title: Integrative analysis of the cancer transcriptome.
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.
authors.affiliation: Department of Pathology, Comprehensive Cancer Center, University of Michigan Medical School, Ann Arbor, Michigan 48109, USA.
authors.forename: Daniel R
authors.initials: DR
authors.lastname: Rhodes
authors.forename: Arul M
authors.initials: AM
authors.lastname: Chinnaiyan
mesh_terms: D000818:Animals; D019295:Computational Biology / Q000639:trends; D020869:Gene Expression Profiling; D006801:Humans; D015201:Meta-Analysis as Topic; D008954:Models, Biological; D009369:Neoplasms / Q000235:genetics*; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D011506:Proteins / Q000378:metabolism; D014158:Transcription, Genetic
chemical_list: D011506:Proteins