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dc.contributor.authorStitziel, Nathan O.
dc.contributor.authorKiezun, Adam
dc.contributor.authorSunyaev, Shamil R.
dc.date.accessioned2012-05-10T23:58:41Z
dc.date.available2012-05-10T23:58:41Z
dc.date.issued2011-09
dc.identifier.issn1465-6906
dc.identifier.issn1474-7596
dc.identifier.urihttp://hdl.handle.net/1721.1/70574
dc.description.abstractNew sequencing technology has enabled the identification of thousands of single nucleotide polymorphisms in the exome, and many computational and statistical approaches to identify disease-association signals have emerged.en_US
dc.description.sponsorshipNational Institutes of Health (U.S.) (Grant R01-MH084676)en_US
dc.description.sponsorshipNational Institutes of Health (U.S.) (Grant R01-GM078598)en_US
dc.description.sponsorshipNational Institutes of Health (U.S.) (Training grant T32-HL07604-25)en_US
dc.description.sponsorshipBrigham and Women's Hospital (Division of Cardiovascular Medicine)en_US
dc.language.isoen_US
dc.publisherBioMed Central Ltd.en_US
dc.relation.isversionofhttp://dx.doi.org/10.1186/gb-2011-12-9-227en_US
dc.rightsCreative Commons Attributionen_US
dc.rights.urihttp://creativecommons.org/licenses/by/2.0en_US
dc.sourceBioMed Centralen_US
dc.titleComputational and statistical approaches to analyzing variants identified by exome sequencingen_US
dc.typeArticleen_US
dc.identifier.citationStitziel, Nathan O, Adam Kiezun, and Shamil Sunyaev. “Computational and Statistical Approaches to Analyzing Variants Identified by Exome Sequencing.” Genome Biology 12.9 (2011): 227. Web.en_US
dc.contributor.departmentHarvard University--MIT Division of Health Sciences and Technologyen_US
dc.contributor.approverSunyaev, Shamil R.
dc.contributor.mitauthorSunyaev, Shamil R.
dc.relation.journalGenome Biologyen_US
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dspace.orderedauthorsStitziel, Nathan O; Kiezun, Adam; Sunyaev, Shamilen
mit.licensePUBLISHER_CCen_US


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