Simulating Metabolic Processes Using an Architecture Based on Networks of Bio-inspired Processors.

Gomez Canaval, Sandra Maria; Sánchez Couso, José Ramón y Arroyo Montoro, Fernando (2013). Simulating Metabolic Processes Using an Architecture Based on Networks of Bio-inspired Processors.. "Lecture Notes in Computer Science: Unconventional Computation and Natural Computation: 12th International Conference, UCNC 2013, Milan, Italy, July 1-5, 2013. Proceedings", v. 7956 ; pp. 255-256. ISSN 978-3-642-39073-9. https://doi.org/10.1007/978-3-642-39074-6.

Descripción

Título: Simulating Metabolic Processes Using an Architecture Based on Networks of Bio-inspired Processors.
Autor/es:
  • Gomez Canaval, Sandra Maria
  • Sánchez Couso, José Ramón
  • Arroyo Montoro, Fernando
Tipo de Documento: Artículo
Título de Revista/Publicación: Lecture Notes in Computer Science: Unconventional Computation and Natural Computation: 12th International Conference, UCNC 2013, Milan, Italy, July 1-5, 2013. Proceedings
Fecha: 2013
Volumen: 7956
Materias:
Escuela: E.U. de Informática (UPM) [antigua denominación]
Departamento: Lenguajes, Proyectos y Sistemas Informáticos
Licencias Creative Commons: Reconocimiento - Sin obra derivada - No comercial

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Resumen

In this work, we propose the Networks of Evolutionary Processors (NEP) [2] as a computational model to solve problems related with biological phenomena. In our first approximation, we simulate biological processes related with cellular signaling and their implications in the metabolism, by using an architecture based on NEP (NEP architecture) and their specializations: Networks of Polarized Evolutionary Processors (NPEP) [1] and NEP Transducers (NEPT) [3]. In particular, we use this architecture to simulate the interplay between cellular processes related with the metabolism as the Krebs cycle and the malate-aspartate shuttle pathway (MAS) both being altered by signaling by calcium.

Más información

ID de Registro: 29093
Identificador DC: http://oa.upm.es/29093/
Identificador OAI: oai:oa.upm.es:29093
Identificador DOI: 10.1007/978-3-642-39074-6
URL Oficial: http://link.springer.com/chapter/10.1007%2F978-3-642-39074-6_28
Depositado por: Memoria Investigacion
Depositado el: 13 Jun 2014 11:56
Ultima Modificación: 22 Sep 2014 11:44
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