Computational Personalized Medicine in Cancer Research in the -Omics Data Era

Abstract

Omics data (e.g., genomics, transcriptomics, proteomics, epigenomics, etc . . . ) generated from high-throughputnext-generation sequencers in the big human genome, andcancer genome projects have changed the way to studypersonalized medicine. In the future, personalized medicinewill not be limited to diagnosis and treatment based on afew known disease-associated mutations on some genes, butwill rely on whole molecular characteristics of patients byintegrating their –omics data. In this study, we draw a bigpicture of personalized medicine research in cancer researchof the –omics data era, including –omics databases, challengesof data fusion to solve two major problems in personalizedmedicine, i.e., personalized diagnosis and treatment. Theseproblems are approached as patient stratification and drugresponse prediction based on the –omics data by computational methods.