Stochastic effects as a force to increase the complexity of signaling networks

Handle URI:
http://hdl.handle.net/10754/325386
Title:
Stochastic effects as a force to increase the complexity of signaling networks
Authors:
Kuwahara, Hiroyuki; Gao, Xin ( 0000-0002-7108-3574 )
Abstract:
Cellular signaling networks are complex and appear to include many nonfunctional elements. Recently, it was suggested that nonfunctional interactions of proteins cause signaling noise, which, perhaps, shapes the signal transduction mechanism. However, the conditions under which molecular noise influences cellular information processing remain unclear. Here, we explore a large number of simple biological models of varying network sizes to understand the architectural conditions under which the interactions of signaling proteins can exhibit specific stochastic effects - called deviant effects - in which the average behavior of a biological system is substantially altered in the presence of molecular noise. We find that a small fraction of these networks does exhibit deviant effects and shares a common architectural feature whereas most of the networks show only insignificant levels of deviations. Interestingly, addition of seemingly unimportant interactions into protein networks gives rise to deviant effects.
KAUST Department:
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Citation:
Kuwahara H, Gao X (2013) Stochastic effects as a force to increase the complexity of signaling networks. Sci Rep 3. doi:10.1038/srep02297.
Publisher:
Nature Publishing Group
Journal:
Scientific Reports
Issue Date:
29-Jul-2013
DOI:
10.1038/srep02297
PubMed ID:
23892365
PubMed Central ID:
PMC3725509
Type:
Article
ISSN:
20452322
Appears in Collections:
Articles; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

Full metadata record

DC FieldValue Language
dc.contributor.authorKuwahara, Hiroyukien
dc.contributor.authorGao, Xinen
dc.date.accessioned2014-08-27T09:50:14Z-
dc.date.available2014-08-27T09:50:14Z-
dc.date.issued2013-7-29en
dc.identifier.citationKuwahara H, Gao X (2013) Stochastic effects as a force to increase the complexity of signaling networks. Sci Rep 3. doi:10.1038/srep02297.en
dc.identifier.issn20452322en
dc.identifier.pmid23892365en
dc.identifier.doi10.1038/srep02297en
dc.identifier.urihttp://hdl.handle.net/10754/325386en
dc.description.abstractCellular signaling networks are complex and appear to include many nonfunctional elements. Recently, it was suggested that nonfunctional interactions of proteins cause signaling noise, which, perhaps, shapes the signal transduction mechanism. However, the conditions under which molecular noise influences cellular information processing remain unclear. Here, we explore a large number of simple biological models of varying network sizes to understand the architectural conditions under which the interactions of signaling proteins can exhibit specific stochastic effects - called deviant effects - in which the average behavior of a biological system is substantially altered in the presence of molecular noise. We find that a small fraction of these networks does exhibit deviant effects and shares a common architectural feature whereas most of the networks show only insignificant levels of deviations. Interestingly, addition of seemingly unimportant interactions into protein networks gives rise to deviant effects.en
dc.language.isoenen
dc.publisherNature Publishing Groupen
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-ShareALike 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-sa/3.0/en
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/3.0/en
dc.subjectproteinen
dc.subjectalgorithmen
dc.subjectbiological modelen
dc.subjectcomputer simulationen
dc.subjectmetabolismen
dc.subjectprotein bindingen
dc.subjectsignal transductionen
dc.subjectAlgorithmsen
dc.subjectComputer Simulationen
dc.subjectModels, Biologicalen
dc.subjectProtein Bindingen
dc.subjectProteinsen
dc.subjectSignal Transductionen
dc.titleStochastic effects as a force to increase the complexity of signaling networksen
dc.typeArticleen
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Divisionen
dc.identifier.journalScientific Reportsen
dc.identifier.pmcidPMC3725509en
dc.eprint.versionPublisher's Version/PDFen
dc.contributor.institutionUnidad Académica de Sistemas Arrecifales (Puerto Morelos), Instituto de Ciencias Del Mar y Limnología, Universidad Nacional Autõnoma de México, Puerto Morelos, QR 77580, Mexicoen
dc.contributor.institutionSchool of Natural Sciences, University of California Merced, 5200 North Lake Road, Merced, CA 95343, United Statesen
dc.contributor.affiliationKing Abdullah University of Science and Technology (KAUST)en
kaust.authorKuwahara, Hiroyukien
kaust.authorGao, Xinen

Related articles on PubMed

This item is licensed under a Creative Commons License
Creative Commons
All Items in KAUST are protected by copyright, with all rights reserved, unless otherwise indicated.