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Fast and accurate protein structure search with Foldseek

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dc.contributor.authorvan Kempen, Michel-
dc.contributor.authorKim, Stephanie S.-
dc.contributor.authorTumescheit, Charlotte-
dc.contributor.authorMirdita, Milot-
dc.contributor.authorLee, Jeongjae-
dc.contributor.authorGilchrist, Cameron L. M.-
dc.contributor.authorSoeding, Johannes-
dc.contributor.authorSteinegger, Martin-
dc.date.accessioned2024-05-16T01:25:37Z-
dc.date.available2024-05-16T01:25:37Z-
dc.date.created2023-06-02-
dc.date.created2023-06-02-
dc.date.issued2024-02-
dc.identifier.citationNature Biotechnology, Vol.42 No.2, pp.243-246-
dc.identifier.issn1087-0156-
dc.identifier.urihttps://hdl.handle.net/10371/202486-
dc.description.abstractAs structure prediction methods are generating millions of publicly available protein structures, searching these databases is becoming a bottleneck. Foldseek aligns the structure of a query protein against a database by describing tertiary amino acid interactions within proteins as sequences over a structural alphabet. Foldseek decreases computation times by four to five orders of magnitude with 86%, 88% and 133% of the sensitivities of Dali, TM-align and CE, respectively. Foldseek speeds up protein structural search by four to five orders of magnitude.-
dc.language영어-
dc.publisherNature Publishing Group-
dc.titleFast and accurate protein structure search with Foldseek-
dc.typeArticle-
dc.identifier.doi10.1038/s41587-023-01773-0-
dc.citation.journaltitleNature Biotechnology-
dc.identifier.wosid000984647200001-
dc.identifier.scopusid2-s2.0-85158125205-
dc.citation.endpage246-
dc.citation.number2-
dc.citation.startpage243-
dc.citation.volume42-
dc.description.isOpenAccessY-
dc.contributor.affiliatedAuthorSteinegger, Martin-
dc.type.docTypeArticle-
dc.description.journalClass1-
dc.subject.keywordPlusSTRUCTURE ALIGNMENT-
dc.subject.keywordPlusDATABASE-
dc.subject.keywordPlusPREDICTION-
dc.subject.keywordPlusALGORITHM-
dc.subject.keywordPlusMODELS-
dc.subject.keywordPlusSPACE-
dc.subject.keywordPlusTIMES-
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Related Researcher

  • College of Natural Sciences
  • School of Biological Sciences
Research Area Development of algorithms to search, cluster and assemble sequence data, Metagenomic analysis, Pathogen detection in sequencing data

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