Pathway-based drug repositioning using causal inference.

ABSTRACT:

Background

Recent in vivo studies showed new hopes of drug repositioning through causality inference from drugs to disease. Inspired by their success, here we present an in silico method for building a causal network (CauseNet) between drugs and diseases, in an attempt to systematically identify new therapeutic uses of existing drugs.

Methods

Unlike the traditional 'one drug-one target-one disease' causal model, we simultaneously consider all possible causal chains connecting drugs to diseases via target- and gene-involved pathways based on rich information in several expert-curated knowledge-bases. With statistical learning, our method estimates transition likelihood of each causal chain in the network based on known drug-disease treatment associations (e.g. bexarotene trea

SUBMITTER: Li J 

PROVIDER: S-EPMC3853312 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature