count: 1106
list:
- accessibility: null
  additionDate: '2024-03-12T13:48:56.972279Z'
  biotoolsCURIE: biotools:clinod
  biotoolsID: clinod
  collectionID: []
  community: null
  confidence_flag: null
  cost: null
  credit: []
  description: 'The command line NoD predictor (clinod) can be run from the command
    line to predict Nucleolar localization sequences (NoLSs) that are short targeting
    sequences responsible for the localization of proteins to the nucleolus.

    The predictor accepts a list of FASTA formatted sequences as an input and outputs
    the NOLS predictions as a result.

    Please note that currently, JPred secondary structure predictions are not supported
    by clinod. However, we are working on it.'
  documentation: []
  download: []
  editPermission:
    authors: []
    type: private
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Nucleic acid sequence analysis
      uri: http://edamontology.org/operation_2478
    output: []
  homepage: https://www.compbio.dundee.ac.uk/www-nod/cli_help.jsp
  homepage_status: 0
  language: []
  lastUpdate: '2024-03-12T13:48:56.975036Z'
  license: null
  link: []
  maturity: null
  name: clinod
  operatingSystem: []
  otherID: []
  owner: paulzierep
  publication: []
  relation: []
  toolType: []
  topic:
  - term: Sequence analysis
    uri: http://edamontology.org/topic_0080
  validated: 0
  version: []
- accessibility: Open access
  additionDate: '2024-03-12T10:56:44.977314Z'
  biotoolsCURIE: biotools:lorikeet
  biotoolsID: lorikeet
  collectionID: []
  community: null
  confidence_flag: null
  cost: null
  credit: []
  description: Tools for M. tuberculosis DNA fingerprinting (spoligotyping)
  documentation: []
  download: []
  editPermission:
    authors: []
    type: public
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Sequence analysis
      uri: http://edamontology.org/operation_2403
    - term: Genotyping
      uri: http://edamontology.org/operation_3196
    output: []
  homepage: https://github.com/AbeelLab/lorikeet
  homepage_status: 0
  language:
  - Java
  lastUpdate: '2024-03-12T10:56:44.980036Z'
  license: GPL-3.0
  link: []
  maturity: Mature
  name: lorikeet
  operatingSystem: []
  otherID: []
  owner: rlibouban
  publication: []
  relation: []
  toolType:
  - Bioinformatics portal
  topic:
  - term: Genotype and phenotype
    uri: http://edamontology.org/topic_0625
  validated: 0
  version:
  - '20'
- accessibility: null
  additionDate: '2024-03-12T09:39:30.275596Z'
  biotoolsCURIE: biotools:bbtools
  biotoolsID: bbtools
  collectionID: []
  community: null
  confidence_flag: null
  cost: null
  credit: []
  description: 'BBTools is a suite of fast, multithreaded bioinformatics tools designed
    for analysis of DNA and RNA sequence data. BBTools can handle common sequencing
    file formats such as fastq, fasta, sam, scarf, fasta+qual, compressed or raw,
    with autodetection of quality encoding and interleaving. It is written in Java
    and works on any platform supporting Java, including Linux, MacOS, and Microsoft
    Windows and Linux; there are no dependencies other than Java (version 7 or higher).
    Program descriptions and options are shown when running the shell scripts with
    no parameters.


    BBTools is open source and free for unlimited use, and is used regularly by DOE
    JGI and other institutions around the world.'
  documentation: []
  download: []
  editPermission:
    authors: []
    type: private
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  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Sequence analysis
      uri: http://edamontology.org/operation_2403
    output: []
  homepage: https://jgi.doe.gov/data-and-tools/software-tools/bbtools/
  homepage_status: 0
  language: []
  lastUpdate: '2024-03-12T09:39:30.279447Z'
  license: null
  link: []
  maturity: null
  name: BBTools
  operatingSystem: []
  otherID: []
  owner: paulzierep
  publication: []
  relation: []
  toolType:
  - Suite
  topic:
  - term: Sequence analysis
    uri: http://edamontology.org/topic_0080
  validated: 0
  version: []
- accessibility: Open access
  additionDate: '2016-05-04T15:36:53Z'
  biotoolsCURIE: biotools:inps-md
  biotoolsID: inps-md
  collectionID:
  - Rare Disease
  - Bologna Biocomputing Group
  community: null
  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: http://www.biocomp.unibo.it
  - 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:
    - 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/inpsSuite
  download: []
  editPermission:
    authors:
    - ELIXIR-ITA-BOLOGNA
    - savo
    type: group
  elixirCommunity:
  - 3D-BioInfo
  elixirNode:
  - Italy
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Protein sequence (raw)
        uri: http://edamontology.org/data_2974
      format:
      - term: FASTA
        uri: http://edamontology.org/format_1929
    note: Prediction of the impact of non-synonymous polymorphisms on protein stability
      from sequence.
