Zobrazeno 1 - 10
of 100
pro vyhledávání: '"Per Lötstedt"'
Autor:
Brian Drawert, Andreas Hellander, Ben Bales, Debjani Banerjee, Giovanni Bellesia, Bernie J Daigle, Geoffrey Douglas, Mengyuan Gu, Anand Gupta, Stefan Hellander, Chris Horuk, Dibyendu Nath, Aviral Takkar, Sheng Wu, Per Lötstedt, Chandra Krintz, Linda R Petzold
Publikováno v:
PLoS Computational Biology, Vol 12, Iss 12, p e1005220 (2016)
We present StochSS: Stochastic Simulation as a Service, an integrated development environment for modeling and simulation of both deterministic and discrete stochastic biochemical systems in up to three dimensions. An easy to use graphical user inter
Externí odkaz:
https://doaj.org/article/18063e6d0322453cbf5a038b4b43f620
Autor:
Per Lötstedt
Publikováno v:
Journal of Mathematical Biology
In certain discrete models of populations of biological cells, the mechanical forces between the cells are center based or vertex based on the microscopic level where each cell is individually represented. The cells are circular or spherical in a cen
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::db7d9c29dca2ecd6b6260470acdaca63
http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-462440
http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-462440
Predictions of future mass loss from ice sheets are afflicted with uncertainty, caused, among others, by insufficient understanding of spatio-temporally variable processes at the inaccessible base of ice sheets for which few direct observations exist
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cf9971290e83f5e1017c33d1f9094b8e
https://www.the-cryosphere-discuss.net/tc-2020-108/
https://www.the-cryosphere-discuss.net/tc-2020-108/
Autor:
Per Lötstedt
Publikováno v:
Bulletin of Mathematical Biology
An algorithm for computing the linear noise approximation (LNA) of the reaction–diffusion master equation (RDME) is developed and tested. The RDME is often used as a model for biochemical reaction networks. The LNA is derived for a general discreti
Autor:
Per Lötstedt, Zahedeh Bashardanesh
Publikováno v:
Journal of Computational Physics. 357:78-99
Efficient Green's function reaction dynamics (GFRD) simulations for diffusion-limited, reversible reactions
Publikováno v:
SIAM Journal on Applied Mathematics. 77:1157-1183
© 2017 Society for Industrial and Applied Mathematics. We analyze the governing partial differential equations of a model of pole-to-pole oscillations of the MinD protein in a bacterial cell. The sensitivity to extrinsic noise in the parameters of t
The full Stokes equations are solved by a finite element method for simulation of large ice sheets and glaciers. The simulation is particularly sensitive to the discretization of the grounding line which separates the ice resting on the bedrock and t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0bf12649ec91feff835ecac0a9455409
https://doi.org/10.5194/gmd-2019-244
https://doi.org/10.5194/gmd-2019-244
Autor:
Per Lötstedt, Gong Cheng
The friction coefficient and the base topography of a stationary and a dynamic ice sheet are perturbed in two models for the ice: the full Stokes equations and the shallow shelf approximation. The sensitivity to the perturbations of the velocity and
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1eab5dcb0595ab9bae490e813da900af
Autor:
Eef C. H. van Dongen, Nina Kirchner, Martin B. van Gijzen, Roderik S. W. van de Wal, Thomas Zwinger, Gong Cheng, Per Lötstedt, Lina von Sydow
Publikováno v:
Geoscientific Model Development, 11(11)
Geoscientific Model Development, 11 (11)
Geoscientific Model Development, 11 (11)
Ice flow forced by gravity is governed by the Full Stokes (FS) equations, which are computationally expensive to solve due to their non-linearity introduced by the rheology. Therefore, approximations to the FS equations are used, especially when mode
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::573b5e0b630a46f0c4d504893ffff7b2
http://resolver.tudelft.nl/uuid:ac82750a-300e-4aa8-8fb3-c4eeade2bf18
http://resolver.tudelft.nl/uuid:ac82750a-300e-4aa8-8fb3-c4eeade2bf18
We develop a mesoscopic modeling framework for diffusion in a crowded environment, particularly targeting applications in the modeling of living cells. Through homogenization techniques we effectively coarse grain a detailed microscopic description i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b42d336c2a364c617669fa94ea3e0fc6
http://arxiv.org/abs/1707.05998
http://arxiv.org/abs/1707.05998