Bedoukian   RussellIPM   RussellIPM   Piezoelectric Micro-Sprayer


Home
Animal Taxa
Plant Taxa
Semiochemicals
Floral Compounds
Semiochemical Detail
Semiochemicals & Taxa
Synthesis
Control
Invasive spp.
References

Abstract

Guide

Alphascents
Pherobio
InsectScience
E-Econex
Counterpart-Semiochemicals
Print
Email to a Friend
Kindly Donate for The Pherobase

« Previous AbstractMethodology for selecting substances for the National Exposure Registry    Next AbstractAnimal interactions and the emergence of territoriality »

Nucleic Acids Res


Title:Discovering pathways by orienting edges in protein interaction networks
Author(s):Gitter A; Klein-Seetharaman J; Gupta A; Bar-Joseph Z;
Address:"Computer Science Department, Carnegie Mellon University, Pittsburgh, PA, USA"
Journal Title:Nucleic Acids Res
Year:2011
Volume:20101124
Issue:4
Page Number:e22 -
DOI: 10.1093/nar/gkq1207
ISSN/ISBN:1362-4962 (Electronic) 0305-1048 (Print) 0305-1048 (Linking)
Abstract:"Modern experimental technology enables the identification 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 signaling 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 orientation problem in weighted protein interaction graphs as an optimization problem and present three approximation algorithms based on either weighted Boolean satisfiability solvers or probabilistic assignments. 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 mechanisms that are not currently present in signaling databases. For some pathways, including the pheromone signaling pathway and the high-osmolarity glycerol pathway, our method suggests interesting and novel components that extend current annotations"
Keywords:*Algorithms Computer Simulation Protein Interaction Mapping/*methods *Signal Transduction Yeasts/metabolism;
Notes:"MedlineGitter, Anthony Klein-Seetharaman, Judith Gupta, Anupam Bar-Joseph, Ziv eng R01 GM085022/GM/NIGMS NIH HHS/ N01 AI-5001/AI/NIAID NIH HHS/ 1R01 GM085022/GM/NIGMS NIH HHS/ Evaluation Study Research Support, N.I.H., Extramural Research Support, U.S. Gov't, Non-P.H.S. England 2010/11/27 Nucleic Acids Res. 2011 Mar; 39(4):e22. doi: 10.1093/nar/gkq1207. Epub 2010 Nov 24"

 
Back to top
 
Citation: El-Sayed AM 2024. The Pherobase: Database of Pheromones and Semiochemicals. <http://www.pherobase.com>.
© 2003-2024 The Pherobase - Extensive Database of Pheromones and Semiochemicals. Ashraf M. El-Sayed.
Page created on 07-09-2024