Integrative analysis of the cancer transcriptome Export

@article{citeulike:238896, abstract = {DNA microarrays have been widely applied to the study of human cancer, delineating myriad molecular subtypes of cancer, many of which are associated with distinct biological underpinnings, disease progression and treatment response. These primary analyses have begun to decipher the molecular heterogeneity of cancer, but integrative analyses that evaluate cancer transcriptome data in the context of other data sources are often capable of extracting deeper biological insight from the data. Here we discuss several such integrative computational and analytical approaches, including meta-analysis, functional enrichment analysis, interactome analysis, transcriptional network analysis and integrative model system analysis.}, address = {Department of Pathology, Comprehensive Cancer Center, University of Michigan Medical School, Ann Arbor, Michigan 48109, USA.}, author = {Rhodes, Daniel R. and Chinnaiyan, Arul M.}, citeulike-article-id = {238896}, citeulike-linkout-0 = {http://dx.doi.org/10.1038/ng1570}, citeulike-linkout-1 = {http://dx.doi.org/10.1038/ng1570}, citeulike-linkout-2 = {http://view.ncbi.nlm.nih.gov/pubmed/15920528}, citeulike-linkout-3 = {http://www.hubmed.org/display.cgi?uids=15920528}, day = {01}, doi = {10.1038/ng1570}, issn = {1061-4036}, journal = {Nature Genetics}, keywords = {analysis, cancer, integrative, microarray, transcriptome}, month = {June}, pages = {S31--S37}, posted-at = {2009-10-06 23:46:47}, priority = {2}, publisher = {Nature Publishing Group}, title = {Integrative analysis of the cancer transcriptome}, url = {http://dx.doi.org/10.1038/ng1570}, volume = {37 Suppl}, year = {2005} }

TY - JOUR ID - citeulike:238896 L3 - citeulike-article-id:238896 N2 - DNA microarrays have been widely applied to the study of human cancer, delineating myriad molecular subtypes of cancer, many of which are associated with distinct biological underpinnings, disease progression and treatment response. These primary analyses have begun to decipher the molecular heterogeneity of cancer, but integrative analyses that evaluate cancer transcriptome data in the context of other data sources are often capable of extracting deeper biological insight from the data. Here we discuss several such integrative computational and analytical approaches, including meta-analysis, functional enrichment analysis, interactome analysis, transcriptional network analysis and integrative model system analysis. JF - Nature Genetics SN - 1061-4036 AD - Department of Pathology, Comprehensive Cancer Center, University of Michigan Medical School, Ann Arbor, Michigan 48109, USA. EP - S37 TI - Integrative analysis of the cancer transcriptome PB - Nature Publishing Group VL - 37 Suppl SP - S31 KW - analysis KW - cancer KW - integrative KW - microarray KW - transcriptome AU - Rhodes, Daniel AU - Chinnaiyan, Arul PY - 2005/06/01/ UR - http://dx.doi.org/10.1038/ng1570 ER -