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

Gonzalo A. Ruz; Eric Goles; Sylvain Sené

doi:10.1109/CEC.2018.8477964

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

Gonzalo A. Ruz, Eric Goles, Sylvain Sené

Facultad de Ingeniería y Ciencias

Producción científica: Capítulo del libro/informe/acta de congreso › Contribución a la conferencia › revisión exhaustiva

6 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 original	Inglés
Título de la publicación alojada	2018 IEEE Congress on Evolutionary Computation, CEC 2018 - Proceedings
Editorial	Institute of Electrical and Electronics Engineers Inc.
ISBN (versión digital)	9781509060177
DOI	https://doi.org/10.1109/CEC.2018.8477964
Estado	Publicada - 28 sep. 2018
Evento	2018 IEEE Congress on Evolutionary Computation, CEC 2018 - Rio de Janeiro, Brasil Duración: 8 jul. 2018 → 13 jul. 2018

Serie de la publicación

Nombre	2018 IEEE Congress on Evolutionary Computation, CEC 2018 - Proceedings

Conferencia

Conferencia	2018 IEEE Congress on Evolutionary Computation, CEC 2018
País/Territorio	Brasil
Ciudad	Rio de Janeiro
Período	8/07/18 → 13/07/18

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10.1109/CEC.2018.8477964

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Ruz, G. A., Goles, E., & Sené, S. (2018). Reconstruction of Boolean Regulatory Models of Flower Development Exploiting an Evolution Strategy. En 2018 IEEE Congress on Evolutionary Computation, CEC 2018 - Proceedings Artículo 8477964 (2018 IEEE Congress on Evolutionary Computation, CEC 2018 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CEC.2018.8477964

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title = "Reconstruction of Boolean Regulatory Models of Flower Development Exploiting an Evolution Strategy",

abstract = "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.",

author = "Ruz, {Gonzalo A.} and Eric Goles and Sylvain Sen{\'e}",

note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 2018 IEEE Congress on Evolutionary Computation, CEC 2018 ; Conference date: 08-07-2018 Through 13-07-2018",

year = "2018",

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day = "28",

doi = "10.1109/CEC.2018.8477964",

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Ruz, GA, Goles, E & Sené, S 2018, Reconstruction of Boolean Regulatory Models of Flower Development Exploiting an Evolution Strategy. En 2018 IEEE Congress on Evolutionary Computation, CEC 2018 - Proceedings., 8477964, 2018 IEEE Congress on Evolutionary Computation, CEC 2018 - Proceedings, Institute of Electrical and Electronics Engineers Inc., 2018 IEEE Congress on Evolutionary Computation, CEC 2018, Rio de Janeiro, Brasil, 8/07/18. https://doi.org/10.1109/CEC.2018.8477964

Reconstruction of Boolean Regulatory Models of Flower Development Exploiting an Evolution Strategy. / Ruz, Gonzalo A.; Goles, Eric; Sené, Sylvain.
2018 IEEE Congress on Evolutionary Computation, CEC 2018 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2018. 8477964 (2018 IEEE Congress on Evolutionary Computation, CEC 2018 - Proceedings).

Producción científica: Capítulo del libro/informe/acta de congreso › Contribución a la conferencia › revisión exhaustiva

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AB - 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.

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Ruz GA, Goles E, Sené S. Reconstruction of Boolean Regulatory Models of Flower Development Exploiting an Evolution Strategy. En 2018 IEEE Congress on Evolutionary Computation, CEC 2018 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2018. 8477964. (2018 IEEE Congress on Evolutionary Computation, CEC 2018 - Proceedings). doi: 10.1109/CEC.2018.8477964

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

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