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Hellander, Stefan
Publications (10 of 17) Show all publications
Bouchnita, A., Hellander, S. & Hellander, A. (2019). A 3D multiscale model to explore the role of EGFR overexpression in tumourigenesis. Bulletin of Mathematical Biology, 81, 2323-2344
Open this publication in new window or tab >>A 3D multiscale model to explore the role of EGFR overexpression in tumourigenesis
2019 (English)In: Bulletin of Mathematical Biology, ISSN 0092-8240, E-ISSN 1522-9602, Vol. 81, p. 2323-2344Article in journal (Refereed) Published
National Category
Bioinformatics (Computational Biology)
Identifiers
urn:nbn:se:uu:diva-382735 (URN)10.1007/s11538-019-00607-y (DOI)000474571900011 ()31016574 (PubMedID)
Projects
eSSENCE
Available from: 2019-04-23 Created: 2019-04-30 Last updated: 2019-09-26Bibliographically approved
Hellander, S., Hellander, A. & Petzold, L. (2017). Mesoscopic-microscopic spatial stochastic simulation with automatic system partitioning. Journal of Chemical Physics, 147(23), Article ID 234101.
Open this publication in new window or tab >>Mesoscopic-microscopic spatial stochastic simulation with automatic system partitioning
2017 (English)In: Journal of Chemical Physics, ISSN 0021-9606, E-ISSN 1089-7690, Vol. 147, no 23, article id 234101Article in journal (Refereed) Published
Abstract [en]

The reaction-diffusion master equation (RDME) is a model that allows for efficient on-lattice simulation of spatially resolved stochastic chemical kinetics. Compared to off-lattice hard-sphere simulations with Brownian dynamics or Green's function reaction dynamics, the RDME can be orders of magnitude faster if the lattice spacing can be chosen coarse enough. However, strongly diffusion-controlled reactions mandate a very fine mesh resolution for acceptable accuracy. It is common that reactions in the same model differ in their degree of diffusion control and therefore require different degrees of mesh resolution. This renders mesoscopic simulation inefficient for systems with multiscale properties. Mesoscopic-microscopic hybrid methods address this problem by resolving the most challenging reactions with a microscale, off-lattice simulation. However, all methods to date require manual partitioning of a system, effectively limiting their usefulness as "black-box" simulation codes. In this paper, we propose a hybrid simulation algorithm with automatic system partitioning based on indirect a priori error estimates. We demonstrate the accuracy and efficiency of the method on models of diffusion-controlled networks in 3D.

