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

  • Lê Đức Hậu Thuyloi University
Keywords: personalized medicine, omics data integration, patient stratification, drug response prediction, computational method

Abstract

Omics data (e.g., genomics, transcriptomics, pro-
teomics, epigenomics, etc . . . ) generated from high-throughput
next-generation sequencers in the big human genome, and
cancer genome projects have changed the way to study
personalized medicine. In the future, personalized medicine
is not limited to diagnosis and treatment based on a few
known disease-associated mutations on some genes, but relied
on whole molecular characteristics of patients by integrating
their omics data. In this study, we draw a big picture of
personalized medicine research in cancer research of the
omics data era, including omics databases, challenges of
data fusion to solve two major problems in personalized
medicine, i.e., personalized diagnosis and treatment. These
problems are approached as patient stratification and drug
response prediction based on the omics data by computa-
tional methods.

Published
2020-12-08
Section
Invited Articles