Discrete Nondeterministic Modeling of the Fas Pathway

Jack, John; Rodríguez-Patón Aradas, Alfonso; Ibarra, Oscar H. y Paun, Andrei Paul (2008). Discrete Nondeterministic Modeling of the Fas Pathway. "International Journal of Foundations of Computer Science", v. 19 (n. 5); pp. 1147-1162. ISSN 0129-0541. https://doi.org/10.1142/S0129054108006194.

Descripción

Título: Discrete Nondeterministic Modeling of the Fas Pathway
Autor/es:
  • Jack, John
  • Rodríguez-Patón Aradas, Alfonso
  • Ibarra, Oscar H.
  • Paun, Andrei Paul
Tipo de Documento: Artículo
Título de Revista/Publicación: International Journal of Foundations of Computer Science
Fecha: Octubre 2008
Volumen: 19
Materias:
Escuela: Facultad de Informática (UPM) [antigua denominación]
Departamento: Inteligencia Artificial
Licencias Creative Commons: Reconocimiento - Sin obra derivada - No comercial

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Resumen

Abstract: Computer modeling of molecular signaling cascades can provide useful insight into the underlying complexities of biological systems. We present a refined approach for the discrete modeling of protein interactions within the environment of a single cell. The technique we offer utilizes the Membrane Systems paradigm which, due to its hierarchical structure, lends itself readily to mimic the behavior of cells. Since our approach is nondeterministic and discrete, it provides an interesting contrast to the standard deterministic ordinary differential equations techniques. We argue that our approach may outperform ordinary differential equations when modeling systems with relatively low numbers of molecules – a frequent occurrence in cellular signaling cascades. Refinements over our previous modeling efforts include the addition of nondeterminism for handling reaction competition over limited reactants, increased efficiency in the storing and sorting of reaction waiting times, and modifications of the model reactions. Results of our discrete simulation of the type I and type II Fas-mediated apoptotic signaling cascade are illustrated and compared with two approaches: one based on ordinary differential equations and another based on the well-known Gillespie algorithm.

Más información

ID de Registro: 2261
Identificador DC: http://oa.upm.es/2261/
Identificador OAI: oai:oa.upm.es:2261
Identificador DOI: 10.1142/S0129054108006194
Depositado por: Memoria Investigacion
Depositado el: 12 Feb 2010 12:31
Ultima Modificación: 20 Abr 2016 12:01
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