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Mining functional relationships in feature subspaces from gene expression profiles and drug activity profiles
Author(s) -
Bao Lei,
Guo Tao,
Sun Zhirong
Publication year - 2002
Publication title -
febs letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.593
H-Index - 257
eISSN - 1873-3468
pISSN - 0014-5793
DOI - 10.1016/s0014-5793(02)02515-2
Subject(s) - feature (linguistics) , gene expression , linear subspace , computational biology , drug , expression (computer science) , gene , biology , genetics , pattern recognition (psychology) , computer science , artificial intelligence , mathematics , pharmacology , philosophy , linguistics , geometry , programming language
In an effort to determine putative functional relationships between gene expression patterns and drug activity patterns of 60 human cancer cell lines, a novel method was developed to discover local associations within cell line subsets. The association of drug–gene pairs is an explorative way of discovering gene markers that predict clinical tumor sensitivity to therapy. Nine drug–gene networks were discovered, as well as dozens of gene–gene and drug–drug networks. Three drug–gene networks with well studied members were discussed and the literature shows that hypothetical functional relationships exist. Therefore, this method enables the gathering of new information beyond global associations.