count: 896
list:
- accessibility: Open access
  additionDate: '2024-05-05T10:53:14.688391Z'
  biotoolsCURIE: biotools:phiembed
  biotoolsID: phiembed
  collectionID: []
  community: null
  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@dlsu.edu.ph
    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: null
    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:
    - Primary contact
    url: https://a-transposable-element.com/
  description: PHIEmbed is a phage-host interaction prediction tool that uses protein
    language models to represent the receptor-binding proteins of phages. It presents
    improvements over using handcrafted (manually feature-engineered) sequence properties
    and eliminates the need to manually extract and select features from phage sequences.
  documentation:
  - note: null
    type:
    - Installation instructions
    - Quick start guide
    - Citation instructions
    - Command-line options
    url: https://github.com/bioinfodlsu/phage-host-prediction
  download:
  - note: null
    type: Source code
    url: https://github.com/bioinfodlsu/phage-host-prediction
    version: null
  editPermission:
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  function:
  - cmd: null
    input:
    - data:
        term: Protein sequence
        uri: http://edamontology.org/data_2976
      format:
      - term: FASTA
        uri: http://edamontology.org/format_1929
    note: Predicts the host genus of a phage given its receptor-binding protein sequences
    operation:
    - term: Prediction and recognition
      uri: http://edamontology.org/operation_2423
    output:
    - data:
        term: Report
        uri: http://edamontology.org/data_2048
      format:
      - term: CSV
        uri: http://edamontology.org/format_3752
  homepage: https://github.com/bioinfodlsu/phage-host-prediction
  homepage_status: 0
  language:
  - Python
  lastUpdate: '2024-05-05T17:41:24.840808Z'
  license: MIT
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/bioinfodlsu/phage-host-prediction
  maturity: Emerging
  name: PHIEmbed
  operatingSystem:
  - Mac
  - Linux
  - Windows
  otherID: []
  owner: memgonzales
  publication:
  - doi: 10.1371/journal.pone.0289030
    metadata: null
    note: null
    pmcid: PMC10365317
    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: Open access
  additionDate: '2024-04-30T12:28:42.617345Z'
  biotoolsCURIE: biotools:probiominserver
  biotoolsID: probiominserver
  collectionID: []
  community: null
  confidence_flag: tool
  cost: Free of charge
  credit:
  - email: chieh@imst.nsysu.edu.tw
    fundrefid: null
    gridid: null
    name: Chih-Chieh Chen
    note: null
    orcidid: https://orcid.org/0000-0002-5844-8428
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Yen-Yi Liu
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole: []
    url: null
  description: Integrated platform for assessing the safety and functional properties
    of potential probiotic strains.
  documentation: []
  download: []
  editPermission:
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  elixirNode: []
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Genome report
        uri: http://edamontology.org/data_2711
      format:
      - term: FASTA-like (text)
        uri: http://edamontology.org/format_2200
    note: null
    operation:
    - term: Data retrieval
      uri: http://edamontology.org/operation_2422
    - term: Multilocus sequence typing
      uri: http://edamontology.org/operation_3840
    - term: Database search
      uri: http://edamontology.org/operation_2421
    output: []
  homepage: https://probiomindb.imst.nsysu.edu.tw
  homepage_status: 0
  language:
  - JavaScript
  - PHP
  - Perl
  lastUpdate: '2024-04-30T12:28:42.620166Z'
  license: null
  link: []
  maturity: null
  name: ProbioMinServer
  operatingSystem:
  - Mac
  - Linux
  - Windows
  otherID: []
  owner: Pub2Tools
  publication:
  - doi: 10.1093/BIOADV/VBAD153
    metadata:
      abstract: 'Motivation: ProbioMinServer is a platform designed to help researchers
        access information on probiotics regarding a wide variety of characteristics,
        such as safety (e.g. antimicrobial resistance, virulence, pathogenic, plasmid,
        and prophage genes) and functionality (e.g. functional classes, carbohydrate-active
        enzyme, and metabolite gene cluster profile). Because probiotics are functional
        foods, their safety and functionality are a crucial part of health care. Genomics
        has become a crucial methodology for investigating the safety and functionality
        of probiotics in food and feed. This shift is primarily attributed to the
        growing affordability of next-generation sequencing technologies. However,
        no integrated platform is available for simultaneously evaluating probiotic
        strain safety, investigating probiotic functionality, and identifying known
        phylogenetically related strains. Results: Thus, we constructed a new platform,
        ProbioMinServer, which incorporates these functions. ProbioMinServer accepts
        whole-genome sequence files in the FASTA format. If the query genome belongs
        to the 25 common probiotic species collected in our database, the server performs
        a database search and analyzes the core-genome multilocus sequence typing.
