title: Mining functional relationships in feature subspaces from gene expression profiles and drug activity profiles.
abstract: 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.
authors.affiliation: Institute of Bioinformatics, Department of Biological Sciences and Biotechnology, Tsinghua University, 100084, Beijing, PR China.
authors.forename: Lei
authors.initials: L
authors.lastname: Bao
authors.forename: Tao
authors.initials: T
authors.lastname: Guo
authors.forename: Zhirong
authors.initials: Z
authors.lastname: Sun
mesh_terms: D000970:Antineoplastic Agents / Q000494:pharmacology*; D003627:Data Interpretation, Statistical; D015870:Gene Expression / Q000187:drug effects; D020869:Gene Expression Profiling / Q000706:statistics & numerical data; D006801:Humans; D008954:Models, Biological; D009369:Neoplasms / Q000188:drug therapy / Q000235:genetics; D014407:Tumor Cells, Cultured
chemical_list: D000970:Antineoplastic Agents