title: Pharmaceutical target identification by gene expression analysis.
abstract: The majority of newly-identified genes in the human genome show no significant sequence similarity to genes whose function is known, so they are not easily recognized as potential drug targets. Expression analysis is an alternative method to suggest possible functions of genes. We review statistical methods for gene expression analysis to identify potential pharmaceutical targets. Specifically, we illustrate the analysis of differential gene expression (using discriminant analysis, t-tests, and analysis of variance) and co-expression (using correlation, clustering, and chi-square). We present an example of the use of expression analysis to identify co-expressed cardiomyopathy-associated genes.
mesh_terms: D000704:Analysis of Variance; D002462:Cell Membrane / Q000187:drug effects; D015195:Drug Design; D005786:Gene Expression Regulation / Q000187:drug effects*; D005826:Genetics, Medical; D006801:Humans; D008969:Molecular Sequence Data; D009369:Neoplasms / Q000235:genetics; D012270:Ribosomes / Q000187:drug effects; D013329:Structure-Activity Relationship