Internal coarse-graining of molecular systems

Abstract : Modelers of molecular signaling networks must cope with the combinatorial explosion of protein states generated by posttranslational modifications and complex formation. Rule-based models provide a powerful alternative to approaches that require explicit enumeration of all possible molecular species of a system. Such models consist of formal rules stipulating the (partial) contexts wherein specific protein–protein interactions occur. These contexts specify molecular patterns that are usually less detailed than molecular species. Yet, the execution of rule-based dynamics requires stochastic simulation, which can be very costly. It thus appears desirable to convert a rule-based model into a reduced system of differential equations by exploiting the granularity at which rules specify interactions. We present a formal (and automated) method for constructing a coarse-grained and self-consistent dynamical system aimed at molecular patterns that are distinguishable by the dynamics of the original system as posited by the rules. The method is formally sound and never requires the execution of the rule-based model. The coarse-grained variables do not depend on the values of the rate constants appearing in the rules, and typically form a system of greatly reduced dimension that can be amenable to numerical integration and further model reduction techniques.
Type de document :
Article dans une revue
Proceedings of the National Academy of Sciences of the United States of America , National Academy of Sciences, 2009, 106 (16), 〈10.1073/pnas.0809908106〉
Liste complète des métadonnées

https://hal.inria.fr/inria-00528330
Contributeur : Jérôme Feret <>
Soumis le : jeudi 21 octobre 2010 - 15:40:38
Dernière modification le : jeudi 11 janvier 2018 - 06:17:47

Lien texte intégral

Identifiants

Collections

PPS | USPC

Citation

Jérôme Feret, Vincent Danos, Jean Krivine, Russ Harmer, Walter Fontana. Internal coarse-graining of molecular systems. Proceedings of the National Academy of Sciences of the United States of America , National Academy of Sciences, 2009, 106 (16), 〈10.1073/pnas.0809908106〉. 〈inria-00528330〉

Partager

Métriques

Consultations de la notice

140