Abstract
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.
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References
Alarcón, P.P., Arroyo, F., Mitrana, V.: Networks of Polarized Evolutionary Processors as Problem Solvers. In: Advances in Knowledge-Based and Intelligent Information and Engineering Systems, pp. 807–815 (2012)
Castellanos, J., Martín-Vide, C., Mitrana, V., Sempere, J.M.: Networks of evolutionary processors. Acta Informática 39, 517–529 (2003)
Gómez Canaval, S., Mitrana, V., Sánchez Couso, J.R.: Transducers Based on Networks of Evolutionary Processors (submitted)
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Gómez Canaval, S., Sánchez, J.R., Arroyo, F. (2013). Simulating Metabolic Processes Using an Architecture Based on Networks of Bio-inspired Processors. In: Mauri, G., Dennunzio, A., Manzoni, L., Porreca, A.E. (eds) Unconventional Computation and Natural Computation. UCNC 2013. Lecture Notes in Computer Science, vol 7956. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39074-6_28
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DOI: https://doi.org/10.1007/978-3-642-39074-6_28
Publisher Name: Springer, Berlin, Heidelberg
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