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dc.contributor.authorGovern, Christopher C.
dc.contributor.authorChakraborty, Arup K
dc.date.accessioned2013-09-27T17:11:49Z
dc.date.available2013-09-27T17:11:49Z
dc.date.issued2013-08
dc.date.submitted2013-03
dc.identifier.issn1932-6203
dc.identifier.urihttp://hdl.handle.net/1721.1/81224
dc.description.abstractTwo theories have emerged for the role that stochasticity plays in biological responses: first, that it degrades biological responses, so the performance of biological signaling machinery could be improved by increasing molecular copy numbers of key proteins; second, that it enhances biological performance, by enabling diversification of population-level responses. Using T cell biology as an example, we demonstrate that these roles for stochastic responses are not sufficient to understand experimental observations of stochastic response in complex biological systems that utilize environmental and genetic diversity to make cooperative responses. We propose a new role for stochastic responses in biology: they enable populations to make complex responses with simpler biochemical signaling machinery than would be required in the absence of stochasticity. Thus, the evolution of stochastic responses may be linked to the evolvability of different signaling machineries.en_US
dc.description.sponsorshipNational Institutes of Health (U.S.). Pioneer Awarden_US
dc.language.isoen_US
dc.publisherPublic Library of Scienceen_US
dc.relation.isversionofhttp://dx.doi.org/10.1371/journal.pone.0065086en_US
dc.rightsCreative Commons Attributionen_US
dc.rights.urihttp://creativecommons.org/licenses/by/2.5/en_US
dc.sourcePLoSen_US
dc.titleStochastic Responses May Allow Genetically Diverse Cell Populations to Optimize Performance with Simpler Signaling Networksen_US
dc.typeArticleen_US
dc.identifier.citationGovern, Christopher C., and Arup K. Chakraborty. “Stochastic Responses May Allow Genetically Diverse Cell Populations to Optimize Performance with Simpler Signaling Networks.” Edited by Michael Polymenis. PLoS ONE 8, no. 8 (August 7, 2013): e65086.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Institute for Medical Engineering & Scienceen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Biological Engineeringen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Chemical Engineeringen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Chemistryen_US
dc.contributor.departmentRagon Institute of MGH, MIT and Harvarden_US
dc.contributor.mitauthorChakraborty, Arup K.en_US
dc.contributor.mitauthorGovern, Christopher C.en_US
dc.relation.journalPLoS ONEen_US
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dspace.orderedauthorsGovern, Christopher C.; Chakraborty, Arup K.en_US
dc.identifier.orcidhttps://orcid.org/0000-0003-1268-9602
mit.licensePUBLISHER_CCen_US
mit.metadata.statusComplete


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