title: Statistical approach to DNA chip analysis.
abstract: Statistical methods for analyzing data from DNA microarray experiments are reviewed. Specifically, we discuss common experimental setups, methods for data reduction and clustering, and analysis of time-course experiments. While early microarray studies focused mainly on the basic methodological and technical aspects of DNA arrays, emphasis has shifted to biological, medical, and clinical applications. We mention several of these and present results from our recent research as illustrative examples. New developments in this ever-growing field are outlined.
authors.affiliation: Department of Psychiatry, Washington University School of Medicine, St. Louis, Missouri 63110, USA. nenad@tci.wustl.edu
authors.forename: N M
authors.initials: NM
authors.lastname: Svrakic
authors.forename: O
authors.initials: O
authors.lastname: Nesic
authors.forename: M R K
authors.initials: MR
authors.lastname: Dasu
authors.forename: D
authors.initials: D
authors.lastname: Herndon
authors.forename: J R
authors.initials: JR
authors.lastname: Perez-Polo
mesh_terms: D000465:Algorithms; D020869:Gene Expression Profiling; D006801:Humans; D008433:Mathematics; D005810:Multigene Family; D009369:Neoplasms / Q000235:genetics; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods / Q000706:statistics & numerical data*; D013997:Time Factors