title: Incorporation of gene ontology annotations to enhance microarray data analysis.
abstract: Typical microarray or GeneChip experiments now provide genome-wide measurements on gene expression across many conditions. Analysis often focuses on only a few of the genes, looking for those that are "differentially expressed" between conditions or groups of conditions. However, the large number of measurements both present statistical problems to such single gene approaches and offers a tremendous amount of information for methods focused on biological processes rather than individual genes. Here we provide a method to utilize biological annotations in the form of gene ontologies to interpret the results of individual or multiple pattern recognition analyses of a microarray experiment.
authors.affiliation: Fox Chase Cancer Center, Philadelphia, PA, USA.
authors.forename: Michael F
authors.initials: MF
authors.lastname: Ochs
authors.forename: Aidan J
authors.initials: AJ
authors.lastname: Peterson
authors.forename: Andrew
authors.initials: A
authors.lastname: Kossenkov
authors.forename: Ghislain
authors.initials: G
authors.lastname: Bidaut
mesh_terms: D000818:Animals; D016000:Cluster Analysis; D003627:Data Interpretation, Statistical; D015870:Gene Expression; D005796:Genes; D016678:Genome; D006801:Humans; D046228:Microarray Analysis / Q000379:methods*; D008967:Molecular Biology / Q000379:methods*; D010363:Pattern Recognition, Automated