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  • We propose an automated method for exploring kinetic parameters of stochastic biochemical systems. The main question addressed is how the validity of an a priori given hypothesis expressed as a temporal logic property depends on kinetic parameters. Our aim is to compute a landscape function that, for each parameter point from the inspected parameter space, returns the quantitative model checking result for the respective continuous time Markov chain. Since the parameter space is in principle dense, it is infeasible to compute the landscape function directly. Hence, we design an effective method that iteratively approximates the lower and upper bounds of the landscape function with respect to a given accuracy. To this end, we modify the standard uniformization technique and introduce an iterative parameter space decomposition. We also demonstrate our approach on two biologically motivated case studies.
  • We propose an automated method for exploring kinetic parameters of stochastic biochemical systems. The main question addressed is how the validity of an a priori given hypothesis expressed as a temporal logic property depends on kinetic parameters. Our aim is to compute a landscape function that, for each parameter point from the inspected parameter space, returns the quantitative model checking result for the respective continuous time Markov chain. Since the parameter space is in principle dense, it is infeasible to compute the landscape function directly. Hence, we design an effective method that iteratively approximates the lower and upper bounds of the landscape function with respect to a given accuracy. To this end, we modify the standard uniformization technique and introduce an iterative parameter space decomposition. We also demonstrate our approach on two biologically motivated case studies. (en)
Title
  • Exploring Parameter Space of Stochastic Biochemical Systems Using Quantitative Model Checking
  • Exploring Parameter Space of Stochastic Biochemical Systems Using Quantitative Model Checking (en)
skos:prefLabel
  • Exploring Parameter Space of Stochastic Biochemical Systems Using Quantitative Model Checking
  • Exploring Parameter Space of Stochastic Biochemical Systems Using Quantitative Model Checking (en)
skos:notation
  • RIV/00216224:14330/13:00066280!RIV14-MSM-14330___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(EE2.3.20.0256), P(EE2.3.30.0009), P(GAP202/11/0312), S
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
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  • 74315
http://linked.open...ai/riv/idVysledku
  • RIV/00216224:14330/13:00066280
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • continuous-time Markov chains; parameter exploration; model checking (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [1C344F1D61BC]
http://linked.open...v/mistoKonaniAkce
  • Saint Petersburg
http://linked.open...i/riv/mistoVydani
  • Berlin
http://linked.open...i/riv/nazevZdroje
  • 25th International Conference, CAV 2013, Saint Petersburg, Russia, July 13-19, 2013. Proceedings
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
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http://linked.open...vavai/riv/projekt
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Brim, Luboš
  • Češka, Milan
  • Šafránek, David
  • Dražan, Sven
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
issn
  • 0302-9743
number of pages
http://bibframe.org/vocab/doi
  • 10.1007/978-3-642-39799-8_7
http://purl.org/ne...btex#hasPublisher
  • Springer-Verlag. (Berlin; Heidelberg)
https://schema.org/isbn
  • 9783642397981
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  • 14330
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