        Front-end applications were implemented in JavaScript with a bootstrap framework,
        and back-end programs were implemented using PHP, Perl, and Python. ProbioMinServer
        can help researchers quickly and easily retrieve information on the safety
        and functionality of various probiotics.'
      authors:
      - name: Liu Y.-Y.
      - name: Hsu C.-Y.
      - name: Yang Y.-C.
      - name: Huang C.-H.
      - name: Chen C.-C.
      citationCount: 0
      date: '2023-01-01T00:00:00Z'
      journal: Bioinformatics Advances
      title: 'ProbioMinServer: an integrated platform for assessing the safety and
        functional properties of potential probiotic strains'
    note: null
    pmcid: PMC10625473
    pmid: '37928343'
    type: []
    version: null
  relation: []
  toolType:
  - Web application
  topic:
  - term: Whole genome sequencing
    uri: http://edamontology.org/topic_3673
  - term: Metabolomics
    uri: http://edamontology.org/topic_3172
  - term: Small molecules
    uri: http://edamontology.org/topic_0154
  - term: Phylogenetics
    uri: http://edamontology.org/topic_3293
  - term: Agricultural science
    uri: http://edamontology.org/topic_3810
  validated: 0
  version: []
- accessibility: Open access
  additionDate: '2017-08-20T16:07:58Z'
  biotoolsCURIE: biotools:htslib
  biotoolsID: htslib
  collectionID:
  - Animal and Crop Genomics
  community: null
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: samtools@sanger.ac.uk
    fundrefid: null
    gridid: null
    name: Wellcome Sanger Institute
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
    - Provider
    - Primary contact
    url: https://www.sanger.ac.uk/
  - email: null
    fundrefid: null
    gridid: null
    name: Samtools Help mailing list
    note: null
    orcidid: null
    rorid: null
    typeEntity: Project
    typeRole:
    - Support
    url: https://lists.sourceforge.net/lists/listinfo/samtools-help
  description: The main purpose of HTSlib is to provide access to genomic information
    files, both alignment data (SAM, BAM, and CRAM formats) and variant data (VCF
    and BCF formats). The library also provides interfaces to access and index genome
    reference data in FASTA format and tab-delimited files with genomic coordinates.
    It is utilized and incorporated into both SAMtools and BCFtools.
  documentation:
  - note: null
    type:
    - User manual
    url: http://www.htslib.org/doc/#manual-pages
  download:
  - note: null
    type: Downloads page
    url: http://www.htslib.org/download/
    version: null
  editPermission:
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    type: group
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  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Sequence trace
        uri: http://edamontology.org/data_0924
      format:
      - term: SAM
        uri: http://edamontology.org/format_2573
      - term: BAM
        uri: http://edamontology.org/format_2572
      - term: CRAM
        uri: http://edamontology.org/format_3462
      - term: FASTA
        uri: http://edamontology.org/format_1929
      - term: FASTQ
        uri: http://edamontology.org/format_1930
    - data:
        term: Sequence variations
        uri: http://edamontology.org/data_3498
      format:
      - term: VCF
        uri: http://edamontology.org/format_3016
      - term: BCF
        uri: http://edamontology.org/format_3020
    note: null
    operation:
    - term: Data handling
      uri: http://edamontology.org/operation_2409
    output:
    - data:
        term: Sequence trace
        uri: http://edamontology.org/data_0924
      format:
      - term: SAM
        uri: http://edamontology.org/format_2573
      - term: BAM
        uri: http://edamontology.org/format_2572
      - term: CRAM
        uri: http://edamontology.org/format_3462
      - term: FASTA
        uri: http://edamontology.org/format_1929
      - term: FASTQ
        uri: http://edamontology.org/format_1930
    - data:
        term: Sequence variations
        uri: http://edamontology.org/data_3498
      format:
      - term: VCF
        uri: http://edamontology.org/format_3016
      - term: BCF
        uri: http://edamontology.org/format_3020
  homepage: http://www.htslib.org/
  homepage_status: 0
  language:
  - C
  lastUpdate: '2024-04-16T10:19:42.968075Z'
  license: MIT
  link:
  - note: null
    type:
    - Repository
    url: https://github.com/samtools/htslib
  - note: null
    type:
    - Mailing list
    url: http://www.htslib.org/support/#lists
  - note: null
    type:
    - Issue tracker
    url: https://github.com/samtools/htslib/issues
  maturity: Mature
  name: HTSlib
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: awhitwham
  publication:
  - doi: 10.1093/gigascience/giab007
    metadata:
      abstract: 'Background: Since the original publication of the VCF and SAM formats,
        an explosion of software tools have been created to process these data files.
