A phenome-guided drug repositioning through a latent variable model.

ABSTRACT:

Background

The phenome represents a distinct set of information in the human population. It has been explored particularly in its relationship with the genome to identify correlations for diseases. The phenome has been also explored for drug repositioning with efforts focusing on the search space for the most similar candidate drugs. For a comprehensive analysis of the phenome, we assumed that all phenotypes (indications and side effects) were inter-connected with a probabilistic distribution and this characteristic may offer an opportunity to identify new therapeutic indications for a given drug. Correspondingly, we employed Latent Dirichlet Allocation (LDA), which introduces latent variables (topics) to govern the phenome distribution.

Results

We developed our model on the

SUBMITTER: Bisgin H 

PROVIDER: S-EPMC4137076 | biostudies-literature | 2014 Aug

REPOSITORIES: biostudies-literature