antiSMASH 3.0-a comprehensive resource for the genome mining of biosynthetic gene clusters

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dc.contributor.authorWeber, Tilmannko
dc.contributor.authorBlin, Kaiko
dc.contributor.authorDuddela, Srikanthko
dc.contributor.authorKrug, Danielko
dc.contributor.authorKim, Hyun Ukko
dc.contributor.authorBruccoleri, Robertko
dc.contributor.authorLee, Sang Yupko
dc.contributor.authorFischbach, Michael A.ko
dc.contributor.authorMueller, Rolfko
dc.contributor.authorWohlleben, Wolfgangko
dc.contributor.authorBreitling, Rainerko
dc.contributor.authorTakano, Erikoko
dc.contributor.authorMedema, Marnix H.ko
dc.date.accessioned2016-04-15T03:09:05Z-
dc.date.available2016-04-15T03:09:05Z-
dc.date.created2015-09-14-
dc.date.created2015-09-14-
dc.date.created2015-09-14-
dc.date.created2015-09-14-
dc.date.created2015-09-14-
dc.date.issued2015-07-
dc.identifier.citationNUCLEIC ACIDS RESEARCH, v.43, no.W1, pp.W237 - W243-
dc.identifier.issn0305-1048-
dc.identifier.urihttp://hdl.handle.net/10203/204002-
dc.description.abstractMicrobial secondary metabolism constitutes a rich source of antibiotics, chemotherapeutics, insecticides and other high-value chemicals. Genome mining of gene clusters that encode the biosynthetic pathways for these metabolites has become a key methodology for novel compound discovery. In 2011, we introduced antiSMASH, a web server and standalone tool for the automatic genomic identification and analysis of biosynthetic gene clusters, available at http://antismash.secondarymetabolites.org. Here, we present version 3.0 of antiSMASH, which has undergone major improvements. A full integration of the recently published ClusterFinder algorithm now allows using this probabilistic algorithm to detect putative gene clusters of unknown types. Also, a new dereplication variant of the ClusterBlast module now identifies similarities of identified clusters to any of 1172 clusters with known end products. At the enzyme level, active sites of key biosynthetic enzymes are now pinpointed through a curated patternmatching procedure and Enzyme Commission numbers are assigned to functionally classify all enzymecoding genes. Additionally, chemical structure prediction has been improved by incorporating polyketide reduction states. Finally, in order for users to be able to organize and analyze multiple antiSMASH outputs in a private setting, a new XML output module allows offline editing of antiSMASH annotations within the Geneious software.-
dc.languageEnglish-
dc.publisherOXFORD UNIV PRESS-
dc.titleantiSMASH 3.0-a comprehensive resource for the genome mining of biosynthetic gene clusters-
dc.typeArticle-
dc.identifier.wosid000359772700037-
dc.identifier.scopusid2-s2.0-84979859096-
dc.type.rimsART-
dc.citation.volume43-
dc.citation.issueW1-
dc.citation.beginningpageW237-
dc.citation.endingpageW243-
dc.citation.publicationnameNUCLEIC ACIDS RESEARCH-
dc.identifier.doi10.1093/nar/gkv437-
dc.embargo.liftdate9999-12-31-
dc.embargo.terms9999-12-31-
dc.contributor.localauthorKim, Hyun Uk-
dc.contributor.localauthorLee, Sang Yup-
dc.contributor.nonIdAuthorWeber, Tilmann-
dc.contributor.nonIdAuthorBlin, Kai-
dc.contributor.nonIdAuthorDuddela, Srikanth-
dc.contributor.nonIdAuthorKrug, Daniel-
dc.contributor.nonIdAuthorBruccoleri, Robert-
dc.contributor.nonIdAuthorFischbach, Michael A.-
dc.contributor.nonIdAuthorMueller, Rolf-
dc.contributor.nonIdAuthorWohlleben, Wolfgang-
dc.contributor.nonIdAuthorBreitling, Rainer-
dc.contributor.nonIdAuthorTakano, Eriko-
dc.contributor.nonIdAuthorMedema, Marnix H.-
dc.description.isOpenAccessY-
dc.type.journalArticleArticle-
dc.subject.keywordPlusNATURAL-PRODUCTS-
dc.subject.keywordPlusTOOLS-
dc.subject.keywordPlusIDENTIFICATION-
dc.subject.keywordPlusANNOTATION-
dc.subject.keywordPlusFAMILIES-
dc.subject.keywordPlusPLATFORM-
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