title: Systems genetics for drug target discovery.
abstract: The collection and analysis of genomic data has the potential to reveal novel druggable targets by providing insight into the genetic basis of disease. However, the number of drugs targeting new molecular entities, approved by the US Food and Drug Administration has not increased in the years since the collection of genomic data has become commonplace. The paucity of translatable results can be partly attributed to conventional analysis methods that test one gene at a time in an effort to identify disease-associated factors as candidate drug targets. By disengaging genetic factors from their position within the genetic regulatory system, much of the information stored within the genomic data set is lost. Here we discuss how genomic data is used to identify disease-associated genes or genomic regions, how disease-associated regions are validated as functional targets, and the role network analysis can play in bridging the gap between data generation and effective drug target identification.
authors.affiliation: Computational Genetics Laboratory Dartmouth Medical School, One Medical Center Drive, Lebanon, NH 03756, USA.
authors.forename: Nadia M
authors.initials: NM
authors.lastname: Penrod
authors.forename: Richard
authors.initials: R
authors.lastname: Cowper-Sal-lari
authors.forename: Jason H
authors.initials: JH
authors.lastname: Moore
mesh_terms: D000818:Animals; D030541:Databases, Genetic; D004194:Disease / Q000235:genetics*; D016503:Drug Delivery Systems; D055808:Drug Discovery; D023281:Genomics; D006801:Humans