Computing with Artificial Gene Regulatory Networks

Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)

Abstract

Gene regulatory networks (GRNs) are the fundamental mechanisms through which biological organisms control their growth, their dynamical behavior, their interaction with their environment, and which underlie much of the complexity in the biosphere. This chapter reviews current understanding of artificial gene regulatory network (AGRN), discussing what is known about their computational properties, detailing how they have been applied to computational problems, and speculating about how they may be used in the future. It discusses what is known about biological GRNs, and the implications this has for the design of AGRNs. The chapter presents the different motivations behind the development of AGRN models. It also discusses the modeling decisions that have to be made when developing AGRN models. AGRNs give the opportunity to explore analogous behaviors within a more general setting, which, in turn, might lead to a better understanding of the general properties of GRNs.
Original languageEnglish
Title of host publicationEvolutionary Computation in Gene Regulatory Network Research
EditorsHitoshi Iba, Nasimul Noman
PublisherWiley
ISBN (Electronic)9781119079453
ISBN (Print)9781118911518
DOIs
Publication statusPublished - 2016

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    Lones, M. A. (2016). Computing with Artificial Gene Regulatory Networks. In H. Iba, & N. Noman (Eds.), Evolutionary Computation in Gene Regulatory Network Research Wiley. https://doi.org/10.1002/9781119079453.ch15