Rule-Based Modelling and Model Perturbation

Vincent Danos 1 Jérôme Feret 2 Walter Fontana 3 Russ Harmer 4 Jean Krivine 3, 5
2 ABSTRACTION - Abstract Interpretation and Static Analysis
DI-ENS - Département d'informatique de l'École normale supérieure, ENS Paris - École normale supérieure - Paris, Inria Paris-Rocquencourt, CNRS - Centre National de la Recherche Scientifique : UMR 8548
Abstract : Rule-based modelling has already proved to be successful for taming the combinatorial complexity, typical of cellular signalling networks, caused by the combination of physical protein-protein interactions and modifications that generate astronomical numbers of distinct molecular species. However, traditional rule-based approaches, based on an unstructured space of agents and rules, remain susceptible to other combinatorial explosions caused by mutated and/or splice variant agents, that share most but not all of their rules with their wild-type counterparts; and by drugs, which must be clearly distinguished from physiological ligands. In this paper, we define a syntactic extension of Kappa, an established rule-based modelling platform, that enables the expression of a structured space of agents and rules that allows us to express mutated agents, splice variants, families of related proteins and ligand/drug interventions uniformly. This also enables a mode of model construction where, starting from the current consensus model, we attempt to reproduce in numero the mutational—and more generally the ligand/drug perturbational—analyses that were used in the process of inferring those pathways in the first place.
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Transactions on Computational Systems Biology, Springer, 2009, Transactions on Computational Systems Biology XI, 5750, pp.116-137. 〈10.1007/978-3-642-04186-0_6〉
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Contributeur : Jérôme Feret <>
Soumis le : jeudi 21 octobre 2010 - 16:23:28
Dernière modification le : jeudi 11 janvier 2018 - 06:22:10

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Vincent Danos, Jérôme Feret, Walter Fontana, Russ Harmer, Jean Krivine. Rule-Based Modelling and Model Perturbation. Transactions on Computational Systems Biology, Springer, 2009, Transactions on Computational Systems Biology XI, 5750, pp.116-137. 〈10.1007/978-3-642-04186-0_6〉. 〈inria-00528364〉

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