    operation:
    - term: Protein sequence analysis
      uri: http://edamontology.org/operation_2479
    - term: Genetic variation analysis
      uri: http://edamontology.org/operation_3197
    output:
    - data:
        term: Protein report
        uri: http://edamontology.org/data_0896
      format:
      - term: HTML
        uri: http://edamontology.org/format_2331
  - cmd: null
    input:
    - data:
        term: Protein structure
        uri: http://edamontology.org/data_1460
      format:
      - term: PDB
        uri: http://edamontology.org/format_1476
    - data:
        term: Polypeptide chain ID
        uri: http://edamontology.org/data_1008
      format:
      - term: Textual format
        uri: http://edamontology.org/format_2330
    note: Prediction of the impact of non-synonymous polymorphisms on protein stability
      from structure.
    operation:
    - term: Protein structure analysis
      uri: http://edamontology.org/operation_2406
    - term: Genetic variation analysis
      uri: http://edamontology.org/operation_3197
    output:
    - data:
        term: Protein report
        uri: http://edamontology.org/data_0896
      format:
      - term: HTML
        uri: http://edamontology.org/format_2331
    - data:
        term: Protein structure
        uri: http://edamontology.org/data_1460
      format:
      - term: PDB
        uri: http://edamontology.org/format_1476
  homepage: http://inpsmd.biocomp.unibo.it
  homepage_status: 0
  language: []
  lastUpdate: '2024-03-11T16:56:00.844792Z'
  license: null
  link: []
  maturity: Mature
  name: INPS-MD
  operatingSystem:
  - Linux
  - Windows
  - Mac
  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: 94
      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: 147
      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:
  - Web application
  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: '2024-03-11T16:40:14.136794Z'
  biotoolsCURIE: biotools:legsta
  biotoolsID: legsta
  collectionID: []
  community: null
  confidence_flag: null
  cost: Free of charge
  credit: []
  description: Performs in silico Legionella pneumophila sequence based typing
  documentation: []
  download: []
  editPermission:
    authors: []
    type: public
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Sequence analysis
      uri: http://edamontology.org/operation_2403
    output: []
  homepage: https://github.com/tseemann/legsta
  homepage_status: 0
  language: []
  lastUpdate: '2024-03-11T16:40:14.139298Z'
  license: GPL-3.0
  link: []
  maturity: Mature
  name: legsta
  operatingSystem: []
  otherID: []
  owner: rlibouban
  publication: []
  relation: []
  toolType:
  - Bioinformatics portal
  - Command-line tool
  topic:
  - term: Public health and epidemiology
    uri: http://edamontology.org/topic_3305
  validated: 0
  version:
  - 0.5.1
  - 0.3.7
  - 0.3.2
  - '0.2'
- accessibility: Open access
  additionDate: '2024-03-11T15:00:11.214878Z'
  biotoolsCURIE: biotools:kofamscan
  biotoolsID: kofamscan
  collectionID: []
  community: null
  confidence_flag: null
  cost: Free of charge
  credit: []
  description: KofamScan is a gene function annotation tool based on KEGG Orthology
    and hidden Markov model. You need KOfam database to use this tool.
  documentation: []
  download: []
  editPermission:
    authors: []
    type: public
  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: Sequence analysis
      uri: http://edamontology.org/operation_2403
    - term: Gene functional annotation
      uri: http://edamontology.org/operation_3672
    output: []
  homepage: https://github.com/takaram/kofam_scan
  homepage_status: 0
  language: []
  lastUpdate: '2024-03-11T15:00:11.219298Z'
  license: MIT
  link: []
  maturity: Mature
  name: kofamscan
  operatingSystem: []
  otherID: []
  owner: rlibouban
  publication: []
  relation: []
  toolType:
  - Bioinformatics portal
  - Command-line tool
  - Web application
  topic:
  - term: Genomics
    uri: http://edamontology.org/topic_0622
  validated: 0
  version:
  - 1.3.0
- accessibility: Open access
  additionDate: '2024-03-11T13:25:13.344697Z'
  biotoolsCURIE: biotools:plasflow
  biotoolsID: plasflow
  collectionID: []
  community: null
  confidence_flag: tool
  cost: null
  credit: []
  description: PlasFlow is a set of scripts used for prediction of plasmid sequences
    in metagenomic contigs.