        To facilitate this a library was produced out of the original SAMtools implementation,
        with a focus on performance and robustness. The file formats themselves have
        become international standards under the jurisdiction of the Global Alliance
        for Genomics and Health. Findings: We present a software library for providing
        programmatic access to sequencing alignment and variant formats. It was born
        out of the widely used SAMtools and BCFtools applications. Considerable improvements
        have been made to the original code plus many new features including newer
        access protocols, the addition of the CRAM file format, better indexing and
        iterators, and better use of threading. Conclusion: Since the original Samtools
        release, performance has been considerably improved, with a BAM read-write
        loop running 5 times faster and BAM to SAM conversion 13 times faster (both
        using 16 threads, compared to Samtools 0.1.19). Widespread adoption has seen
        HTSlib downloaded >1 million times from GitHub and conda. The C library has
        been used directly by an estimated 900 GitHub projects and has been incorporated
        into Perl, Python, Rust, and R, significantly expanding the number of uses
        via other languages. HTSlib is open source and is freely available from htslib.org
        under MIT/BSD license.'
      authors:
      - name: Bonfield J.K.
      - name: Marshall J.
      - name: Danecek P.
      - name: Li H.
      - name: Ohan V.
      - name: Whitwham A.
      - name: Keane T.
      citationCount: 116
      date: '2021-02-01T00:00:00Z'
      journal: GigaScience
      title: 'HTSlib: C library for reading/writing high-Throughput sequencing data'
    note: 'HTSlib: C library for reading/writing high-throughput sequencing data.'
    pmcid: PMC7931820
    pmid: '33594436'
    type:
    - Primary
    version: null
  relation:
  - biotoolsID: samtools
    type: usedBy
  - biotoolsID: bcftools
    type: usedBy
  toolType:
  - Library
  topic:
  - term: Data management
    uri: http://edamontology.org/topic_3071
  validated: 1
  version:
  - '1.0'
  - '1.1'
  - '1.2'
  - 1.2.1
  - '1.3'
  - 1.3.1
  - 1.3.2
  - '1.4'
  - 1.4.1
  - '1.5'
  - '1.6'
  - '1.7'
  - '1.8'
  - '1.9'
  - '1.10'
  - 1.10.1
  - 1.10.2
  - '1.11'
  - '1.12'
  - '1.13'
  - '1.14'
  - '1.15'
  - 1.15.1
  - '1.16'
  - '1.17'
  - '1.18'
  - '1.19'
  - '1.20'
- accessibility: Open access
  additionDate: '2022-03-22T18:57:49.937151Z'
  biotoolsCURIE: biotools:proteinortho
  biotoolsID: proteinortho
  collectionID: []
  community: null
  confidence_flag: null
  cost: Free of charge
  credit:
  - email: null
    fundrefid: null
    gridid: null
    name: Marcus Lechner
    note: null
    orcidid: null
    rorid: null
    typeEntity: null
    typeRole: []
    url: null
  - email: null
    fundrefid: null
    gridid: null
    name: Sonja J Prohaska
    note: null
    orcidid: null
    rorid: null
    typeEntity: null
    typeRole: []
    url: null
  description: Proteinortho is a tool to detect orthologous genes within different
    species
  documentation: []
  download:
  - note: null
    type: Source code
    url: https://gitlab.com/paulklemm_PHD/proteinortho/-/archive/master/proteinortho-master.zip
    version: null
  - note: Installation with dpkg (root privileges are required)
    type: Downloads page
    url: https://packages.debian.org/unstable/proteinortho
    version: null
  editPermission:
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  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Nucleic acid sequence
        uri: http://edamontology.org/data_2977
      format:
      - term: FASTA
        uri: http://edamontology.org/format_1929
    - data:
        term: Protein sequence
        uri: http://edamontology.org/data_2976
      format:
      - term: FASTA
        uri: http://edamontology.org/format_1929
    note: null
    operation:
    - term: Homology-based gene prediction
      uri: http://edamontology.org/operation_3663
    output:
    - data:
        term: Report
        uri: http://edamontology.org/data_2048
      format:
      - term: XML
        uri: http://edamontology.org/format_2332
      - term: HTML
        uri: http://edamontology.org/format_2331
  homepage: https://www.bioinf.uni-leipzig.de/Software/proteinortho/
  homepage_status: 0
  language:
  - Perl
  - C++
  - Python
  lastUpdate: '2024-03-12T09:10:35.206389Z'
  license: GPL-2.0
  link:
  - note: null
    type:
    - Repository
    url: https://gitlab.com/paulklemm_PHD/proteinortho
  - note: null
    type:
    - Issue tracker
    url: https://gitlab.com/paulklemm_PHD/proteinortho/-/issues?sort=created_date&state=opened
  - note: null
    type:
    - Galaxy service
