The Connectivity Map: using gene-expression signatures to connect small molecules, genes, and disease

Lamb J, Crawford ED, Peck D, Modell JW, Blat IC, Wrobel MJ, Lerner J, Brunet JP, Subramanian A, Ross KN, et al. The Connectivity Map: using gene-expression signatures to connect small molecules, genes, and disease. Science. 2006;313:1929–35.

NOTES

Lamb, JustinCrawford, Emily DPeck, DavidModell, Joshua WBlat, Irene CWrobel, Matthew JLerner, JimBrunet, Jean-PhilippeSubramanian, AravindRoss, Kenneth NReich, MichaelHieronymus, HaleyWei, GuoArmstrong, Scott AHaggarty, Stephen JClemons, Paul AWei, RuCarr, Steven ALander, Eric SGolub, Todd RengResearch Support, N.I.H., ExtramuralResearch Support, Non-U.S. Gov'tScience. 2006 Sep 29;313(5795):1929-35. doi: 10.1126/science.1132939.

Abstract

To pursue a systematic approach to the discovery of functional connections among diseases, genetic perturbation, and drug action, we have created the first installment of a reference collection of gene-expression profiles from cultured human cells treated with bioactive small molecules, together with pattern-matching software to mine these data. We demonstrate that this "Connectivity Map" resource can be used to find connections among small molecules sharing a mechanism of action, chemicals and physiological processes, and diseases and drugs. These results indicate the feasibility of the approach and suggest the value of a large-scale community Connectivity Map project.
Last updated on 02/17/2021