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dc.contributor.authorLi, Tiejun
dc.contributor.authorLi, Fangting
dc.contributor.authorLi, Xianggang
dc.contributor.authorLu, Cheng
dc.date.accessioned2017-06-08T06:32:29Z
dc.date.available2017-06-08T06:32:29Z
dc.date.issued2016-01-07
dc.identifier.urihttp://hdl.handle.net/10754/624856
dc.description.abstractThe construction of energy landscape for bio-dynamics is attracting more and more attention recent years. In this talk, I will introduce the strategy to construct the landscape from the connection to rare events, which relies on the large deviation theory for Gillespie-type jump dynamics. In the application to a typical genetic switching model, the two-scale large deviation theory is developed to take into account the fast switching of DNA states. The comparison with other proposals are also discussed. We demonstrate different diffusive limits arise when considering different regimes for genetic translation and switching processes.
dc.relation.urlhttp://mediasite.kaust.edu.sa/Mediasite/Play/dbdb315ec34c4d3b89ebb53fb41c19fa1d?catalog=ca65101c-a4eb-4057-9444-45f799bd9c52
dc.titleQuasi-potential and Two-Scale Large Deviation Theory for Gillespie Dynamics
dc.typePresentation
dc.conference.dateJanuary 5-10, 2016
dc.conference.nameAdvances in Uncertainty Quantification Methods, Algorithms and Applications (UQAW 2016)
dc.conference.locationKAUST
dc.contributor.institutionPeking University
refterms.dateFOA2018-06-13T14:50:04Z


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