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CellMC: a multiplatform model compiler for the Cell Broadband Engine and x86
Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för teknisk databehandling. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Tillämpad beräkningsvetenskap.
2010 (engelsk)Inngår i: Bioinformatics, ISSN 1367-4803, E-ISSN 1367-4811, Vol. 26, s. 426-428Artikkel i tidsskrift (Fagfellevurdert) Published
sted, utgiver, år, opplag, sider
2010. Vol. 26, s. 426-428
HSV kategori
Identifikatorer
URN: urn:nbn:se:uu:diva-111276DOI: 10.1093/bioinformatics/btp662ISI: 000274342800026OAI: oai:DiVA.org:uu-111276DiVA, id: diva2:280200
Prosjekter
eSSENCETilgjengelig fra: 2009-12-08 Laget: 2009-12-08 Sist oppdatert: 2018-01-12bibliografisk kontrollert
Inngår i avhandling
1. Multiscale Stochastic Simulation of Reaction-Transport Processes: Applications in Molecular Systems Biology
Åpne denne publikasjonen i ny fane eller vindu >>Multiscale Stochastic Simulation of Reaction-Transport Processes: Applications in Molecular Systems Biology
2011 (engelsk)Doktoravhandling, med artikler (Annet vitenskapelig)
Abstract [en]

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.

sted, utgiver, år, opplag, sider
Uppsala: Acta Universitatis Upsaliensis, 2011. s. 63
Serie
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Science and Technology, ISSN 1651-6214 ; 832
Emneord
stochastic simulation, chemical master equation, reaction-diffusion master equation, unstructured mesh, active transport, hybrid methods, URDME
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Forskningsprogram
Beräkningsvetenskap
Identifikatorer
urn:nbn:se:uu:diva-152098 (URN)978-91-554-8089-9 (ISBN)
Disputas
2011-06-10, Room 2446, Polacksbacken, Lägerhyddsvägen 2D, Uppsala, 10:15 (engelsk)
Opponent
Veileder
Prosjekter
eSSENCE
Tilgjengelig fra: 2011-05-19 Laget: 2011-04-23 Sist oppdatert: 2012-01-26bibliografisk kontrollert

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