KOLČÁK, Juraj, David ŠAFRÁNEK, Stefan HAAR and Loïc PAULEVÉ. Parameter space abstraction and unfolding semantics of discrete regulatory networks. Theoretical Computer Science. Elsevier, 2019, vol. 765, April, p. 120-144. ISSN 0304-3975. Available from: https://dx.doi.org/10.1016/j.tcs.2018.03.009.
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Basic information
Original name Parameter space abstraction and unfolding semantics of discrete regulatory networks
Authors KOLČÁK, Juraj (703 Slovakia, belonging to the institution), David ŠAFRÁNEK (203 Czech Republic, guarantor, belonging to the institution), Stefan HAAR (276 Germany) and Loïc PAULEVÉ (250 France).
Edition Theoretical Computer Science, Elsevier, 2019, 0304-3975.
Other information
Original language English
Type of outcome Article in a journal
Field of Study 10201 Computer sciences, information science, bioinformatics
Country of publisher Czech Republic
Confidentiality degree is not subject to a state or trade secret
WWW URL
Impact factor Impact factor: 0.747
RIV identification code RIV/00216224:14330/19:00108116
Organization unit Faculty of Informatics
Doi http://dx.doi.org/10.1016/j.tcs.2018.03.009
UT WoS 000473372600007
Keywords in English Boolean networks; Thomas networks; Parametrised discrete dynamics; Asynchronous systems; Concurrency; Systems biology
Tags International impact, Reviewed
Changed by Changed by: doc. RNDr. David Šafránek, Ph.D., učo 3159. Changed: 27/4/2020 15:32.
Abstract
The modelling of discrete regulatory networks combines a graph specifying the pairwise influences between the variables of the system, and a parametrisation from which can be derived a discrete transition system. Given the influence graph only, the exploration of admissible parametrisations and the behaviours they enable is computationally demanding due to the combinatorial explosions of both parametrisation and reachable state space. This article introduces an abstraction of the parametrisation space and its refinement to account for the existence of given transitions, and for constraints on the sign and observability of influences. The abstraction uses a convex sublattice containing the concrete parametrisation space specified by its infimum and supremum parametrisations. It is shown that the computed abstractions are optimal, i.e., no smaller convex sublattice exists. Although the abstraction may introduce over-approximation, it has been proven to be conservative with respect to reachability of states. Then, an unfolding semantics for Parametric Regulatory Networks is defined, taking advantage of concurrency between transitions to provide a compact representation of reachable transitions. A prototype implementation is provided: it has been applied to several examples of Boolean and multi-valued networks, showing its tractability for networks with numerous components.
Links
GA15-11089S, research and development projectName: Získávání parametrů biologických modelů pomocí techniky ověřování modelů
Investor: Czech Science Foundation
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