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MMseqs2 enables sensitive protein sequence searching for the analysis of massive data sets

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dc.contributor.authorSteinegger, Martin-
dc.contributor.authorSoeding, Johannes-
dc.date.accessioned2024-05-16T01:29:22Z-
dc.date.available2024-05-16T01:29:22Z-
dc.date.created2020-06-26-
dc.date.created2020-06-26-
dc.date.created2020-06-26-
dc.date.issued2017-11-
dc.identifier.citationNature Biotechnology, Vol.35 No.11, pp.1026-1028-
dc.identifier.issn1087-0156-
dc.identifier.urihttps://hdl.handle.net/10371/202581-
dc.language영어-
dc.publisherNature Publishing Group-
dc.titleMMseqs2 enables sensitive protein sequence searching for the analysis of massive data sets-
dc.typeArticle-
dc.identifier.doi10.1038/nbt.3988-
dc.citation.journaltitleNature Biotechnology-
dc.identifier.wosid000414856200015-
dc.identifier.scopusid2-s2.0-85033571642-
dc.citation.endpage1028-
dc.citation.number11-
dc.citation.startpage1026-
dc.citation.volume35-
dc.description.isOpenAccessN-
dc.contributor.affiliatedAuthorSteinegger, Martin-
dc.type.docTypeLetter-
dc.description.journalClass1-
dc.subject.keywordPlusGENERATION-
dc.subject.keywordPlusALIGNMENT-
dc.subject.keywordPlusFASTER-
dc.subject.keywordPlusBLAST-
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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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