Integrative analysis for identifying joint modular patterns of gene-expression and drug-response data | Zendy

Jinyu Chen | Zendy; Shihua Zhang | Zendy

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Integrative analysis for identifying joint modular patterns of gene-expression and drug-response data

Author(s) -

Jinyu Chen,

Shihua Zhang

Publication year - 2016

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btw059

Subject(s) - pharmacogenomics , computational biology , pairwise comparison , drug , gene , gene expression , cancer , modular design , biology , bioinformatics , computer science , pharmacology , genetics , artificial intelligence , operating system

The underlying relationship between genomic factors and the response of diverse cancer drugs still remains unclear. A number of studies showed that the heterogeneous responses to anticancer treatments of patients were partly associated with their specific changes in gene expression and somatic alterations. The emerging large-scale pharmacogenomic data provide us valuable opportunities to improve existing therapies or to guide early-phase clinical trials of compounds under development. However, how to identify the underlying combinatorial patterns among pharmacogenomics data are still a challenging issue.

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