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dc.contributor.authorGhosh, Debashisen_US
dc.date.accessioned2006-09-11T19:34:20Z
dc.date.available2006-09-11T19:34:20Z
dc.date.issued2005-01en_US
dc.identifier.citationGhosh, Debashis; (2005). "Nonparametric methods for analyzing replication origins in genomewide data." Functional & Integrative Genomics 5(1): 28-31. <http://hdl.handle.net/2027.42/47937>en_US
dc.identifier.issn1438-7948en_US
dc.identifier.issn1438-793Xen_US
dc.identifier.urihttps://hdl.handle.net/2027.42/47937
dc.identifier.urihttp://www.ncbi.nlm.nih.gov/sites/entrez?cmd=retrieve&db=pubmed&list_uids=15599787&dopt=citationen_US
dc.description.abstractDue to the advent of high-throughput genomic technology, it has become possible to monitor cellular activities on a genomewide basis. With these new methods, scientists can begin to address important biological questions. One such question involves the identification of replication origins, which are regions in the chromosomes where DNA replication is initiated. One hypothesis is that their locations are nonrandom throughout the genome. In this article, we analyze data from a recent yeast study in which candidate replication origins were profiled using cDNA microarrays to test this hypothesis. We find no evidence for such clustering.en_US
dc.format.extent104596 bytes
dc.format.extent3115 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypetext/plain
dc.language.isoen_US
dc.publisherSpringer-Verlagen_US
dc.subject.otherGene Expressionen_US
dc.subject.otherDensity Estimationen_US
dc.subject.otherKernel Smoothingen_US
dc.subject.otherDerivative Estimationen_US
dc.subject.otherLifeSciencesen_US
dc.subject.otherChangepointen_US
dc.titleNonparametric methods for analyzing replication origins in genomewide dataen_US
dc.typeArticleen_US
dc.subject.hlbsecondlevelGeneticsen_US
dc.subject.hlbtoplevelHealth Sciencesen_US
dc.description.peerreviewedPeer Revieweden_US
dc.contributor.affiliationumDepartments of Biostatistics, School of Public Health, University of Michigan, 1420 Washington Heights, Room M4057, Ann Arbor, MI, 48109-2029, USAen_US
dc.contributor.affiliationumcampusAnn Arboren_US
dc.identifier.pmid15599787en_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/47937/1/10142_2004_Article_122.pdfen_US
dc.identifier.doihttp://dx.doi.org/10.1007/s10142-004-0122-1en_US
dc.identifier.sourceFunctional & Integrative Genomicsen_US
dc.owningcollnameInterdisciplinary and Peer-Reviewed


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