Titre :

The Attributed Pi Calculus

Auteur(s) :

John, Mathias [Auteur]
University of Rostock
Lhoussaine, Cedric [Auteur]
Laboratoire d'Informatique Fondamentale de Lille [LIFL]
Niehren, Joachim [Auteur correspondant]
Programming Languages for Biological Modeling and Simulation [BioComputing]
Modeling Tree Structures, Machine Learning, and Information Extraction [MOSTRARE]
Uhrmacher, Adelinde [Auteur]
University of Rostock

Éditeur(s) ou directeur(s) scientifique(s) :

Springer

Titre de la manifestation scientifique :

Computational Methods in Systems Biology, 6th International Conference CMSB

Ville :

Rostock

Pays :

Allemagne

Date de début de la manifestation scientifique :

2008-10-12

Éditeur :

Lecture Notes in Bioinformatics

Date de publication :

2008

Discipline(s) HAL :

Informatique [cs]/Langage de programmation [cs.PL]
Informatique [cs]/Bio-informatique [q-bio.QM]
Sciences du Vivant [q-bio]/Bio-Informatique, Biologie Systémique [q-bio.QM]

Résumé en anglais : [en]

The attributed pi calculus (pi(L)) forms an extension of the pi calculus with attributed processes and attribute dependent synchronization. To ensure flexibility, the calculus is parametrized with the language L which ...
Lire la suite >The attributed pi calculus (pi(L)) forms an extension of the pi calculus with attributed processes and attribute dependent synchronization. To ensure flexibility, the calculus is parametrized with the language L which defines possible values of attributes. pi(L) can express polyadic synchronization as in pi@ and thus diverse compartment organizations. A non-deterministic and a stochastic semantics, where rates may depend on attribute values, is introduced. The stochastic semantics is based on continuous time Markov chains. A simulation algorithm is developed which is firmly rooted in this stochastic semantics. Two examples, the movement processes in the phototaxis of Euglena and the cooperative binding in the gene regulation of the lambda Phage, underline the applicability of pi(L) to systems biology.Lire moins >

Langue :

Anglais

Comité de lecture :

Oui

Audience :

Internationale

Vulgarisation :

Non

Projet ANR :

A Uniform Approach for Stochastic Modeling with Spatial Aspects in Systems Biology

Collections :

• Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189

Source :

Harvested from HAL