.unipd.it/soda/help
  download: []
  editPermission:
    authors: []
    type: private
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Protein sequence
        uri: http://edamontology.org/data_2976
      format:
      - term: FASTA
        uri: http://edamontology.org/format_1929
    note: null
    operation:
    - term: Protein secondary structure prediction
      uri: http://edamontology.org/operation_0267
    - term: Protein feature detection
      uri: http://edamontology.org/operation_3092
    output:
    - data:
        term: Protein features
        uri: http://edamontology.org/data_1277
      format:
      - term: JSON
        uri: http://edamontology.org/format_3464
      - term: HTML
        uri: http://edamontology.org/format_2331
      - term: TSV
        uri: http://edamontology.org/format_3475
  homepage: http://protein.bio.unipd.it/soda/
  homepage_status: 0
  language:
  - Python
  lastUpdate: '2024-11-25T14:23:38.672551Z'
  license: CC-BY-NC-ND-4.0
  link: []
  maturity: Mature
  name: SODA
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: ELIXIR-ITA-PADOVA
  publication:
  - doi: 10.1093/nar/gkx412
    metadata:
      abstract: Solubility is an important, albeit not well understood, feature determining
        protein behavior. It is of paramount importance in protein engineering, where
        similar folded proteins may behave in very different ways in solution. Here
        we present SODA, a novel method to predict the changes of protein solubility
        based on several physico-chemical properties of the protein. SODA uses the
        propensity of the protein sequence to aggregate as well as intrinsic disorder,
        plus hydrophobicity and secondary structure preferences to estimate changes
        in solubility. It has been trained and benchmarked on two different datasets.
        The comparison to other recently published methods shows that SODA has state-of-the-art
        performance and is particularly well suited to predict mutations decreasing
        solubility. The method is fast, returning results for single mutations in
        seconds. A usage example estimating the full repertoire of mutations for a
        human germline antibody highlights several solubility hotspots on the surface.
      authors:
      - name: Paladin L.
      - name: Piovesan D.
      - name: Tosatto S.C.E.
      citationCount: 47
      date: '2017-07-03T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'SODA: Prediction of protein solubility from disorder and aggregation
        propensity'
    note: null
    pmcid: PMC7059794
    pmid: '28505312'
    type:
    - Primary
    version: null
  relation: []
  toolType:
  - Web API
  - Web application
  topic:
  - term: Protein sites, features and motifs
    uri: http://edamontology.org/topic_3510
  - term: Protein disordered structure
    uri: http://edamontology.org/topic_3538
  - term: Protein structure analysis
    uri: http://edamontology.org/topic_2814
  validated: 1
  version:
  - '1.0'
next: ?page=2
previous: null
