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Multiscale Stochastic Simulation of Reaction-Transport Processes: Applications in Molecular Systems BiologyPrimeFaces.cw("AccordionPanel","widget_formSmash_some",{id:"formSmash:some",widgetVar:"widget_formSmash_some",multiple:true}); PrimeFaces.cw("AccordionPanel","widget_formSmash_all",{id:"formSmash:all",widgetVar:"widget_formSmash_all",multiple:true});
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PrimeFaces.cw("AccordionPanel","widget_formSmash_responsibleOrgs",{id:"formSmash:responsibleOrgs",widgetVar:"widget_formSmash_responsibleOrgs",multiple:true}); 2011 (English)Doctoral thesis, comprehensive summary (Other academic)
##### Abstract [en]

##### Place, publisher, year, edition, pages

Uppsala: Acta Universitatis Upsaliensis , 2011. , 63 p.
##### Series

Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Science and Technology, ISSN 1651-6214 ; 832
##### Keyword [en]

stochastic simulation, chemical master equation, reaction-diffusion master equation, unstructured mesh, active transport, hybrid methods, URDME
##### National Category

Computational Mathematics
##### Research subject

Scientific Computing
##### Identifiers

URN: urn:nbn:se:uu:diva-152098ISBN: 978-91-554-8089-9 (print)OAI: oai:DiVA.org:uu-152098DiVA: diva2:412484
##### Public defence

2011-06-10, Room 2446, Polacksbacken, Lägerhyddsvägen 2D, Uppsala, 10:15 (English)
##### Opponent

PrimeFaces.cw("AccordionPanel","widget_formSmash_j_idt1095",{id:"formSmash:j_idt1095",widgetVar:"widget_formSmash_j_idt1095",multiple:true});
##### Supervisors

PrimeFaces.cw("AccordionPanel","widget_formSmash_j_idt1101",{id:"formSmash:j_idt1101",widgetVar:"widget_formSmash_j_idt1101",multiple:true});
#####

PrimeFaces.cw("AccordionPanel","widget_formSmash_j_idt1107",{id:"formSmash:j_idt1107",widgetVar:"widget_formSmash_j_idt1107",multiple:true});
##### Projects

eSSENCE
Available from: 2011-05-19 Created: 2011-04-23 Last updated: 2012-01-26Bibliographically approved
##### List of papers

Quantitative descriptions of reaction kinetics formulated at the stochastic mesoscopic level are frequently used to study various aspects of regulation and control in models of cellular control systems. For this type of systems, numerical simulation offers a variety of challenges caused by the high dimensionality of the problem and the multiscale properties often displayed by the biochemical model.

In this thesis I have studied several aspects of stochastic simulation of both well-stirred and spatially heterogenous systems. In the well-stirred case, a hybrid method is proposed that reduces the dimension and stiffness of a model. We also demonstrate how both a high performance implementation and a variance reduction technique based on quasi-Monte Carlo can reduce the computational cost to estimate the probability density of the system.

In the spatially dependent case, the use of unstructured, tetrahedral meshes to sample realizations of the stochastic process is proposed. Using such meshes, we then extend the reaction-diffusion framework to incorporate active transport of cellular cargo in a seamless manner. Finally, two multilevel methods for spatial stochastic simulation are considered. One of them is a space-time adaptive method combining exact stochastic, approximate stochastic and macroscopic modeling levels to reduce the simualation cost. The other method blends together mesoscale and microscale simulation methods to locally increase modeling resolution.

1. Hybrid method for the chemical master equation$(function(){PrimeFaces.cw("OverlayPanel","overlay54649",{id:"formSmash:j_idt1143:0:j_idt1147",widgetVar:"overlay54649",target:"formSmash:j_idt1143:0:partsLink",showEvent:"mousedown",hideEvent:"mousedown",showEffect:"blind",hideEffect:"fade",appendToBody:true});});

2. CellMC: a multiplatform model compiler for the Cell Broadband Engine and x86$(function(){PrimeFaces.cw("OverlayPanel","overlay280200",{id:"formSmash:j_idt1143:1:j_idt1147",widgetVar:"overlay280200",target:"formSmash:j_idt1143:1:partsLink",showEvent:"mousedown",hideEvent:"mousedown",showEffect:"blind",hideEffect:"fade",appendToBody:true});});

3. Efficient computation of transient solutions of the chemical master equation based on uniformization and quasi-Monte Carlo$(function(){PrimeFaces.cw("OverlayPanel","overlay43876",{id:"formSmash:j_idt1143:2:j_idt1147",widgetVar:"overlay43876",target:"formSmash:j_idt1143:2:partsLink",showEvent:"mousedown",hideEvent:"mousedown",showEffect:"blind",hideEffect:"fade",appendToBody:true});});

4. Simulation of stochastic reaction-diffusion processes on unstructured meshes$(function(){PrimeFaces.cw("OverlayPanel","overlay172726",{id:"formSmash:j_idt1143:3:j_idt1147",widgetVar:"overlay172726",target:"formSmash:j_idt1143:3:partsLink",showEvent:"mousedown",hideEvent:"mousedown",showEffect:"blind",hideEffect:"fade",appendToBody:true});});

5. Incorporating active transport of cellular cargo in stochastic mesoscopic models of living cells$(function(){PrimeFaces.cw("OverlayPanel","overlay353558",{id:"formSmash:j_idt1143:4:j_idt1147",widgetVar:"overlay353558",target:"formSmash:j_idt1143:4:partsLink",showEvent:"mousedown",hideEvent:"mousedown",showEffect:"blind",hideEffect:"fade",appendToBody:true});});

6. An adaptive algorithm for simulation of stochastic reaction-diffusion processes$(function(){PrimeFaces.cw("OverlayPanel","overlay241523",{id:"formSmash:j_idt1143:5:j_idt1147",widgetVar:"overlay241523",target:"formSmash:j_idt1143:5:partsLink",showEvent:"mousedown",hideEvent:"mousedown",showEffect:"blind",hideEffect:"fade",appendToBody:true});});

7. Coupled mesoscopic and microscopic simulation of stochastic reaction-diffusion processes in mixed dimensions$(function(){PrimeFaces.cw("OverlayPanel","overlay413048",{id:"formSmash:j_idt1143:6:j_idt1147",widgetVar:"overlay413048",target:"formSmash:j_idt1143:6:partsLink",showEvent:"mousedown",hideEvent:"mousedown",showEffect:"blind",hideEffect:"fade",appendToBody:true});});

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