  documentation: []
  download: []
  editPermission:
    authors: []
    type: public
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Sequence analysis
      uri: http://edamontology.org/operation_2403
    output: []
  homepage: https://github.com/smaegol/PlasFlow
  homepage_status: 0
  language: []
  lastUpdate: '2024-03-11T13:25:32.934504Z'
  license: GPL-3.0
  link: []
  maturity: Mature
  name: PlasFlow
  operatingSystem: []
  otherID: []
  owner: rlibouban
  publication: []
  relation: []
  toolType:
  - Bioinformatics portal
  - Command-line tool
  topic:
  - term: Metagenomics
    uri: http://edamontology.org/topic_3174
  validated: 0
  version:
  - '1.1'
- accessibility: Open access
  additionDate: '2024-02-25T14:24:16.153524Z'
  biotoolsCURIE: biotools:deep-avpiden
  biotoolsID: deep-avpiden
  collectionID: []
  community: null
  confidence_flag: tool
  cost: Free of charge
  credit:
  - email: vishakhasingh.rs.cse20@iitbhu.ac.in
    fundrefid: null
    gridid: null
    name: Vishakha Singh
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  - email: sks.cse@iitbhu.ac.in
    fundrefid: null
    gridid: null
    name: Sanjay Kumar Singh
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  description: 'A separable temporal convolutional networks based deep learning technique
    for discovering antiviral medicines.

    The model behind this app is based on Temporal Convolutional Network (TCN). It
    uses the amino acid sequences of a given peptide as input and predicts whether
    the peptide is antifungal or not. The model consists of a word embedding layer,
    a spatial dropout layer, two TCN blocks, a global average pooling layer, a dense
    layer, and a dropout layer.'
  documentation: []
  download: []
  editPermission:
    authors: []
    type: public
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Protein sequence
        uri: http://edamontology.org/data_2976
      format: []
    note: null
    operation:
    - term: Virtual screening
      uri: http://edamontology.org/operation_3938
    - term: Network analysis
      uri: http://edamontology.org/operation_3927
    - term: Protein sequence analysis
      uri: http://edamontology.org/operation_2479
    output: []
  homepage: https://deep-avpiden.anvil.app
  homepage_status: 0
  language: []
  lastUpdate: '2024-02-25T14:24:16.156284Z'
  license: CC-BY-4.0
  link: []
  maturity: null
  name: Deep-AVPiden
  operatingSystem:
  - Mac
  - Linux
  - Windows
  otherID: []
  owner: Pub2Tools
  publication:
  - doi: 10.1038/S41598-023-40922-Y
    metadata:
      abstract: An alarming number of fatalities caused by the COVID-19 pandemic has
        forced the scientific community to accelerate the process of therapeutic drug
        discovery. In this regard, the collaboration between biomedical scientists
        and experts in artificial intelligence (AI) has led to a number of in silico
        tools being developed for the initial screening of therapeutic molecules.
        All living organisms produce antiviral peptides (AVPs) as a part of their
        first line of defense against invading viruses. The Deep-AVPiden model proposed
        in this paper and its corresponding web app, deployed at https://deep-avpiden.anvil.app
        , is an effort toward discovering novel AVPs in proteomes of living organisms.
        Apart from Deep-AVPiden, a computationally efficient model called Deep-AVPiden
        (DS) has also been developed using the same underlying network but with point-wise
        separable convolutions. The Deep-AVPiden and Deep-AVPiden (DS) models show
        an accuracy of 90% and 88%, respectively, and both have a precision of 90%.
