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Characterizing activating and inhibiting protein interactions based on a genome-wide siRNA cellular phenotyping screen

Apichat Suratanee(1,2), Martin H. Schaefer(3), Zita Soons(1,2), Heiko Mannsperger(1,2), Nathalie Harder(1,2), Marcus Oswald(1,2), Markus Gipp(4), Ellen Ramminger(5), Guillermo Marcus(4), Reinhard Männer(4), Karl Rohr(1,2), Erich Wanker(3,5), Miguel A. Andrade-Navarro(3), Roland Eils(1,2, *), Rainer König(1,2, *)

1 Department of Bioinformatics and Functional Genomics, Institute of Pharmacy and Molecular Biotechnology, BioQuant, University of Heidelberg, INF 267, 69120 Heidelberg, Germany 2 Division of Theoretical Bioinformatics, German Cancer Research Center, INF 280, 69120 Heidelberg, Germany 3 Computational Biology and Data Mining Group, Max Delbrueck Center for Molecular Medicine, 13092 Berlin, Germany 4 Department of Computer Science V, Institute of Computer Engineering, University of Mannheim, B6, 26, 68131 Mannheim, Germany 5 AG Neuroproteomics, Max Delbrueck Center for Molecular Medicine, 13092 Berlin, Germany

Characterizing the activating and inhibiting effect of protein-protein interactions (PPI) is fundamental to gain insight into the complex signaling system of a human cell. A plethora of methods has been suggested to infer PPI from data, but none of them is able to characterize the effect of this interaction. We presented a novel computational development that employs mitotic phenotypes of a genome-wide RNAi knockdown screen and enables identifying the activating and inhibiting effects of PPIs (Suratanee et al., submitted). This webpage contains the accompanying software for this study.

System requirements

R package (version 2.15.0 or higher) with installed libraries e1071, MASS and ROCR.
GNU Linear Programming Kit (GLPK)


Short manual

Please cite: Suratanee A, Schaefer MH, Betts MJ, Soons Z, Mannsperger H, Harder N, et al. Characterizing protein interactions employing a genome-wide siRNA cellular phenotyping screen. PLoS Comput Biol. 2014;10(9):e1003814.

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