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dc.contributor.author이민수*
dc.date.accessioned2016-09-21T01:09:20Z-
dc.date.available2016-09-21T01:09:20Z-
dc.date.issued2016*
dc.identifier.issn1367-4803*
dc.identifier.issn1460-2059*
dc.identifier.otherOAK-19252*
dc.identifier.urihttps://dspace.ewha.ac.kr/handle/2015.oak/232284-
dc.description.abstractMGEScan-long terminal repeat (LTR) and MGEScan-non-LTR are successfully used programs for identifying LTRs and non-LTR retrotransposons in eukaryotic genome sequences. However, these programs are not supported by easy-to-use interfaces nor well suited for data visualization in general data formats. Here, we present MGEScan, a user-friendly system that combines these two programs with a Galaxy workflow system accelerated with MPI and Python threading on compute clusters. MGEScan and Galaxy empower researchers to identify transposable elements in a graphical user interface with ready-to-use workflows. MGEScan also visualizes the custom annotation tracks for mobile genetic elements in public genome browsers. A maximum speed-up of 3.26x is attained for execution time using concurrent processing and MPI on four virtual cores. MGEScan provides four operational modes: as a command line tool, as a Galaxy Toolshed, on a Galaxy-based web server, and on a virtual cluster on the Amazon cloud.*
dc.languageEnglish*
dc.publisherOXFORD UNIV PRESS*
dc.titleMGEScan: a Galaxy-based system for identifying retrotransposons in genomes*
dc.typeArticle*
dc.relation.issue16*
dc.relation.volume32*
dc.relation.indexSCIE*
dc.relation.indexSCOPUS*
dc.relation.startpage2502*
dc.relation.lastpage2504*
dc.relation.journaltitleBIOINFORMATICS*
dc.identifier.doi10.1093/bioinformatics/btw157*
dc.identifier.wosidWOS:000383682900014*
dc.identifier.scopusid2-s2.0-84983266553*
dc.author.googleLee, Hyungro*
dc.author.googleLee, Minsu*
dc.author.googleIsmail, Wazim Mohammed*
dc.author.googleRho, Mina*
dc.author.googleFox, Geoffrey C.*
dc.author.googleOh, Sangyoon*
dc.author.googleTang, Haixu*
dc.contributor.scopusid이민수(56142596700)*
dc.date.modifydate20240322133738*
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인공지능대학 > 컴퓨터공학과 > Journal papers
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