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@inproceedings{850840,
author = {Barnat, Jiří and Brim, Luboš and Černá, Ivana and Dražan, Sven and Fabriková, Jana and Šafránek, David},
address = {Los Alamitos (California)},
booktitle = {International Workshop on High Performance Computational Systems Biology},
keywords = {biological networks; parallel model checking; dynamics systems; rectangular abstraction},
howpublished = {paměťový nosič},
language = {eng},
location = {Los Alamitos (California)},
isbn = {978-0-7695-3809-9},
pages = {81-90},
publisher = {IEEE Computer Society},
title = {Computational Analysis of Large-Scale Multi-Affine ODE Models},
url = {https://ieeexplore.ieee.org/document/5298697},
year = {2009}
}
TY - JOUR
ID - 850840
AU - Barnat, Jiří - Brim, Luboš - Černá, Ivana - Dražan, Sven - Fabriková, Jana - Šafránek, David
PY - 2009
TI - Computational Analysis of Large-Scale Multi-Affine ODE Models
PB - IEEE Computer Society
CY - Los Alamitos (California)
SN - 9780769538099
KW - biological networks
KW - parallel model checking
KW - dynamics systems
KW - rectangular abstraction
UR - https://ieeexplore.ieee.org/document/5298697
L2 - https://ieeexplore.ieee.org/document/5298697
N2 - A biological system as considered in systems biology is understood in the form of a network of interactions among individual biochemical species. Complexity of these networks is inherently enormous, even for simple (e.g., procaryotic) organisms. When modeling and analyzing dynamics of these networks, i.e., exploring how the species evolve in time, we have to fight even another level of complexity - the enormous state space. In this paper we deal with a class of biological models that can be described in terms of multi-affine dynamic systems. First, we present a prototype tool for parallel (distributed) analysis of multi-affine systems discretized into rectangles that adapts the approach of Belta et.al. Secondly, we propose heuristics that significantly increase applicability of the approach to large biological models. Effects of different settings of the heuristics is firstly compared on a set of experiments performed on small models. Subsequently, experiments on large models are provided as well.
ER -
BARNAT, Jiří, Luboš BRIM, Ivana ČERNÁ, Sven DRAŽAN, Jana FABRIKOVÁ a David ŠAFRÁNEK. Computational Analysis of Large-Scale Multi-Affine ODE Models. In \textit{International Workshop on High Performance Computational Systems Biology}. Los Alamitos (California): IEEE Computer Society. s.~81-90. ISBN~978-0-7695-3809-9. 2009.
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