Searching for Synergies: Matrix Algebraic Approaches for Efficient Pair Screening
Artikel i vetenskaplig tidskrift, 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

Göteborgs universitet

Chalmers, Matematiska vetenskaper, Matematik

Linnéa Schmidt

Göteborgs universitet

Naser Monsefi

Göteborgs universitet

Teresia Kling

Göteborgs universitet

Rebecka Jörnsten

Chalmers, Matematiska vetenskaper, matematisk statistik

Göteborgs universitet

Sven Nelander

Göteborgs universitet


1932-6203 (ISSN)

Vol. 8 Art. no. e68598- e68598


Klinisk medicin