Handbook of graph grammars and computing by graph transformation
Graph transformation for specification and programming
Science of Computer Programming
An Algorithm for Subgraph Isomorphism
Journal of the ACM (JACM)
Information Processing Letters
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Graphs for Core Molecular Biology
CMSB '03 Proceedings of the First International Workshop on Computational Methods in Systems Biology
Pathway Logic Modeling of Protein Functional Domains in Signal Transduction
CSB '03 Proceedings of the IEEE Computer Society Conference on Bioinformatics
Theoretical Computer Science - Special issue: Computational systems biology
Graphical rule-based representation of signal-transduction networks
Proceedings of the 2005 ACM symposium on Applied computing
Rule-based modeling of biochemical networks: Research Articles
Complexity - Understanding Complex Systems: Part II
Graph transformation in molecular biology
Formal Methods in Software and Systems Modeling
Developing SBML beyond level 2: proposals for development
CMSB'04 Proceedings of the 20 international conference on Computational Methods in Systems Biology
A Rewriting Calculus for Multigraphs with Ports
Electronic Notes in Theoretical Computer Science (ENTCS)
CMSB '08 Proceedings of the 6th International Conference on Computational Methods in Systems Biology
The κ-Lattice: Decidability Boundaries for Qualitative Analysis in Biological Languages
CMSB '09 Proceedings of the 7th International Conference on Computational Methods in Systems Biology
Abstract interpretation of cellular signalling networks
VMCAI'08 Proceedings of the 9th international conference on Verification, model checking, and abstract interpretation
Compartmental rule-based modeling of biochemical systems
Winter Simulation Conference
Containment in Rule-Based Models
Electronic Notes in Theoretical Computer Science (ENTCS)
Pattern graphs and rule-based models: the semantics of kappa
FOSSACS'13 Proceedings of the 16th international conference on Foundations of Software Science and Computation Structures
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We introduce a graph-theoretic formalism suitable for modeling biochemical networks marked by combinatorial complexity, such as signal-transduction systems, in which protein-protein interactions play a prominent role. This development extends earlier work by allowing for explicit representation of the connectivity of a protein complex. Within the formalism, typed attributed graphs are used to represent proteins and their functional components, complexes, conformations, and states of post-translational covalent modification. Graph transformation rules are used to represent protein-protein interactions and their effects. Each rule defines a generalized reaction, i.e., a class of potential reactions that are logically consistent with knowledge or assumptions about the represented biomolecular interaction. A model is specified by defining 1) molecular-entity graphs, which delimit the molecular entities and material components of a system and their possible states, 2) graph transformation rules, and 3) a seed set of graphs representing chemical species, such as the initial species present before introduction of a signal. A reaction network is generated iteratively through application of the graph transformation rules. The rules are first applied to the seed graphs and then to any and all new graphs that subsequently arise as a result of graph transformation. This procedure continues until no new graphs are generated or a specified termination condition is satisfied. The formalism supports the generation of a list of reactions in a system, which can be used to derive different types of physicochemical models, which can be simulated and analyzed in different ways. The processes of generating and simulating the network may be combined so that species are generated only as needed.