Communicating Hierarchical State Machines
ICAL '99 Proceedings of the 26th International Colloquium on Automata, Languages and Programming
CellDesigner: a modeling tool for biochemical networks
Proceedings of the 38th conference on Winter simulation
Probabilistic model checking of complex biological pathways
Theoretical Computer Science
Compositional semantics and behavioral equivalences for P Systems
Theoretical Computer Science
Bio-PEPA: A framework for the modelling and analysis of biological systems
Theoretical Computer Science
Efficient, correct simulation of biological processes in the stochastic pi-calculus
CMSB'07 Proceedings of the 2007 international conference on Computational methods in systems biology
The calculus of looping sequences
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
Natural Computing: an international journal
Spatial Calculus of Looping Sequences
Theoretical Computer Science
Bisimulation congruences in the calculus of looping sequences
ICTAC'06 Proceedings of the Third international conference on Theoretical Aspects of Computing
Transactions on Computational Systems Biology VII
Theoretical Computer Science
Foundational aspects of multiscale modeling of biological systems with process algebras
Theoretical Computer Science
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Biochemical pathways are abstract descriptions of the interactions among the molecular species involved in a process. Different molecular species mentioned in a pathway often represent different states of the same biological entity (e.g. the unbound and bound states of a certain molecule). Hence, a pathway can be seen as a network of interactions between entities which may change state synchronously by means of reactions. We consider such biological entities as pathway components and define a semi-automatic algorithm to infer the components from their interactions described in the pathway. Since this problem is inherently ambiguous, interaction with a domain expert might be needed to resolve any ambiguity that should arise. We apply the algorithm to the identification of components in a model of the EGF signaling pathway from the literature, and discuss possible uses of the component categorization as regards (i) the extraction of subpathways by projecting over a subset of components, and (ii) the automatic translation into finite state automata or process algebra terms.