National Category
Other Chemistry Topics
Identifiers
urn:nbn:se:uu:diva-339766 (URN)10.1063/1.5002773 (DOI)000418648200003 ()29272930 (PubMedID)
Funder
NIH (National Institute of Health), R01-EB014877Swedish Research Council, 2015-03964eSSENCE - An eScience Collaboration
Available from: 2018-02-09 Created: 2018-02-09 Last updated: 2018-02-09Bibliographically approved
Golkaram, M., Jang, J., Hellander, S., Kosik, K. S. & Petzold, L. R. (2017). The role of chromatin density in cell population heterogeneity during stem cell differentiation. Scientific Reports, 7, 13307:1-11, Article ID 13307.
Open this publication in new window or tab >>The role of chromatin density in cell population heterogeneity during stem cell differentiation
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2017 (English)In: Scientific Reports, ISSN 2045-2322, E-ISSN 2045-2322, Vol. 7, p. 13307:1-11, article id 13307Article in journal (Refereed) Published
National Category
Bioinformatics (Computational Biology)
Identifiers
urn:nbn:se:uu:diva-334978 (URN)10.1038/s41598-017-13731-3 (DOI)000413084800004 ()29042584 (PubMedID)
Projects
eSSENCE
Available from: 2017-10-17 Created: 2017-11-29 Last updated: 2018-02-07Bibliographically approved
Hellander, S., Hellander, A. & Petzold, L. (2015). Reaction rates for mesoscopic reaction-diffusion kinetics. Physical Review E. Statistical, Nonlinear, and Soft Matter Physics, 91, 023312:1-12, Article ID 023312.
Open this publication in new window or tab >>Reaction rates for mesoscopic reaction-diffusion kinetics
2015 (English)In: Physical Review E. Statistical, Nonlinear, and Soft Matter Physics, ISSN 1539-3755, E-ISSN 1550-2376, Vol. 91, p. 023312:1-12, article id 023312Article in journal (Refereed) Published
National Category
Computational Mathematics Biochemistry and Molecular Biology
Identifiers
urn:nbn:se:uu:diva-245747 (URN)10.1103/PhysRevE.91.023312 (DOI)000352064400018 ()
Projects
eSSENCE
Available from: 2015-02-23 Created: 2015-02-27 Last updated: 2017-12-04Bibliographically approved
Wang, S., Elf, J., Hellander, S. & Lötstedt, P. (2014). Stochastic reaction–diffusion processes with embedded lower-dimensional structures. Bulletin of Mathematical Biology, 76, 819-853
Open this publication in new window or tab >>Stochastic reaction–diffusion processes with embedded lower-dimensional structures
2014 (English)In: Bulletin of Mathematical Biology, ISSN 0092-8240, E-ISSN 1522-9602, Vol. 76, p. 819-853Article in journal (Refereed) Published
National Category
Computational Mathematics Biochemistry and Molecular Biology
Identifiers
urn:nbn:se:uu:diva-211350 (URN)10.1007/s11538-013-9910-x (DOI)000334933100004 ()
Projects
eSSENCE
Available from: 2013-10-26 Created: 2013-11-21 Last updated: 2017-12-06Bibliographically approved
Flegg, M. B., Hellander, S. & Erban, R. (2013). Convergence of methods for coupling of microscopic and mesoscopic reaction-diffusion simulations.
Open this publication in new window or tab >>Convergence of methods for coupling of microscopic and mesoscopic reaction-diffusion simulations
2013 (English)Report (Other academic)
Series
Technical report / Department of Information Technology, Uppsala University, ISSN 1404-3203 ; 2013-010
National Category
Computational Mathematics Biochemistry and Molecular Biology
Identifiers
urn:nbn:se:uu:diva-198521 (URN)
Projects
eSSENCE
Available from: 2013-04-18 Created: 2013-04-18 Last updated: 2013-05-21Bibliographically approved
Bani-Hashemian, M. H., Hellander, S. & Lötstedt, P. (2013). Efficient sampling in event-driven algorithms for reaction-diffusion processes. Communications in Computational Physics, 13, 958-984
Open this publication in new window or tab >>Efficient sampling in event-driven algorithms for reaction-diffusion processes
2013 (English)In: Communications in Computational Physics, ISSN 1815-2406, E-ISSN 1991-7120, Vol. 13, p. 958-984Article in journal (Refereed) Published
National Category
Computational Mathematics
Identifiers
urn:nbn:se:uu:diva-181793 (URN)10.4208/cicp.271011.230312a (DOI)000322065200002 ()
Projects
eSSENCE
Available from: 2012-09-21 Created: 2012-09-28 Last updated: 2017-12-07Bibliographically approved
Hellander, S. (2013). Single molecule simulations in complex geometries with embedded dynamic one-dimensional structures.
Open this publication in new window or tab >>Single molecule simulations in complex geometries with embedded dynamic one-dimensional structures
2013 (English)Report (Other academic)
Series
Technical report / Department of Information Technology, Uppsala University, ISSN 1404-3203 ; 2013-009
National Category
Computational Mathematics Biochemistry and Molecular Biology
Identifiers
urn:nbn:se:uu:diva-198504 (URN)
Projects
eSSENCE
Available from: 2013-04-16 Created: 2013-04-16 Last updated: 2013-05-06Bibliographically approved
Hellander, S. (2013). Single molecule simulations in complex geometries with embedded dynamic one-dimensional structures. Journal of Chemical Physics, 139, 014103:1-11
Open this publication in new window or tab >>Single molecule simulations in complex geometries with embedded dynamic one-dimensional structures
2013 (English)In: Journal of Chemical Physics, ISSN 0021-9606, E-ISSN 1089-7690, Vol. 139, p. 014103:1-11Article in journal (Refereed) Published
National Category
Computational Mathematics Biochemistry and Molecular Biology
Identifiers
urn:nbn:se:uu:diva-206449 (URN)10.1063/1.4811395 (DOI)000321716400005 ()
Projects
eSSENCE
Available from: 2013-07-01 Created: 2013-08-30 Last updated: 2017-12-06Bibliographically approved
Hellander, S. (2013). Stochastic Simulation of Reaction-Diffusion Processes. (Doctoral dissertation). Uppsala: Acta Universitatis Upsaliensis
Open this publication in new window or tab >>Stochastic Simulation of Reaction-Diffusion Processes
2013 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Numerical simulation methods have become an important tool in the study of chemical reaction networks in living cells. Many systems can, with high accuracy, be modeled by deterministic ordinary differential equations, but other systems require a more detailed level of modeling. Stochastic models at either the mesoscopic level or the microscopic level can be used for cases when molecules are present in low copy numbers.

In this thesis we develop efficient and flexible algorithms for simulating systems at the microscopic level. We propose an improvement to the Green's function reaction dynamics algorithm, an efficient microscale method. Furthermore, we describe how to simulate interactions with complex internal structures such as membranes and dynamic fibers.

The mesoscopic level is related to the microscopic level through the reaction rates at the respective scale. We derive that relation in both two dimensions and three dimensions and show that the mesoscopic model breaks down if the discretization of space becomes too fine. For a simple model problem we can show exactly when this breakdown occurs.

We show how to couple the microscopic scale with the mesoscopic scale in a hybrid method. Using the fact that some systems only display microscale behaviour in parts of the system, we can gain computational time by restricting the fine-grained microscopic simulations to only a part of the system.

Finally, we have developed a mesoscopic method that couples simulations in three dimensions with simulations on general embedded lines. The accuracy of the method has been verified by comparing the results with purely microscopic simulations as well as with theoretical predictions.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2013. p. 46
Series
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Science and Technology, ISSN 1651-6214 ; 1042
Keywords
stochastic simulation, microscale, mesoscale, Smoluchowski's equation, hybrid methods
National Category
Computational Mathematics Biochemistry and Molecular Biology
Research subject
Scientific Computing with specialization in Numerical Analysis
Identifiers
urn:nbn:se:uu:diva-198522 (URN)978-91-554-8667-9 (ISBN)
Public defence
2013-06-05, Room 2446, Polacksbacken, Lägerhyddsvägen 2D, Uppsala, 10:15 (English)
Opponent
Supervisors
Projects
eSSENCE
Available from: 2013-05-14 Created: 2013-04-18 Last updated: 2013-08-30Bibliographically approved
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