Evolutionary Dynamics in Gene Networks and Inference Algorithms
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 regulat...
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doaj-599297a4c51e453f93ad01c9059971522020-11-24T22:01:23ZengMDPI AGComputation2079-31972015-03-01319911310.3390/computation3010099computation3010099Evolutionary Dynamics in Gene Networks and Inference AlgorithmsDaniel Aguilar-Hidalgo0María C. Lemos1Antonio Córdoba2Max Planck Institute for the Physics of Complex Systems, Nöthnitzer Straße 38, 01187 Dresden, GermanyDepartamento de Física de la Materia Condensada, Universidad de Sevilla, 41012 Sevilla, SpainDepartamento de Física de la Materia Condensada, Universidad de Sevilla, 41012 Sevilla, SpainDynamical 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.http://www.mdpi.com/2079-3197/3/1/99evolutionary dynamicsevolutionary algorithmsgene regulatory networks |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Daniel Aguilar-Hidalgo María C. Lemos Antonio Córdoba |
spellingShingle |
Daniel Aguilar-Hidalgo María C. Lemos Antonio Córdoba Evolutionary Dynamics in Gene Networks and Inference Algorithms Computation evolutionary dynamics evolutionary algorithms gene regulatory networks |
author_facet |
Daniel Aguilar-Hidalgo María C. Lemos Antonio Córdoba |
author_sort |
Daniel Aguilar-Hidalgo |
title |
Evolutionary Dynamics in Gene Networks and Inference Algorithms |
title_short |
Evolutionary Dynamics in Gene Networks and Inference Algorithms |
title_full |
Evolutionary Dynamics in Gene Networks and Inference Algorithms |
title_fullStr |
Evolutionary Dynamics in Gene Networks and Inference Algorithms |
title_full_unstemmed |
Evolutionary Dynamics in Gene Networks and Inference Algorithms |
title_sort |
evolutionary dynamics in gene networks and inference algorithms |
publisher |
MDPI AG |
series |
Computation |
issn |
2079-3197 |
publishDate |
2015-03-01 |
description |
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. |
topic |
evolutionary dynamics evolutionary algorithms gene regulatory networks |
url |
http://www.mdpi.com/2079-3197/3/1/99 |
work_keys_str_mv |
AT danielaguilarhidalgo evolutionarydynamicsingenenetworksandinferencealgorithms AT mariaclemos evolutionarydynamicsingenenetworksandinferencealgorithms AT antoniocordoba evolutionarydynamicsingenenetworksandinferencealgorithms |
_version_ |
1725839907639787520 |