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Bioinformatics Strategies for Translating Genome-Wide Expression Analyses into Clinically Useful Cancer Markers
dc.contributor.authorRhodes, Daniel R.en_US
dc.contributor.authorChinnaiyan, Arul M.en_US
dc.date.accessioned2010-06-01T20:18:17Z
dc.date.available2010-06-01T20:18:17Z
dc.date.issued2004-05en_US
dc.identifier.citationRHODES, DANIEL R.; CHINNAIYAN, ARUL M. (2004). "Bioinformatics Strategies for Translating Genome-Wide Expression Analyses into Clinically Useful Cancer Markers." Annals of the New York Academy of Sciences 1020(1 The Applications of Bioinformatics in Cancer Detection ): 32-40. <http://hdl.handle.net/2027.42/73423>en_US
dc.identifier.issn0077-8923en_US
dc.identifier.issn1749-6632en_US
dc.identifier.urihttps://hdl.handle.net/2027.42/73423
dc.identifier.urihttp://www.ncbi.nlm.nih.gov/sites/entrez?cmd=retrieve&db=pubmed&list_uids=15208181&dopt=citationen_US
dc.description.abstractThe DNA microarray has revolutionized cancer research. Now, scientists can obtain a genome-wide perspective of cancer gene expression. One potential application of this technology is the discovery of novel cancer biomarkers for more accurate diagnosis and prognosis, and potentially for the earlier detection of disease or the monitoring of treatment effectiveness. Because microarray experiments generate a tremendous amount of data and because the number of laboratories generating microarray data is rapidly growing, new bioinformatics strategies that promote the maximum utilization of such data are necessary. Here, we describe a method to validate multiple microarray data sets, a Web-based cancer microarray database for biomarker discovery, and methods for integrating gene ontology annotations with microarray data to improve candidate biomarker selection.en_US
dc.format.extent2667819 bytes
dc.format.extent3109 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypetext/plain
dc.publisherBlackwell Publishing Ltden_US
dc.rights2004 New York Academy of Sciencesen_US
dc.subject.otherCanceren_US
dc.subject.otherBiomarkersen_US
dc.subject.otherBioinformaticsen_US
dc.subject.otherMeta-analysisen_US
dc.subject.otherMicroarrayen_US
dc.titleBioinformatics Strategies for Translating Genome-Wide Expression Analyses into Clinically Useful Cancer Markersen_US
dc.typeArticleen_US
dc.subject.hlbsecondlevelScience (General)en_US
dc.subject.hlbtoplevelScienceen_US
dc.description.peerreviewedPeer Revieweden_US
dc.contributor.affiliationumDepartment of Pathology, University of Michigan Medical School, Ann Arbor, Michigan 48109, USAen_US
dc.contributor.affiliationumDepartment of Urology, University of Michigan Medical School, Ann Arbor, Michigan 48109, USAen_US
dc.contributor.affiliationumComprehensive Cancer Center, University of Michigan Medical School, Ann Arbor, Michigan 48109, USAen_US
dc.identifier.pmid15208181en_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/73423/1/annals.1310.005.pdf
dc.identifier.doi10.1196/annals.1310.005en_US
dc.identifier.sourceAnnals of the New York Academy of Sciencesen_US
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dc.owningcollnameInterdisciplinary and Peer-Reviewed


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