        Also, the proposed models were statistically compared using the Student’s
        t-test. On comparing the proposed models with the state-of-the-art classifiers,
        it was found that they are much better than them. To test the proposed model,
        we identified some AVPs in the natural defense proteins of plants, mammals,
        and fishes and found them to have appreciable sequence similarity with some
        experimentally validated antimicrobial peptides. These AVPs can be chemically
        synthesized and tested for their antiviral activity.
      authors:
      - name: Singh V.
      - name: Singh S.K.
      citationCount: 1
      date: '2023-12-01T00:00:00Z'
      journal: Scientific Reports
      title: A separable temporal convolutional networks based deep learning technique
        for discovering antiviral medicines
    note: null
    pmcid: PMC10444765
    pmid: '37608092'
    type: []
    version: null
  relation: []
  toolType:
  - Web application
  topic:
  - term: Machine learning
    uri: http://edamontology.org/topic_3474
  - term: Small molecules
    uri: http://edamontology.org/topic_0154
  - term: Model organisms
    uri: http://edamontology.org/topic_0621
  - term: Proteomics
    uri: http://edamontology.org/topic_0121
  - term: Medicine
    uri: http://edamontology.org/topic_3303
  validated: 0
  version: []
- accessibility: null
  additionDate: '2017-12-18T00:14:19Z'
  biotoolsCURIE: biotools:wise
  biotoolsID: wise
  collectionID: []
  community: null
  confidence_flag: null
  cost: null
  credit:
  - email: null
    fundrefid: null
    gridid: null
    name: null
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: https://www.ebi.ac.uk/support/index.php
  - email: birney@ebi.ac.uk
    fundrefid: null
    gridid: null
    name: Ewan Birney
    note: null
    orcidid: http://orcid.org/0000-0001-8314-8497
    rorid: null
    typeEntity: null
    typeRole: []
    url: null
  description: Compare a protein sequences or protein HMMs to a genomic DNA sequence,
    allowing for introns and frameshifting errors.
  documentation:
  - note: null
    type:
    - General
    url: https://www.ebi.ac.uk/~birney/wise2/
  download:
  - note: null
    type: Software package
    url: https://www.ebi.ac.uk/~birney/wise2/wise2.4.1.tar.gz
    version: null
  editPermission:
    authors:
    - jdispatcher
    type: group
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Protein sequence analysis
      uri: http://edamontology.org/operation_2479
    output: []
  - cmd: null
    input: []
    note: null
    operation:
    - term: Sequence alignment
      uri: http://edamontology.org/operation_0292
    output: []
  homepage: http://www.ebi.ac.uk/Tools/Wise2/
  homepage_status: 0
  language:
  - Perl
  lastUpdate: '2024-02-22T10:19:57.092379Z'
  license: null
  link:
  - note: null
    type:
    - Software catalogue
    url: http://www.mybiosoftware.com/wise-2-2-0-compare-protein-sequence-genomic-dna-sequence.html
  maturity: null
  name: Wise2.4
  operatingSystem:
  - Linux
  otherID: []
  owner: mbs_import
  publication:
  - doi: 10.1101/gr.10.4.547
    metadata:
      abstract: The GeneWise method for combining gene prediction and homology searches
        was applied to the 2.9-Mb region from Drosophila melanogaster. The results
        from the Genome Annotation Assessment Project (GASP) showed that GeneWise
        provided reasonably accurate gene predictions. Further investigation indicates
        that many of the incorrect gene predictions from GeneWise were due to transposons
        with valid protein-coding genes and the remaining cases are pseudogenes or
        possible annotation oversights.
      authors:
      - name: Birney E.
      - name: Durbin R.
      citationCount: 283
      date: '2000-04-01T00:00:00Z'
      journal: Genome Research
      title: Using GeneWise in the Drosophila annotation experiment
    note: null
    pmcid: PMC310858
    pmid: '10779496'
    type:
    - Primary
    version: null
  - doi: null
    metadata:
      abstract: 'We present two algorithms in this paper: GeneWise, which predicts
        gene structure using similar protein sequences, and Genomewise, which provides
        a gene structure final parse across cDNA- and EST-defined spliced structure.
        Both algorithms are heavily used by the Ensembl annotation system. The GeneWise
        algorithm was developed from a principled combination of hidden Markov models
        (HMMs). Both algorithms are highly accurate and can provide both accurate
        and complete gene structures when used with the correct evidence. ©2004 by
        Cold Spring Harbor Laboratory Press.'
      authors:
      - name: Birney E.
      - name: Clamp M.