    url: https://toolshed.g2.bx.psu.edu/repository?repository_id=584d8accff31aefe&changeset_revision=4850f0d15f01
  maturity: null
  name: Proteinortho
  operatingSystem:
  - Linux
  - Mac
  - Windows
  otherID: []
  owner: klemmp
  publication:
  - doi: 10.1186/1471-2105-12-124
    metadata:
      abstract: 'Background: Orthology analysis is an important part of data analysis
        in many areas of bioinformatics such as comparative genomics and molecular
        phylogenetics. The ever-increasing flood of sequence data, and hence the rapidly
        increasing number of genomes that can be compared simultaneously, calls for
        efficient software tools as brute-force approaches with quadratic memory requirements
        become infeasible in practise. The rapid pace at which new data become available,
        furthermore, makes it desirable to compute genome-wide orthology relations
        for a given dataset rather than relying on relations listed in databases.Results:
        The program Proteinortho described here is a stand-alone tool that is geared
        towards large datasets and makes use of distributed computing techniques when
        run on multi-core hardware. It implements an extended version of the reciprocal
        best alignment heuristic. We apply Proteinortho to compute orthologous proteins
        in the complete set of all 717 eubacterial genomes available at NCBI at the
        beginning of 2009. We identified thirty proteins present in 99% of all bacterial
        proteomes.Conclusions: Proteinortho significantly reduces the required amount
        of memory for orthology analysis compared to existing tools, allowing such
        computations to be performed on off-the-shelf hardware. © 2011 Lechner et
        al; licensee BioMed Central Ltd.'
      authors:
      - name: Lechner M.
      - name: Findeiss S.
      - name: Steiner L.
      - name: Marz M.
      - name: Stadler P.F.
      - name: Prohaska S.J.
      citationCount: 656
      date: '2011-04-28T00:00:00Z'
      journal: BMC Bioinformatics
      title: 'Proteinortho: Detection of (Co-)orthologs in large-scale analysis'
    note: null
    pmcid: PMC3114741
    pmid: '21526987'
    type:
    - Primary
    version: null
  relation: []
  toolType:
  - Desktop application
  topic:
  - term: Phylogeny
    uri: http://edamontology.org/topic_0084
  validated: 1
  version:
  - 6.0.14
- accessibility: Open access
  additionDate: '2024-03-12T06:13:17.739591Z'
  biotoolsCURIE: biotools:hiv-trace
  biotoolsID: hiv-trace
  collectionID: []
  community: null
  confidence_flag: null
  cost: Free of charge
  credit: []
  description: HIV-TRACE is an application that identifies potential transmission
    clusters within a supplied FASTA file.
  documentation: []
  download:
  - note: null
    type: Source code
    url: https://github.com/veg/hivtrace/archive/refs/tags/0.7.1.zip
    version: 0.1.7
  editPermission:
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  elixirNode: []
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  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: RNA sequence
        uri: http://edamontology.org/data_3495
      format:
      - term: FASTA
        uri: http://edamontology.org/format_1929
    note: null
    operation:
    - term: Operation
      uri: http://edamontology.org/operation_0004
    output:
    - data:
        term: Evidence
        uri: http://edamontology.org/data_2042
      format:
      - term: JSON
        uri: http://edamontology.org/format_3464
  homepage: https://github.com/veg/hivtrace
  homepage_status: 0
  language:
  - JavaScript
  lastUpdate: '2024-03-12T06:13:17.741892Z'
  license: MIT
  link:
  - note: null
    type:
    - Issue tracker
    url: https://github.com/veg/hivtrace?tab=readme-ov-file
  maturity: Mature
  name: HIV-TRACE
  operatingSystem: []
  otherID: []
  owner: klemmp
  publication: []
  relation: []
  toolType: []
  topic: []
  validated: 0
  version:
  - 0.1.7
- accessibility: Open access
  additionDate: '2015-01-22T11:31:41Z'
  biotoolsCURIE: biotools:predgpi
  biotoolsID: predgpi
  collectionID:
  - 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: null
  - email: andrea@biocomp.unibo.it
    fundrefid: null
    gridid: null
    name: Andrea Pierleoni
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  - email: casadio@biocomp.unibo.it
    fundrefid: null
    gridid: null
    name: Rita Casadio
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  - email: pierluigi.martelli@unibo.it
    fundrefid: null
    gridid: null
    name: Pier Luigi Martelli
    note: null
    orcidid: https://orcid.org/0000-0002-0274-5669
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  - 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
    url: null
  description: Prediction system for GPI-anchored proteins.
