Model checking
Symbolic Model Checking of Biochemical Networks
CMSB '03 Proceedings of the First International Workshop on Computational Methods in Systems Biology
Multi.Objective Hypergraph Partitioning Algorithms for Cut and Maximum Subdomain Degree Minimization
Proceedings of the 2003 IEEE/ACM international conference on Computer-aided design
Modeling and querying biomolecular interaction networks
Theoretical Computer Science - Special issue: Computational systems biology
Assumption-based distribution of CTL model checking
International Journal on Software Tools for Technology Transfer (STTT) - Special section on parallel and distributed model checking
The biochemical abstract machine BIOCHAM
CMSB'04 Proceedings of the 20 international conference on Computational Methods in Systems Biology
CMBSlib: a library for comparing formalisms and models of biological systems
CMSB'04 Proceedings of the 20 international conference on Computational Methods in Systems Biology
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In this paper, we use some observations on the nature of biochemical reactions to derive interesting properties of qualitative biochemical Kripke structures. We show that these characteristics make Kripke structures of biochemical pathways suitable for assumption based distributed model checking. The number of chemical species participating in a biochemical reaction is usually bounded by a small constant. This observation is used to show that the Hamming distance between adjacent states of a qualitative biochemical Kripke structures is bounded. We call such structures as Bounded Hamming Distance Kripke structures (BHDKS). We, then, argue the suitability of assumption based distributed model checking for BHDKS by constructively deriving worst case upper bounds on the size of the fragments of the state space that need to be stored at each distributed node. We also show that the distributed state space can be mapped naturally to a hypercube based distributed architecture. We support our results by experimental evaluation over benchmarks and biochemical pathways from public databases.