Abstract
Biological systems are highly complex and separating them into individual parts facilitates their study. The representation of bio-logical systems as Genetic Regulatory Networks (GRN) that form a map of the interactions between the molecules in an organism is a standard way of representing such biological complexity. GRN are composed of genes that are translated into transcription factors, which in turn regulate other genes. For simulation and inference purposes, many different mathematical and algorithmic models have been adopted to represent the GRN in the past few years. In this paper we present the first efforts to develop a simulator using the MAS for to model generics GRN. To accomplish it, we develop a Multiagent System (MAS) that is composed of agents that mimic the biochemical processes of gene regulation.
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We would like to thank CAPES (Coordination for the Improvement of Higher Education Personnel) for the financial support to Doctorate Scholarship.
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Agostinho, N.B., Wherhli, A.V., Adamatti, D.F. (2021). Development of a Multiagent Simulator to Genetic Regulatory Networks. In: Novais, P., Vercelli, G., Larriba-Pey, J.L., Herrera, F., Chamoso, P. (eds) Ambient Intelligence – Software and Applications . ISAmI 2020. Advances in Intelligent Systems and Computing, vol 1239. Springer, Cham. https://doi.org/10.1007/978-3-030-58356-9_31
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DOI: https://doi.org/10.1007/978-3-030-58356-9_31
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