  documentation:
  - note: null
    type:
    - General
    url: http://gpcr.biocomp.unibo.it/predgpi
  download: []
  editPermission:
    authors:
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    type: group
  elixirCommunity: []
  elixirNode:
  - Italy
  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Protein sequence (raw)
        uri: http://edamontology.org/data_2974
      format:
      - term: FASTA
        uri: http://edamontology.org/format_1929
    note: Prediction
    operation:
    - term: Molecular surface analysis
      uri: http://edamontology.org/operation_3351
    output:
    - data:
        term: Protein report
        uri: http://edamontology.org/data_0896
      format:
      - term: HTML
        uri: http://edamontology.org/format_2331
  homepage: http://gpcr.biocomp.unibo.it/predgpi
  homepage_status: 0
  language: []
  lastUpdate: '2024-03-11T16:58:28.865213Z'
  license: null
  link: []
  maturity: Mature
  name: PredGPI
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: ELIXIR-ITA-BOLOGNA
  publication:
  - doi: 10.1186/1471-2105-9-392
    metadata:
      abstract: 'Background: Several eukaryotic proteins associated to the extracellular
        leaflet of the plasma membrane carry a Glycosylphosphatidylinositol (GPI)
        anchor, which is linked to the C-terminal residue after a proteolytic cleavage
        occurring at the so called ω-site. Computational methods were developed to
        discriminate proteins that undergo this post-translational modification starting
        from their aminoacidic sequences. However more accurate methods are needed
        for a reliable annotation of whole proteomes. Results: Here we present PredGPI,
        a prediction method that, by coupling a Hidden Markov Model (HMM) and a Support
        Vector Machine (SVM), is able to efficiently predict both the presence of
        the GPI-anchor and the position of the ω-site. PredGPI is trained on a non-redundant
        dataset of experimentally characterized GPI-anchored proteins whose annotation
        was carefully checked in the literature. Conclusion: PredGPI outperforms all
        the other previously described methods and is able to correctly replicate
        the results of previously published high-throughput experiments. PredGPI reaches
        a lower rate of false positive predictions with respect to other available
        methods and it is therefore a costless, rapid and accurate method for screening
        whole proteomes. © 2008 Pierleoni et al; licensee BioMed Central Ltd.'
      authors:
      - name: Pierleoni A.
      - name: Martelli P.
      - name: Casadio R.
      citationCount: 463
      date: '2008-09-23T00:00:00Z'
      journal: BMC Bioinformatics
      title: 'PredGPI: A GPI-anchor predictor'
    note: null
    pmcid: null
    pmid: null
    type:
    - Primary
    version: null
  relation: []
  toolType:
  - Web application
  topic:
  - term: Protein secondary structure
    uri: http://edamontology.org/topic_3542
  - term: Protein properties
    uri: http://edamontology.org/topic_0123
  validated: 1
  version:
  - '1.0'
- accessibility: Open access
  additionDate: '2016-01-22T15:53:12Z'
  biotoolsCURIE: biotools:tppred_2.0
  biotoolsID: tppred_2.0
  collectionID:
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  confidence_flag: tool
  cost: Free of charge
  credit:
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    fundrefid: null
    gridid: null
    name: ELIXIR-ITA-BOLOGNA
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
    - Provider
    url: null
  - 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: rita.casadio@unibo.it
    fundrefid: null
    gridid: null
    name: Rita Casadio
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - 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
  - 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:
    - Primary contact
    url: null
  description: Mitochondrial targeting peptide prediction.
  documentation:
  - note: null
    type:
    - General
    url: https://tppred3.biocomp.unibo.it/tppred3/default/help
  - note: Installation instructions
    type:
    - Command-line options
    url: https://tppred2.biocomp.unibo.it/tppred2/default/software
  download:
  - note: null
    type: Source code
    url: http://biocomp.unibo.it/savojard/tppred2.tar.gz
    version: null
  editPermission:
    authors:
    - ELIXIR-ITA-BOLOGNA
    - savo
    type: group
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  - Italy
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  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
    operation:
    - term: Protein subcellular localisation prediction
      uri: http://edamontology.org/operation_2489
    - term: Protein feature detection
      uri: http://edamontology.org/operation_3092
    - term: Sequence feature detection
      uri: http://edamontology.org/operation_0253
    - term: Protein cleavage site prediction
      uri: http://edamontology.org/operation_0422
    output:
    - data:
        term: Protein report
        uri: http://edamontology.org/data_0896
      format:
      - term: HTML
        uri: http://edamontology.org/format_2331
  homepage: https://tppred2.biocomp.unibo.it
  homepage_status: 0
  language:
  - Python
  lastUpdate: '2024-03-11T16:57:44.699185Z'
  license: GPL-3.0
  link: []
  maturity: Mature
  name: TPpred 2.0
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: ELIXIR-ITA-BOLOGNA
  publication:
  - doi: 10.1093/bioinformatics/btu411
    metadata: null
    note: null
    pmcid: null
    pmid: '24974200'
    type:
    - Primary
    version: null
  - doi: 10.1093/bioinformatics/btt089
    metadata:
      abstract: 'Motivation: Targeting peptides are the most important signal controlling
        the import of nuclear encoded proteins into mitochondria and plastids. In
        the lack of experimental information, their prediction is an essential step
        when proteomes are annotated for inferring both the localization and the sequence
        of mature proteins.Results: We developed TPpred a new predictor of organelle-targeting
        peptides based on Grammatical-Restrained Hidden Conditional Random Fields.
