Reconstruction of Boolean Regulatory Models of Flower Development Exploiting an Evolution Strategy

Gonzalo A. Ruz, Eric Goles, Sylvain Sené

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

5 Citas (Scopus)

Resumen

One of the first popular applications of Boolean networks for gene regulatory networks corresponds to the Mendoza Alvarez-Buylla network of flower development. In this paper, we consider this model and a reduced version to reconstruct synthetic threshold Boolean networks that have the same asymptotic behavior as these base models. For this, we employ an evolution strategy to search for neighboring solutions. We were able to find solutions with fewer edges as well as networks with more balanced distributions of basins of attractions. Overall, our results show the effectiveness of using evolutionary computation in this application to explore alternative solutions with desired properties.

Idioma originalInglés
Título de la publicación alojada2018 IEEE Congress on Evolutionary Computation, CEC 2018 - Proceedings
EditorialInstitute of Electrical and Electronics Engineers Inc.
ISBN (versión digital)9781509060177
DOI
EstadoPublicada - 28 sep. 2018
Evento2018 IEEE Congress on Evolutionary Computation, CEC 2018 - Rio de Janeiro, Brasil
Duración: 8 jul. 201813 jul. 2018

Serie de la publicación

Nombre2018 IEEE Congress on Evolutionary Computation, CEC 2018 - Proceedings

Conferencia

Conferencia2018 IEEE Congress on Evolutionary Computation, CEC 2018
País/TerritorioBrasil
CiudadRio de Janeiro
Período8/07/1813/07/18

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