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Evolutionary Dynamics in Gene Networks and Inference Algorithms

 

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Autor: Aguilar Hidalgo, Daniel
Lemos Fernández, María del Carmen
Córdoba Zurita, Antonio
Departamento: Universidad de Sevilla. Departamento de Física de la Materia Condensada
Fecha: 2015
Publicado en: Computation, 3 (1), 99-113.
Tipo de documento: Artículo
Resumen: Dynamical interactions among sets of genes (and their products) regulate developmental processes and some dynamical diseases, like cancer. Gene regulatory networks (GRNs) are directed networks that define interactions (links) among different genes/proteins involved in such processes. Genetic regulation can be modified during the time course of the process, which may imply changes in the nodes activity that leads the system from a specific state to a different one at a later time (dynamics). How the GRN modifies its topology, to properly drive a developmental process, and how this regulation was acquired across evolution are questions that the evolutionary dynamics of gene networks tackles. In the present work we review important methodology in the field and highlight the combination of these methods with evolutionary algorithms. In recent years, this combination has become a powerful tool to fit models with the increasingly available experimental data.
Cita: Aguilar Hidalgo, D., Lemos Fernández, M.d.C. y Córdoba Zurita, A. (2015). Evolutionary Dynamics in Gene Networks and Inference Algorithms. Computation, 3 (1), 99-113.
Tamaño: 837.2Kb
Formato: PDF

URI: http://hdl.handle.net/11441/48871

DOI: http://dx.doi.org/10.3390/computation3010099

Salvo que se indique lo contrario, los contenidos de esta obra estan sujetos a la licencia de Creative Commons: 
Attribution-NonCommercial-NoDerivatives 4.0 InternacionalAttribution-NonCommercial-NoDerivatives 4.0 Internacional

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