        TPpred is trained on a non-redundant dataset of proteins where the presence
        of a target peptide was experimentally validated, comprising 297 sequences.
        When tested on the 297 positive and some other 8010 negative examples, TPpred
        outperformed available methods in both accuracy and Matthews correlation index
        (96% and 0.58, respectively). Given its very low-false-positive rate (3.0%),
        TPpred is, therefore, well suited for large-scale analyses at the proteome
        level. We predicted that from ∼4 to 9% of the sequences of human, Arabidopsis
        thaliana and yeast proteomes contain targeting peptides and are, therefore,
        likely to be localized in mitochondria and plastids. TPpred predictions correlate
        to a good extent with the experimental annotation of the subcellular localization,
        when available. TPpred was also trained and tested to predict the cleavage
        site of the organelle-targeting peptide: on this task, the average error of
        TPpred on mitochondrial and plastidic proteins is 7 and 15 residues, respectively.
        This value is lower than the error reported by other methods currently available.
        © 2013 The Author.'
      authors:
      - name: Indio V.
      - name: Martelli P.L.
      - name: Savojardo C.
      - name: Fariselli P.
      - name: Casadio R.
      citationCount: 14
      date: '2013-04-15T00:00:00Z'
      journal: Bioinformatics
      title: The prediction of organelle-targeting peptides in eukaryotic proteins
        with Grammatical-Restrained Hidden Conditional Random Fields
    note: null
    pmcid: null
    pmid: '23428638'
    type:
    - Primary
    version: null
  relation:
  - biotoolsID: tppred_1.0
    type: isNewVersionOf
  - biotoolsID: tppred_3.0
    type: hasNewVersion
  toolType:
  - Command-line tool
  - Web application
  topic:
  - term: Sequence sites, features and motifs
    uri: http://edamontology.org/topic_0160
  - term: Small molecules
    uri: http://edamontology.org/topic_0154
  - term: Protein targeting and localisation
    uri: http://edamontology.org/topic_0140
  validated: 1
  version:
  - '2.0'
- accessibility: Open access
  additionDate: '2015-01-22T11:31:40Z'
  biotoolsCURIE: biotools:memloci
  biotoolsID: memloci
  collectionID:
  - 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: null
  - email: andrea@biocomp.unibo.it
    fundrefid: null
    gridid: null
    name: Andrea Pierleoni
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  - email: pierluigi.martelli@unibo.it
    fundrefid: null
    gridid: null
    name: Pier Luigi Martelli
    note: null
    orcidid: https://orcid.org/0000-0002-0274-5669
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  - 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
    url: null
  description: Predictor for the subcellular localization of proteins associated or
    inserted in eukaryotes membranes.
  documentation:
  - note: null
    type:
    - General
    url: https://mu2py.biocomp.unibo.it/memloci/default/info
  download: []
  editPermission:
    authors: []
    type: private
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  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
    operation:
    - term: Protein subcellular localisation prediction
      uri: http://edamontology.org/operation_2489
    output:
    - data:
        term: Protein features
        uri: http://edamontology.org/data_1277
      format:
      - term: Textual format
        uri: http://edamontology.org/format_2330
  homepage: https://mu2py.biocomp.unibo.it/memloci
  homepage_status: 0
  language: []
  lastUpdate: '2024-03-11T16:57:20.943436Z'
  license: null
  link: []
  maturity: Mature
  name: MemLoci
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: ELIXIR-ITA-BOLOGNA
  publication:
  - doi: 10.1093/bioinformatics/btr108
    metadata:
      abstract: 'Motivation: Subcellular localization is a key feature in the process
        of functional annotation of both globular and membrane proteins. In the absence
        of experimental data, protein localization is inferred on the basis of annotation
        transfer upon sequence similarity search. However, predictive tools are necessary
        when the localization of homologs is not known. This is so particularly for
        membrane proteins. Furthermore, most of the available predictors of subcellular
        localization are specifically trained on globular proteins and poorly perform
        on membrane proteins. Results: Here we develop MemLoci, a new support vector
        machinebased tool that discriminates three membrane protein localizations:
        plasma, internal and organelle membrane. When tested on an independent set,
        MemLoci outperforms existing methods, reaching an overall accuracy of 70%
        on predicting the location in the three membrane types, with a generalized
        correlation coefficient as high as 0.50. © The Author 2011. Published by Oxford
        University Press. All rights reserved.'
      authors:
      - name: Pierleoni A.
