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dc.contributor.authorMehta, Gaurangzh_CN
dc.contributor.authorDeelman, Ewazh_CN
dc.contributor.authorKnowles, James A.zh_CN
dc.contributor.authorChen, Tingzh_CN
dc.contributor.authorWang, Yinzh_CN
dc.contributor.authorV枚ckler, Jenszh_CN
dc.contributor.authorBuyske, Stevenzh_CN
dc.contributor.authorMatise, Tarazh_CN
dc.contributor.author王颖zh_CN
dc.date.accessioned2015-07-22T02:39:53Z
dc.date.available2015-07-22T02:39:53Z
dc.date.issued2012zh_CN
dc.identifier.citationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2012:23-32zh_CN
dc.identifier.other20133516665281zh_CN
dc.identifier.urihttps://dspace.xmu.edu.cn/handle/2288/86838
dc.descriptionConference Name:17th Parallel Processing Workshops, Euro-Par 2011: CCPI 2011, CGWS 2011, HeteroPar 2011, HiBB 2011, HPCVirt 2011, HPPC 2011, HPSS 2011, MDGS 2011, ProPer 2011, Resilience 2011, UCHPC 2011, VHPC 2011. Conference Address: Bordeaux, France. Time:August 29, 2011 - September 2, 2011.zh_CN
dc.description.abstractAccelerated growth in the field of bioinformatics has resulted in large data sets being produced and analyzed. With this rapid growth has come the need to analyze these data in a quick, easy, scalable, and reliable manner on a variety of computing infrastructures including desktops, clusters, grids and clouds. This paper presents the application of workflow technologies, and, specifically, Pegasus WMS, a robust scientific workflow management system, to a variety of bioinformatics projects from RNA sequencing, proteomics, and data quality control in population studies using GWAS data. 漏 2012 Springer-Verlag Berlin Heidelberg.zh_CN
dc.language.isoen_USzh_CN
dc.publisherSpringer Verlagzh_CN
dc.source.urihttp://dx.doi.org/10.1007/978-3-642-29740-3-4zh_CN
dc.subjectInformation managementzh_CN
dc.subjectMolecular biologyzh_CN
dc.subjectParallel architectureszh_CN
dc.subjectPopulation statisticszh_CN
dc.titleEnabling data and compute intensive workflows in bioinformaticszh_CN
dc.typeConferencezh_CN


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