Memorias de investigación
Artículos en revistas:
Simulating FAS-induced apoptosis by using P systems
Año:2007

Áreas de investigación
  • Inteligencia artificial

Datos
Descripción
In contrast to differential equations, P systems are an unconventional model of computation which takes into consideration the discrete character of the quantity of components and the inherent randomness that exists in biological phenomena. The key feature of P systems is their compartmentatised structure which represents the heterogeneity of the structural organisation of the cells, and where one can take into account the role played by membranes in the functioning of the system, for example signalling at the cell surface, selective uptake of substances from the media, diffusion across different compartments, etc. We show here that P systems can be a reliable tool for Systems Biology and could even outperform in some cases the current simulation techniques based on differential equations. We will also use a strategy based on the well known Gillespie algorithm but running on more than one compartment called Multi-compartmental Gillespie Algorithm.
Internacional
Si
JCR del ISI
Si
Título de la revista
PROG NAT SCI
ISSN
1002-0071
Factor de impacto JCR
0,508
Información de impacto
Volumen
17
DOI
Número de revista
4
Desde la página
424
Hasta la página
431
Mes
ABRIL
Ranking

Esta actividad pertenece a memorias de investigación

Participantes
  • Participante: Andrei Pabreveun Department of Computer Science IfM, Louisiana Tech University, Ruston, USA
  • Participante: Oscar H. Ibarra Department of Computer Science, University of California -Santa Barbara, Santa Barbara, USA
  • Autor: Paul Andrei Paun . UPM
  • Participante: Smitha Cheruku Department of Computer Science IfM, Louisiana Tech University, Ruston, USA
  • Participante: Francisco J Romero-Campero Department of Computer Science and Artificial Intelligence, University of Seville, Sevilla, Spain

Grupos de investigación, Departamentos, Centros e Institutos de I+D+i relacionados
  • Creador: Grupo de Investigación: Grupo de Inteligencia Artificial (LIA)
  • Departamento: Inteligencia Artificial