      - name: Martelli P.L.
      - name: Casadio R.
      citationCount: 47
      date: '2011-05-01T00:00:00Z'
      journal: Bioinformatics
      title: 'MemLoci: Predicting subcellular localization of membrane proteins in
        eukaryotes'
    note: null
    pmcid: null
    pmid: null
    type:
    - Primary
    version: null
  relation: []
  toolType:
  - Web application
  topic:
  - term: Protein targeting and localisation
    uri: http://edamontology.org/topic_0140
  - term: Membrane and lipoproteins
    uri: http://edamontology.org/topic_0820
  - term: Model organisms
    uri: http://edamontology.org/topic_0621
  validated: 1
  version:
  - '1.0'
- accessibility: null
  additionDate: '2015-01-22T11:31:40Z'
  biotoolsCURIE: biotools:mempype
  biotoolsID: mempype
  collectionID:
  - 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: null
  - email: andrea@biocomp.unibo.it
    fundrefid: null
    gridid: null
    name: Andrea Pierleoni
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  - email: pierluigi.martelli@unibo.it
    fundrefid: null
    gridid: null
    name: Pier Luigi Martelli
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - Primary contact
    url: null
  - 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
    url: null
  description: Prediction of topology and subcellular localization of Eukaryotic membrane
    proteins.
  documentation:
  - note: null
    type:
    - General
    url: https://mu2py.biocomp.unibo.it/mempype/default/help
  download: []
  editPermission:
    authors: []
    type: private
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  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
    operation:
    - term: Protein secondary structure prediction (helices)
      uri: http://edamontology.org/operation_0468
    - term: Protein signal peptide detection
      uri: http://edamontology.org/operation_0418
    - term: Protein cleavage site prediction
      uri: http://edamontology.org/operation_0422
    - term: Protein subcellular localisation prediction
      uri: http://edamontology.org/operation_2489
    output:
    - data:
        term: Protein report
        uri: http://edamontology.org/data_0896
      format:
      - term: HTML
        uri: http://edamontology.org/format_2331
  homepage: https://mu2py.biocomp.unibo.it/mempype
  homepage_status: 0
  language: []
  lastUpdate: '2024-03-11T16:56:43.617506Z'
  license: null
  link: []
  maturity: Mature
  name: MemPype
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: ELIXIR-ITA-BOLOGNA
  publication:
  - doi: 10.1093/nar/gkr282
    metadata:
      abstract: 'MemPype is a Python-based pipeline including previously published
        methods for the prediction of signal peptides (SPEP), glycophosphatidylinositol
        (GPI) anchors (PredGPI), all-alpha membrane topology (ENSEMBLE), and a recent
        method (MemLoci) that specifically discriminates the localization of eukaryotic
        membrane proteins in: ''cell membrane'', ''internal membranes'', ''organelle
        membranes''. MemLoci scores with accuracy of 70 and generalized correlation
        coefficient (GCC) of 0.50 on a rigorous homology-unbiased validation set and
        overpasses other predictors for subcellular localization. The annotation process
        is based both on inheritance through homology and computational methods. Each
        submitted protein first retrieves, when available, up to 25 similar proteins
        (with sequence identity ≥50 and alignment coverage ≥50 on both sequences).
        This helps the identification of membrane-associated proteins and detailed
        localization tags. Each protein is also filtered for the presence of a GPI
        anchor [0.8 false positive rate (FPR)]. A positive score of GPI anchor prediction
        labels the sequence as exposed to ''Cell surface''. Concomitantly the sequence
        is analysed for the presence of a signal peptide and classified with MemLoci
        into one of three discriminated classes. Finally the sequence is filtered
        for predicting its putative all-alpha protein membrane topology (FPR<1). The
        web server is available at: http://mu2py.biocomp.unibo.it/ mempype. © 2011
        The Author(s).'
      authors:
      - name: Pierleoni A.
      - name: Indio V.
      - name: Savojardo C.
      - name: Fariselli P.
      - name: Martelli P.L.