      - name: Durbin R.
      citationCount: 1775
      date: '2004-05-01T00:00:00Z'
      journal: Genome Research
      title: GeneWise and Genomewise
    note: null
    pmcid: null
    pmid: '15123596'
    type:
    - Primary
    version: null
  relation: []
  toolType:
  - Command-line tool
  topic:
  - term: HMMs
    uri: http://edamontology.org/topic_0160
  - term: DNA
    uri: http://edamontology.org/topic_0654
  validated: 1
  version:
  - 2.4.1
- accessibility: null
  additionDate: '2017-02-10T14:15:37Z'
  biotoolsCURIE: biotools:gpcrsclass
  biotoolsID: gpcrsclass
  collectionID:
  - gpcr
  community: null
  confidence_flag: null
  cost: null
  credit:
  - email: raghava@iiitd.ac.in
    fundrefid: null
    gridid: null
    name: G.P.S. Raghava
    note: Prof Raghava is know to develop open source in bioinformatics
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  description: Tool for predicting amine-binding receptors based on a protein sequence
    provided by the user.
  documentation:
  - note: null
    type:
    - General
    url: http://webs.iiitd.edu.in/raghava/gpcrsclass/help.html
  download: []
  editPermission:
    authors:
    - mbermudez1
    type: group
  elixirCommunity: []
  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input: []
    note: null
    operation:
    - term: Protein sequence analysis
      uri: http://edamontology.org/operation_2479
    - term: Transmembrane protein prediction
      uri: http://edamontology.org/operation_0269
    - term: Protein feature detection
      uri: http://edamontology.org/operation_3092
    output: []
  homepage: http://webs.iiitd.edu.in/raghava/gpcrsclass/
  homepage_status: 0
  language: []
  lastUpdate: '2024-02-15T12:37:17.336664Z'
  license: null
  link: []
  maturity: null
  name: GPCRsclass
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: raghavagps
  publication:
  - doi: null
    metadata:
      abstract: The receptors of amine subfamily are specifically major drug targets
        for therapy of nervous disorders and psychiatric diseases. The recognition
        of novel amine type of receptors and their cognate ligands is of paramount
        interest for pharmaceutical companies. In the past, Chou and co-workers have
        shown that different types of amine receptors are correlated with their amino
        acid composition and are predictable on its basis with considerable accuracy
        [Elrod and Chou (2002) Protein Eng., 15, 713-715]. This motivated us to develop
        a better method for the recognition of novel amine receptors and for their
        further classification. The method was developed on the basis of amino acid
        composition and dipeptide composition of proteins using support vector machine.
        The method was trained and tested on 167 proteins of amine subfamily of G-protein-coupled
        receptors (GPCRs). The method discriminated amine subfamily of GPCRs from
        globular proteins with Matthew's correlation coefficient of 0.98 and 0.99
        using amino acid composition and dipeptide composition, respectively. In classifying
        different types of amine receptors using amino acid composition and dipeptide
        composition, the method achieved an accuracy of 89.8 and 96.4%, respectively.
        The performance of the method was evaluated using 5-fold cross-validation.
        The dipeptide composition based method predicted 67.6% of protein sequences
        with an accuracy of 100% with a reliability index ≥5. A web server GPCRsclass
        has been developed for predicting amine-binding receptors from its amino acid
        sequence [http://www.imtech.res.in/raghava/gpcrsclass/ and http://bioinformatics.uams.edu/raghava/gpersclass/
        (mirror site)]. © 2005 Oxford University Press.
      authors:
      - name: Bhasin M.
      - name: Raghava G.P.S.
      citationCount: 57
      date: '2005-07-01T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'GPCRsclass: A web tool for the classification of amine type of G-protein-coupled
        receptors'
    note: null
    pmcid: null
    pmid: '15980444'
    type: []
    version: null
  relation: []
  toolType:
  - Web application
  topic:
  - term: Proteins
    uri: http://edamontology.org/topic_0078
  - term: Protein sites, features and motifs
    uri: http://edamontology.org/topic_3510
  - term: Sequence composition, complexity and repeats
    uri: http://edamontology.org/topic_0157
  - term: Gene and protein families
    uri: http://edamontology.org/topic_0623
  - term: Structure prediction
    uri: http://edamontology.org/topic_0082
  validated: 1
  version: []
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