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Please use this identifier to cite or link to this item: http://hdl.handle.net/2289/2312
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dc.contributor.authorKrishna, Sandeep-
dc.contributor.authorBanerjee, Bidisha-
dc.contributor.authorRamakrishnan, T.V.-
dc.contributor.authorShivashankar, G.V.-
dc.date.accessioned2007-05-16T05:55:38Z-
dc.date.available2007-05-16T05:55:38Z-
dc.date.issued2005-03-29-
dc.identifier.citationProceedings of the National Academy of Sciences of the U S A., 2005, Vol.102, p4771–4776en
dc.identifier.issn0027-8424-
dc.identifier.issn1091-6490 (Online)-
dc.identifier.urihttp://hdl.handle.net/2289/2312-
dc.descriptionRestricted Access. Please click on the alternative location for the open-access full text.en
dc.description.abstractGene expression noise results in protein number distributions ranging from long-tailed to Gaussian. We show how long-tailed distributions arise from a stochastic model of the constituent chemical reactions and suggest that, in conjunction with cooperative switches, they lead to more sensitive selection of a subpopulation of cells with high protein number than is possible with Gaussian distributions. Single-cell-tracking experiments are presented to validate some of the assumptions of the stochastic simulations. We also examine the effect of DNA looping on the shape of protein distributions. We further show that when switches are incorporated in the regulation of a gene via a feedback loop, the distributions can become bimodal. This might explain the bimodal distribution of certain morphogens during early embryogenesis.en
dc.format.extent529288 bytes-
dc.format.mimetypeapplication/pdf-
dc.language.isoenen
dc.publisherThe National Academy of Sciencesen
dc.relation.urihttp://dx.doi.org/10.1073/pnas.0406415102en
dc.rights2005 The National Academy of Sciencesen
dc.subjectfluctuationsen
dc.subjectgenetic switchesen
dc.subjectsingle cellen
dc.titleStochastic simulations of the origins and implications of long-tailed distributions in gene expressionen
dc.typeArticleen
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