      - name: Casadio R.
      citationCount: 27
      date: '2011-07-01T00:00:00Z'
      journal: Nucleic Acids Research
      title: 'MemPype: A pipeline for the annotation of eukaryotic membrane proteins'
    note: null
    pmcid: null
    pmid: null
    type:
    - Primary
    version: null
  relation: []
  toolType:
  - Web application
  topic:
  - term: Protein targeting and localisation
    uri: http://edamontology.org/topic_0140
  - term: Membrane and lipoproteins
    uri: http://edamontology.org/topic_0820
  - term: Model organisms
    uri: http://edamontology.org/topic_0621
  validated: 1
  version:
  - '1.0'
- accessibility: Open access
  additionDate: '2015-11-18T13:30:48Z'
  biotoolsCURIE: biotools:tppred_1.0
  biotoolsID: tppred_1.0
  collectionID:
  - Bologna Biocomputing Group
  community: null
  confidence_flag: tool
  cost: Free of charge
  credit:
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    gridid: null
    name: ELIXIR-ITA-BOLOGNA
    note: null
    orcidid: null
    rorid: null
    typeEntity: Institute
    typeRole:
    - Provider
    url: null
  - email: rita.casadio@unibo.it
    fundrefid: null
    gridid: null
    name: Rita Casadio
    note: null
    orcidid: null
    rorid: null
    typeEntity: Person
    typeRole:
    - 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
  - 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:
    - Primary contact
    - Developer
    - Maintainer
    url: null
  description: Organelle targeting peptide prediction.
  documentation:
  - note: null
    type:
    - General
    url: https://tppred.biocomp.unibo.it/tppred/default/about
  download: []
  editPermission:
    authors:
    - ELIXIR-ITA-BOLOGNA
    - savo
    type: group
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  elixirNode:
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  elixirPlatform: []
  elixir_badge: 0
  function:
  - cmd: null
    input:
    - data:
        term: Protein sequence (raw)
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      format:
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        uri: http://edamontology.org/format_1929
    note: Prediction
    operation:
    - term: Protein subcellular localisation prediction
      uri: http://edamontology.org/operation_2489
    - term: Sequence feature detection
      uri: http://edamontology.org/operation_0253
    - term: Protein feature detection
      uri: http://edamontology.org/operation_3092
    output:
    - data:
        term: Protein report
        uri: http://edamontology.org/data_0896
      format:
      - term: HTML
        uri: http://edamontology.org/format_2331
  homepage: http://tppred.biocomp.unibo.it/tppred/default/index
  homepage_status: 0
  language: []
  lastUpdate: '2024-03-11T16:56:24.696925Z'
  license: null
  link: []
  maturity: Mature
  name: TPpred 1.0
  operatingSystem:
  - Linux
  - Windows
  - Mac
  otherID: []
  owner: ELIXIR-ITA-BOLOGNA
  publication:
  - doi: 10.1093/bioinformatics/btt089
    metadata:
      abstract: 'Motivation: Targeting peptides are the most important signal controlling
        the import of nuclear encoded proteins into mitochondria and plastids. In
        the lack of experimental information, their prediction is an essential step
        when proteomes are annotated for inferring both the localization and the sequence
        of mature proteins.Results: We developed TPpred a new predictor of organelle-targeting
        peptides based on Grammatical-Restrained Hidden Conditional Random Fields.
        TPpred is trained on a non-redundant dataset of proteins where the presence
        of a target peptide was experimentally validated, comprising 297 sequences.
        When tested on the 297 positive and some other 8010 negative examples, TPpred
        outperformed available methods in both accuracy and Matthews correlation index
        (96% and 0.58, respectively). Given its very low-false-positive rate (3.0%),
        TPpred is, therefore, well suited for large-scale analyses at the proteome
        level. We predicted that from ∼4 to 9% of the sequences of human, Arabidopsis
        thaliana and yeast proteomes contain targeting peptides and are, therefore,
        likely to be localized in mitochondria and plastids. TPpred predictions correlate
        to a good extent with the experimental annotation of the subcellular localization,
        when available. TPpred was also trained and tested to predict the cleavage
        site of the organelle-targeting peptide: on this task, the average error of
        TPpred on mitochondrial and plastidic proteins is 7 and 15 residues, respectively.
        This value is lower than the error reported by other methods currently available.
        © 2013 The Author.'
      authors:
      - name: Indio V.
      - name: Martelli P.L.
      - name: Savojardo C.
      - name: Fariselli P.
      - name: Casadio R.
      citationCount: 14
      date: '2013-04-15T00:00:00Z'
      journal: Bioinformatics
      title: The prediction of organelle-targeting peptides in eukaryotic proteins
        with Grammatical-Restrained Hidden Conditional Random Fields
    note: null
    pmcid: null
    pmid: '23428638'
    type:
    - Primary
    version: null
  relation:
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    type: hasNewVersion
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    type: hasNewVersion
  toolType:
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  topic:
  - term: Sequence sites, features and motifs
    uri: http://edamontology.org/topic_0160
  - term: Small molecules
    uri: http://edamontology.org/topic_0154
  - term: Protein targeting and localisation
    uri: http://edamontology.org/topic_0140
  validated: 1
  version:
  - '1.0'
next: ?page=2
previous: null
