Systems biology data analysis methodology in pharmacogenomics.

TitleSystems biology data analysis methodology in pharmacogenomics.
Publication TypeJournal Article
Year of Publication2011
AuthorsRodin, AS, Gogoshin, G, Boerwinkle, E
JournalPharmacogenomics
Volume12
Issue9
Pagination1349-60
Date Published2011 Sep
ISSN1744-8042
KeywordsArtificial Intelligence, Drug Discovery, Drug-Related Side Effects and Adverse Reactions, Epistasis, Genetic, Genotype, Humans, Molecular Epidemiology, Pharmacogenetics, Research Design, Statistics as Topic, Systems Biology
Abstract

Pharmacogenetics aims to elucidate the genetic factors underlying the individual's response to pharmacotherapy. Coupled with the recent (and ongoing) progress in high-throughput genotyping, sequencing and other genomic technologies, pharmacogenetics is rapidly transforming into pharmacogenomics, while pursuing the primary goals of identifying and studying the genetic contribution to drug therapy response and adverse effects, and existing drug characterization and new drug discovery. Accomplishment of both of these goals hinges on gaining a better understanding of the underlying biological systems; however, reverse-engineering biological system models from the massive datasets generated by the large-scale genetic epidemiology studies presents a formidable data analysis challenge. In this article, we review the recent progress made in developing such data analysis methodology within the paradigm of systems biology research that broadly aims to gain a 'holistic', or 'mechanistic' understanding of biological systems by attempting to capture the entirety of interactions between the components (genetic and otherwise) of the system.

DOI10.2217/pgs.11.76
Alternate JournalPharmacogenomics
PubMed ID21919609
PubMed Central IDPMC3482399
Grant ListRC2 HL102419 / HL / NHLBI NIH HHS / United States
5RC2HL102419 / HL / NHLBI NIH HHS / United States
U01 GM074492 / GM / NIGMS NIH HHS / United States
5R01HL083498 / HL / NHLBI NIH HHS / United States
R01 HL072810 / HL / NHLBI NIH HHS / United States
R01 HL083498 / HL / NHLBI NIH HHS / United States
U01 HG004402 / HG / NHGRI NIH HHS / United States
R03 LM009738 / LM / NLM NIH HHS / United States
5R01HL086694 / HL / NHLBI NIH HHS / United States
P50 GM065509 / GM / NIGMS NIH HHS / United States
5R03LM009738 / LM / NLM NIH HHS / United States
5P50GM065509 / GM / NIGMS NIH HHS / United States
5R01HL084099 / HL / NHLBI NIH HHS / United States
2U01GM074492 / GM / NIGMS NIH HHS / United States
R01 HL084099 / HL / NHLBI NIH HHS / United States
5R01HL072810 / HL / NHLBI NIH HHS / United States
R01 AI085014 / AI / NIAID NIH HHS / United States
1R01AI085014 / AI / NIAID NIH HHS / United States
3U01HG004402 / HG / NHGRI NIH HHS / United States