Combinatorial therapy discovery using mixed integer linear programming.

ABSTRACT:

Motivation

Combinatorial therapies play increasingly important roles in combating complex diseases. Owing to the huge cost associated with experimental methods in identifying optimal drug combinations, computational approaches can provide a guide to limit the search space and reduce cost. However, few computational approaches have been developed for this purpose, and thus there is a great need of new algorithms for drug combination prediction.

Results

Here we proposed to formulate the optimal combinatorial therapy problem into two complementary mathematical algorithms, Balanced Target Set Cover (BTSC) and Minimum Off-Target Set Cover (MOTSC). Given a disease gene set, BTSC seeks a balanced solution that maximizes the coverage on the disease genes and minimizes the off-target

SUBMITTER: Pang K 

PROVIDER: S-EPMC4016706 | biostudies-literature | 2014 May

REPOSITORIES: biostudies-literature