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

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Motivation: The underlying relationship between genomic factors and the response of diverse cancer drugs still remains unclear.A number of studies have shown that the heterogeneous responses to anticancer treatments of patients are 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 the early-phase clinical trials of the compounds under development.However, how to identify the underlying combinatorial patterns among the data is still a challenging issue.
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