Evolutionary Dynamics in Gene Networks and Inference Algorithms

Computation

Daniel Aguilar-Hidalgo²  Mar໚ C. Lemos³  Antonio Córdoba³  Marnix Medema¹ 

[1] id="af1-computation-03-00099">1Max Planck Institute for the Physics of Complex Systems, Nöthnitzer Straße 38, 01187 Dresden, Germa;Max Planck Institute for the Physics of Complex Systems, Nöthnitzer Straße 38, 01187 Dresden, Germany;Departamento de Física de la Materia Condensada, Universidad de Sevilla, 41012 Sevilla, Spain; E-Mails:

关键词: evolutionary dynamics;    evolutionary algorithms;    gene regulatory networks;   

DOI  :  10.3390/computation3010099

来源: mdpi

【 摘 要 】

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.

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland.