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Science DOI:10.1126/science.1132939

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

Publication TypeJournal Article
Year of Publication2006
AuthorsLamb, J, Crawford, ED, Peck, D, Modell, JW, Blat, IC, Wrobel, MJ, Lerner, J, Brunet, J-P, Subramanian, A, Ross, KN, Reich, M, Hieronymus, H, Wei, G, Armstrong, SA, Haggarty, SJ, Clemons, PA, Wei, R, Carr, SA, Lander, ES, Golub, TR
JournalScience
Volume313
Issue5795
Pages1929-35
Date Published2006 Sep 29
ISSN1095-9203
KeywordsAlzheimer Disease, Cell Line, Cell Line, Tumor, Databases, Factual, Dexamethasone, Drug Evaluation, Preclinical, Drug Resistance, Neoplasm, Enzyme Inhibitors, Estrogens, Gene Expression, Gene Expression Profiling, Histone Deacetylase Inhibitors, HSP90 Heat-Shock Proteins, Humans, Limonins, Obesity, Oligonucleotide Array Sequence Analysis, Phenothiazines, Precursor Cell Lymphoblastic Leukemia-Lymphoma, Sirolimus, Software
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.

URLhttp://www.sciencemag.org/cgi/pmidlookup?view=long&pmid=17008526
DOI10.1126/science.1132939
Pubmed

http://www.ncbi.nlm.nih.gov/pubmed/17008526?dopt=Abstract

Alternate JournalScience
PubMed ID17008526