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dc.contributor.authorKates-Harbeck, Julian
dc.contributor.authorTilloy, Antoine
dc.contributor.authorPrentiss, Mara
dc.date.accessioned2019-10-03T14:39:43Z
dc.date.issued2013
dc.identifier.citationKates-Harbeck, Julian, Antoine Tilloy, and Mara Prentiss. 2013. “Simplified Biased Random Walk Model for RecA-Protein-Mediated Homology Recognition Offers Rapid and Accurate Self-Assembly of Long Linear Arrays of Binding Sites.” Physical Review E 88 (1). https://doi.org/10.1103/physreve.88.012702.
dc.identifier.issn1539-3755
dc.identifier.issn1550-2376
dc.identifier.urihttp://nrs.harvard.edu/urn-3:HUL.InstRepos:41461286*
dc.description.abstractInspired by RecA-protein-based homology recognition, we consider the pairing of two long linear arrays of binding sites. We propose a fully reversible, physically realizable biased random walk model for rapid and accurate self-assembly due to the spontaneous pairing of matching binding sites, where the statistics of the searched sample are included. In the model, there are two bound conformations, and the free energy for each conformation is a weakly nonlinear function of the number of contiguous matched bound sites.
dc.language.isoen_US
dc.publisherAmerican Physical Society
dash.licenseOAP
dc.titleSimplified biased random walk model for RecA-protein-mediated homology recognition offers rapid and accurate self-assembly of long linear arrays of binding sites
dc.typeJournal Article
dc.description.versionAccepted Manuscript
dc.relation.journalPhysical Review E - Statistical, Nonlinear, and Soft Matter Physics
dash.depositing.authorPrentiss, Mara::6d301a8de03860625d7558e450f9a0ca::600
dc.date.available2019-10-03T14:39:43Z
dash.workflow.comments1Science Serial ID 80536
dc.identifier.doi10.1103/PhysRevE.88.012702
dash.source.volume88;1
dash.source.page12702


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