KLARNER, Hannes, Adam STRECK, David ŠAFRÁNEK, Juraj KOLČÁK a Heike SIEBERT. Parameter Identification and Model Ranking of Thomas Networks. In Computational Methods in Systems Biology: 10th International Conference, CMSB 2012, London, UK, October 3-5, 2012. Proceedings. Berlin: Springer, 2012, s. 207-226. ISBN 978-3-642-33635-5. Dostupné z: https://dx.doi.org/10.1007/978-3-642-33636-2_13. |
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@inproceedings{1071805, author = {Klarner, Hannes and Streck, Adam and Šafránek, David and Kolčák, Juraj and Siebert, Heike}, address = {Berlin}, booktitle = {Computational Methods in Systems Biology: 10th International Conference, CMSB 2012, London, UK, October 3-5, 2012. Proceedings}, doi = {http://dx.doi.org/10.1007/978-3-642-33636-2_13}, keywords = {Thomas network; parameter identification; model checking}, howpublished = {tištěná verze "print"}, language = {eng}, location = {Berlin}, isbn = {978-3-642-33635-5}, pages = {207-226}, publisher = {Springer}, title = {Parameter Identification and Model Ranking of Thomas Networks}, url = {http://link.springer.com/chapter/10.1007/978-3-642-33636-2_13}, year = {2012} }
TY - JOUR ID - 1071805 AU - Klarner, Hannes - Streck, Adam - Šafránek, David - Kolčák, Juraj - Siebert, Heike PY - 2012 TI - Parameter Identification and Model Ranking of Thomas Networks PB - Springer CY - Berlin SN - 9783642336355 KW - Thomas network KW - parameter identification KW - model checking UR - http://link.springer.com/chapter/10.1007/978-3-642-33636-2_13 L2 - http://link.springer.com/chapter/10.1007/978-3-642-33636-2_13 N2 - We propose a new methodology for identification and analysis of discrete gene networks as defined by René Thomas, supported by a tool chain: (i) given a Thomas network with partially known kinetic parameters, we reduce the number of acceptable parametrizations to those that fit time-series measurements and reflect other known constraints by an improved technique of coloured LTL model checking performing efficiently on Thomas networks in distributed environment; (ii) we introduce classification of acceptable parametrizations to identify most optimal ones; (iii) we propose two ways of visualising parametrizations dynamics wrt time-series data. Finally, computational efficiency is evaluated and the methodology is validated on bacteriophage \lambda case study. ER -
KLARNER, Hannes, Adam STRECK, David ŠAFRÁNEK, Juraj KOLČÁK a Heike SIEBERT. Parameter Identification and Model Ranking of Thomas Networks. In \textit{Computational Methods in Systems Biology: 10th International Conference, CMSB 2012, London, UK, October 3-5, 2012. Proceedings}. Berlin: Springer, 2012, s.~207-226. ISBN~978-3-642-33635-5. Dostupné z: https://dx.doi.org/10.1007/978-3-642-33636-2\_{}13.
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