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Selections for constituting new RNA–protein interactions in catalytic RNP

Nucleic Acids Research
Oxford University Press
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  • Biology
  • Computer Science


gkq1207 1..12 Discovering pathways by orienting edges in protein interaction networks Anthony Gitter1, Judith Klein-Seetharaman2, Anupam Gupta1 and Ziv Bar-Joseph1,* 1Computer Science Department, Carnegie Mellon University and 2Department of Structural Biology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA Received August 13, 2010; Revised October 24, 2010; Accepted November 8, 2010 ABSTRACT Modern experimental technology enables the iden- tification of the sensory proteins that interact with the cells’ environment or various pathogens. Expression and knockdown studies can determine the downstream effects of these interactions. However, when attempting to reconstruct the signal- ing networks and pathways between these sources and targets, one faces a substantial challenge. Although pathways are directed, high-throughput protein interaction data are undirected. In order to utilize the available data, we need methods that can orient protein interaction edges and discover high- confidence pathways that explain the observed experimental outcomes. We formalize the orienta- tion problem in weighted protein interaction graphs as an optimization problem and present three approximation algorithms based on either weighted Boolean satisfiability solvers or probabilistic assign- ments. We use these algorithms to identify pathways in yeast. Our approach recovers twice as many known signaling cascades as a recent unoriented signaling pathway prediction technique and over 13 times as many as an existing network orientation algorithm. The discovered paths match several known signaling pathways and suggest new mech- anisms that are not currently present in signaling databases. For some pathways, including the phero- mone signaling pathway and the high-osmolarity glycerol pathway, our method suggests inter- esting and novel components that extend current annotations. INTRODUCTION Reconstructing interaction networks in the cell is one of the great challenges of computational biology

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