title: Integrated analysis of microarray results.
abstract: Gene expression microarrays are becoming increasingly widespread, especially as a way to rapidly identify putative functions of unknown genes. Accurate microarray data analysis, however, still remains a challenge. The recent availability of multiple types of high-throughput functional genomic data can facilitate accurate and effective analysis of microarray experiments and thereby accelerate functional annotation of sequenced genomes. But genomic data often sacrifice specificity for scale, yielding very large quantities of relatively lower quality data than traditional experimental methods. Advanced analysis methods are thus necessary to make accurate functional interpretation of these large-scale datasets. This chapter outlines recently developed methods that integrate the analysis of microarray data with sequence, interaction, localization, and literature data and further outlines specific problems in currently available integrated analysis technologies.
authors.affiliation: Lewis-Sigler Institute for Integrative Genomics, Carl Icahn Laboratory, Princeton University, NJ, USA.
authors.forename: Olga G
authors.initials: OG
authors.lastname: Troyanskaya
mesh_terms: D000465:Algorithms; D000818:Animals; D030541:Databases, Genetic; D020869:Gene Expression Profiling / Q000379:methods* / Q000639:trends; D005786:Gene Expression Regulation / Q000502:physiology*; D006801:Humans; D016247:Information Storage and Retrieval / Q000379:methods / Q000639:trends; D008954:Models, Biological; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods* / Q000639:trends; D018511:Systems Integration