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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, 2009, s.~81-90. ISBN~978-0-7695-3809-9.
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