Searching for Synergies: Matrix Algebraic Approaches for Efficient Pair Screening
Journal article, 2013

Functionally interacting perturbations, such as synergistic drugs pairs or synthetic lethal gene pairs, are of key interest in both pharmacology and functional genomics. However, to find such pairs by traditional screening methods is both time consuming and costly. We present a novel computational-experimental framework for efficient identification of synergistic target pairs, applicable for screening of systems with sizes on the order of current drug, small RNA or SGA (Synthetic Genetic Array) libraries (>1000 targets). This framework exploits the fact that the response of a drug pair in a given system, or a pair of genes' propensity to interact functionally, can be partly predicted by computational means from (i) a small set of experimentally determined target pairs, and (ii) pre-existing data (e.g. gene ontology, PPI) on the similarities between targets. Predictions are obtained by a novel matrix algebraic technique, based on cyclical projections onto convex sets. We demonstrate the efficiency of the proposed method using drug-drug interaction data from seven cancer cell lines and gene-gene interaction data from yeast SGA screens. Our protocol increases the rate of synergism discovery significantly over traditional screening, by up to 7-fold. Our method is easy to implement and could be applied to accelerate pair screening for both animal and microbial systems.


Philip Gerlee

University of Gothenburg

Chalmers, Mathematical Sciences, Mathematics

Linnéa Schmidt

University of Gothenburg

Naser Monsefi

University of Gothenburg

Teresia Kling

University of Gothenburg

Rebecka Jörnsten

Chalmers, Mathematical Sciences, Mathematical Statistics

University of Gothenburg

Sven Nelander

University of Gothenburg


1932-6203 (ISSN)

Vol. 8 7 Art. no. e68598- e68598

Subject Categories

Clinical Medicine



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