4 datasets found
  1. Content of the Bioinformatics for Dentistry, with its respective primary...

    • plos.figshare.com
    xls
    Updated Jun 6, 2024
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    Ava K. Chow; Rachel Low; Jerald Yuan; Karen K. Yee; Jaskaranjit Kaur Dhaliwal; Shanice Govia; Nazlee Sharmin (2024). Content of the Bioinformatics for Dentistry, with its respective primary sources. [Dataset]. http://doi.org/10.1371/journal.pone.0303628.t002
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    xlsAvailable download formats
    Dataset updated
    Jun 6, 2024
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Ava K. Chow; Rachel Low; Jerald Yuan; Karen K. Yee; Jaskaranjit Kaur Dhaliwal; Shanice Govia; Nazlee Sharmin
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Content of the Bioinformatics for Dentistry, with its respective primary sources.

  2. e

    Data from: PROSITE

    • prosite.expasy.org
    • identifiers.org
    • +7more
    Updated Oct 15, 2025
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    (2025). PROSITE [Dataset]. https://prosite.expasy.org/
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    Dataset updated
    Oct 15, 2025
    Description

    PROSITE consists of documentation entries describing protein domains, families and functional sites as well as associated patterns and profiles to identify them [More... / References / Commercial users ]. PROSITE is complemented by ProRule , a collection of rules based on profiles and patterns, which increases the discriminatory power of profiles and patterns by providing additional information about functionally and/or structurally critical amino acids [More...].

  3. The Encyclopedia of Domains (TED) structural domains assignments for...

    • zenodo.org
    application/gzip, bz2 +1
    Updated Oct 31, 2024
    + more versions
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    Andy Lau; Andy Lau; Nicola Bordin; Nicola Bordin; Shaun Kandathil; Shaun Kandathil; Ian Sillitoe; Ian Sillitoe; Vaishali Waman; Vaishali Waman; Jude Wells; Jude Wells; Christine Orengo; Christine Orengo; David T Jones; David T Jones (2024). The Encyclopedia of Domains (TED) structural domains assignments for AlphaFold Database v4 [Dataset]. http://doi.org/10.5281/zenodo.13369203
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    application/gzip, bz2, zipAvailable download formats
    Dataset updated
    Oct 31, 2024
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Andy Lau; Andy Lau; Nicola Bordin; Nicola Bordin; Shaun Kandathil; Shaun Kandathil; Ian Sillitoe; Ian Sillitoe; Vaishali Waman; Vaishali Waman; Jude Wells; Jude Wells; Christine Orengo; Christine Orengo; David T Jones; David T Jones
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Dataset description:

    The Encyclopedia of Domains (TED) is a joint effort by CATH (Orengo group) and the Jones group at University College London to identify and classify protein domains in AlphaFold2 models from AlphaFold Database version 4, covering over 188 million unique sequences and 324 million domain assignments.

    In this data release, we will be making available to the community a table of domain boundaries and additional metadata on quality (pLDDT, globularity, number of secondary structures), taxonomy and putative CATH SuperFamily or Fold assignments for all 324 million domains in TED100.

    For all chains in the TED-redundant dataset, the attached file contains boundaries predictions, consensus level and information on the TED100 representative.

    Additionally, an archive with chain-level consensus domain assignments are available for 21 model organisms and 25 global health proteomes:

    For both TED100 and TEDredundant we provide domain boundaries predictions outputted by each of the three methods employed in the project (Chainsaw, Merizo, UniDoc).

    We are making available 7,427 novel folds PDB files, identified during the TED classification process with an annotation table sorted by novelty.

    Please use the gunzip command to extract files with a '.gz' extension.

    CATH annotations have been assigned using the FoldSeek algorithm applied in various modes and the FoldClass algorithm, both of which are used to report significant structural similarity to a known CATH domain.
    Note: The TED protocol differs from that of our standard CATH Assignment protocol for superfamily assignment, which also involves HMM-based protocols and manual curation for remote matches.


