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Searching for Synergies: Matrix Algebraic Approaches for Efficient Pair Screening

Journal article
Authors Philip Gerlee
Linnéa Schmidt
Naser Monsefi
Teresia Kling
Rebecka Jörnsten
Sven Nelander
Published in PLoS ONE
Volume 8
Issue 7
Pages Art. no. e68598
ISSN 1932-6203
Publication year 2013
Published at Sahlgrenska Cancer Center
Department of Mathematical Sciences, Mathematical Statistics
Department of Mathematical Sciences, Mathematics
Pages Art. no. e68598
Language en
Links dx.doi.org/10.1371/journal.pone.006...
https://gup.ub.gu.se/file/192198
Subject categories Clinical Medicine

Abstract

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.

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