MD-Miner: a network-based approach for personalized drug repositioning.

ABSTRACT:

Background

Due to advances in next generation sequencing technologies and corresponding reductions in cost, it is now attainable to investigate genome-wide gene expression and variants at a patient-level, so as to better understand and anticipate heterogeneous responses to therapy. Consequently, it is feasible to inform personalized drug treatment decisions using personal genomics data. However, these efforts are limited due to a lack of reliable computational approaches for predicting effective drugs for individual patients. The reverse gene set enrichment analysis (i.e., connectivity mapping) approach and its variants have been widely and successfully used for drug prediction. However, the performance of these methods is limited by undefined mechanism of action (MoA) of drugs and

SUBMITTER: Wu H 

PROVIDER: S-EPMC5629618 | biostudies-literature | 2017 Oct

REPOSITORIES: biostudies-literature