Abstract
Today, it is natural that great efforts are directed towards the development of tools to improve our knowledge about molecular interactions. The representation of biological systems as Genetic Regulatory Networks (GRN) that form a map of the interactions between the molecules in an organism is a way of representing such biological complexity. In the past few years, for simulation and inference purposes, many different mathematical and algorithmic models have been adopted to represent the GRN. Among these methods, Multiagent Systems (MAS) are somewhat neglected. Thus, in this paper was performed a Systematic Literature Review (SLR) to clarify the use of MAS in the representation of GRN. The results show that there are very few studies in which the MAS are applied in the task of modeling the GRN. Therefore, given the interesting properties of MAS, it is expected that it can be further investigated in the task of GRN modelling.
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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). A Systematic Review to Multiagent Systems and Regulatory Networks. In: Dong, Y., Herrera-Viedma, E., Matsui, K., Omatsu, S., González Briones, A., Rodríguez González, S. (eds) Distributed Computing and Artificial Intelligence, 17th International Conference. DCAI 2020. Advances in Intelligent Systems and Computing, vol 1237. Springer, Cham. https://doi.org/10.1007/978-3-030-53036-5_25
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