Symbolic modeling of signal transduction in pathway logic
Proceedings of the 38th conference on Winter simulation
Multiple representations of biological processes
Transactions on Computational Systems Biology VI
A fast linear-arithmetic solver for DPLL(T)
CAV'06 Proceedings of the 18th international conference on Computer Aided Verification
An Exact Brownian Dynamics Method for Cell Simulation
CMSB '08 Proceedings of the 6th International Conference on Computational Methods in Systems Biology
SFM'08 Proceedings of the Formal methods for the design of computer, communication, and software systems 8th international conference on Formal methods for computational systems biology
Identifying Necessary Reactions in Metabolic Pathways by Minimal Model Generation
Proceedings of the 2010 conference on ECAI 2010: 19th European Conference on Artificial Intelligence
TLCA'11 Proceedings of the 10th international conference on Typed lambda calculi and applications
Analyzing pathways using ASP-based approaches
ANB'10 Proceedings of the 4th international conference on Algebraic and Numeric Biology
| Hi-index | 0.00 |
A network of reactions is a commonly used paradigm for representing knowledge about a biological process. How does one understand such generic networks and answer queries using them? In this paper, we present a novel approach based on translation of generic reaction networks to Boolean weighted MaxSAT. The Boolean weighted MaxSAT instance is generated by encoding the equilibrium configurations of a reaction network by weighted boolean clauses. The important feature of this translation is that it uses reactions, rather than the species, as the boolean variables. Existing weighted MaxSAT solvers are used to solve the generated instances and find equilibrium configurations. This method of analyzing reaction networks is generic, flexible and scales to large models of reaction networks. We present a few case studies to validate our claims.