    This dataset contains:

    • ted_214m_per_chain_segmentation.tsv
      The file contains all 214M protein chains in TED with consensus domain boundaries and proteome information in the following columns.
      1. AFDB_model_ID: chain identifier from AFDB in the format AF-
    • ted_365m_domain_boundaries_consensus_level.tsv.gz
      The file contains all domain assignments in TED100 and TED-redundant (365M) in the format:
      1. TED_ID: TED domain identifier in the format AF-
    • ted_100_324m.domain_summary.cath.globularity.taxid.tsv and novel_folds_set.domain_summary.tsv are header-less with the following columns separated by tabs (.tsv).
    • ted_324m_seq_clustering.cathlabels.tsv
      The file contains the results of the domain sequences clustering with MMseqs2.
      Columns:
      1. Cluster_representative
      2. Cluster_member
      3. CATH code assignment if available i.e. 3.40.50.300 for a domain with a homologous match or 3.20.20 for a domain matching at the fold level in the CATH classification
      4. CATH assignment type - either Foldseek-T, Foldseek-H or Foldclass
    • novel_folds_set.domain_summary.tsv is sorted by novelty.
      1. ted_id - TED domain identifier in the format AF-
    • Domain assignments for TED redundant using single-chain and multi-chain consensus in ted_redundant_39m.multichain.consensus_domain_summary.taxid.tsv and ted_redundant_39m.singlechain.consensus_domain_summary.taxid.tsv
      The files contain a header with the following fields. Each column is tab-separated (.tsv).
      1. TED_redundant_id - TED chain identifier in the format AF-
    • and ted_redundant_39m.singlechain.consensus_domain_summary.taxid.tsv
      The file contains a header with the following fields. Each column is tab-separated (.tsv).
      1. TED_redundant_id - TED chain identifier in the format AF-
    • novel_folds_set_models.tar.gz contains PDB files of all novel folds identified in TED100.
    • All per-tool domain boundaries predictions are in the same format with the following columns.
      1. TED_chainID - TED chain identifier in the format AF-
    • Domain boundaries predictions share the same format, with each segment separated by '_' and segment boundaries (start,stop) separated by '-'

      i.e.domain prediction by Merizo for AF-A0A000-F1-model_v4
      AF-A0A000-F1-model_v4 e8872c7a0261b9e88e6ff47eb34e4162 394 2 10-52_289-394,53-288 0.90077

      Merizo predicts one continuous domain and a discontinuous domain,
      Domain1 (discontinuous): 10-52_289-394
      segment1: 10-52
      segment2: 289-394
      Domain 2 (continuous):
      segment 1: 53-288
    • ted-tools-main.zip - copy of the https://github.com/psipred/ted-tools repository, containing tools and software used to generate TED.
    • cath-alphaflow-main.zip - copy of CATH-AlphaFlow, used to generate globularity scores for TED domains.
    • ted-web-master.zip - copy of TED-web, containing code to generate the web interface of TED (https://ted.cathdb.info)
    • gofocus_data.tar.bz2 - GOFocus model weights
  4. Metabolite BridgeDb ID Mapping Database (20180705)

    • figshare.com
    zip
    Updated Jun 5, 2023
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    Denise Slenter (2023). Metabolite BridgeDb ID Mapping Database (20180705) [Dataset]. http://doi.org/10.6084/m9.figshare.6741491.v1
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    zipAvailable download formats
    Dataset updated
    Jun 5, 2023
    Dataset provided by
    figshare
    Figsharehttp://figshare.com/
    Authors
    Denise Slenter
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    BridgeDb ID mapping database for metabolites, using HMDB 4.0 (Release of 18 June 2018), ChEBI 165, and Wikidata (07 July 2018) as data sources. Two major changes:- 120% more mappings to LIPID MAPS IDs (from Wikidata).- Change in mapping between old(secondary) and new (primary) HMDB IDs.This work was funded by ELIXIR, the research infrastructure for life-science data.

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    Learn how you can add new datasets to our index.

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Ava K. Chow; Rachel Low; Jerald Yuan; Karen K. Yee; Jaskaranjit Kaur Dhaliwal; Shanice Govia; Nazlee Sharmin (2024). Content of the Bioinformatics for Dentistry, with its respective primary sources. [Dataset]. http://doi.org/10.1371/journal.pone.0303628.t002
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Content of the Bioinformatics for Dentistry, with its respective primary sources.

Related Article
Explore at:
xlsAvailable download formats
Dataset updated
Jun 6, 2024
Dataset provided by
PLOShttp://plos.org/
Authors
Ava K. Chow; Rachel Low; Jerald Yuan; Karen K. Yee; Jaskaranjit Kaur Dhaliwal; Shanice Govia; Nazlee Sharmin
License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically

Description

Content of the Bioinformatics for Dentistry, with its respective primary sources.

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