| 1. |
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| 2. |
- Bauer, Pavol, et al.
(author)
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URDME v. 1.2: User's manual
- 2012
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Reports (other academic/artistic)abstract
- We have developed URDME, a general software for simulation of stochastic reaction-diffusion processes on unstructured meshes. This allows for a more flexible handling of complicated geometries and curved boundaries compared to simulations on structured, cartesian meshes. The underlying algorithm is the next subvolume method, extended to unstructured meshes by obtaining jump coefficients from a finite element formulation of the corresponding macroscopic equation. This manual describes version 1.2 of the software. URDME 1.2 includes support for Comsol Multiphysics 4.1, 4.2, 4.3 as well as the previous version 3.5a. Additionally, support for basic SBML has been added along with the possibility to compile in stand-alone mode.
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| 3. |
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| 4. |
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| 5. |
- Drawert, Brian, et al.
(author)
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URDME v. 1.1: User's manual
- 2011
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Reports (other academic/artistic)abstract
- We have developed URDME, a general software for simulation of stochastic reaction-diffusion processes on unstructured meshes. This allows for a more flexible handling of complicated geometries and curved boundaries compared to simulations on structured, cartesian meshes. The underlying algorithm is the next subvolume method (NSM), extended to unstructured meshes by obtaining jump coefficients from the finite element formulation of the corresponding macroscopic equation. This manual describes the changes in the software compared to the previous version, URDME 1.0. Notable changes include support for Comsol Multiphysics 3.5a and a stronger decoupling between core simulation routines and the Matlab interface by making core solvers stand-alone executables. This opens up for more flexible simulation workflows when many realizations of the stochastic process need to be generated.
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| 6. |
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| 7. |
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| 8. |
- Jiang, Richard, et al.
(author)
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Epidemiological modeling in StochSS Live!
- 2021
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In: Bioinformatics. - : Oxford University Press. - 1367-4803 .- 1367-4811 .- 1460-2059. ; 37:17, s. 2787-2788
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Journal article (peer-reviewed)abstract
- We present StochSS Live!, a web-based service for modeling, simulation and analysis of a wide range of mathematical, biological and biochemical systems. Using an epidemiological model of COVID-19, we demonstrate the power of StochSS Live! to enable researchers to quickly develop a deterministic or a discrete stochastic model, infer its parameters and analyze the results.StochSS Live! is freely available at https://live.stochss.org/Supplementary data are available at Bioinformatics online.
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| 9. |
- Östberg, Per-Olov, et al.
(author)
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Abstractions for scaling escience applications to distributed computing environments : a StratUm Integration Case Study in Molecular Systems Biology
- 2012
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In: Bioinformatics. - SETUBAL : SCITEPRESS. - 9789898425904 ; , s. 290-294
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Conference paper (other academic/artistic)abstract
- Management of eScience computations and resulting data in distributed computing environments is complicated and often introduces considerable overhead. In this work we address a lack of integration tools that provide the abstraction levels, performance, and usability required to facilitate migration of eScience applications to distributed computing environments, In particular, we explore an approach to raising abstraction levels based on separation of computation design computation management and present StratUm, a computation enactment tool for distributed computing environments. Results are illustrated in a case study of integration of a software from the systems biology community with a grid computation management system.
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| 10. |
- Östberg, Per-Olov, 1973-, et al.
(author)
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Reducing Complexity in Management of eScience Computation
- 2012
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In: CCGrid 2012. - Los Alamitos, CA : IEEE. - 9781467313957 - 9780769546919 ; , s. 845-852
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Conference paper (peer-reviewed)abstract
- In this paper we address reduction of complexity in management of scientific computations in distributed computing environments. We explore an approach based on separation of computation design (application development) and distributed execution of computations, and investigate best practices for construction of virtual infrastructures for computational science - software systems that abstract and virtualize the processes of managing scientific computations on heterogeneous distributed resource systems. As a result we present StratUm, a toolkit for management of eScience computations. To illustrate use of the toolkit, we present it in the context of a case study where we extend the capabilities of an existing kinetic Monte Carlo software framework to utilize distributed computational resources. The case study illustrates a viable design pattern for construction of virtual infrastructures for distributed scientific computing. The resulting infrastructure is evaluated using a computational experiment from molecular systems biology.
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