Network design meets in silico evolutionary biology.
Cell fate is programmed through gene regulatory networks that perform several calculations to take the appropriate decision. In silico evolutionary optimization mimics the way Nature has designed such gene regulatory networks. In this review we discuss the basic principles of these evolutionary approaches and how they can be applied to engineer synthetic networks. We summarize the basic guidelines to implement an in silico evolutionary design method, the operators for mutation and selection that iteratively drive the network architecture towards a specified dynamical behavior. Interestingly, as it happens in natural evolution, we show the existence of patterns of punctuated evolution. In addition, we highlight several examples of models that have been designed using automated procedures, together with different objective functions to select for the proper behavior. Finally, we briefly discuss the modular designability of gene regulatory networks and its potential application in biotechnology.
Rodrigo
Guillermo
G
Instituto de Biología Molecular y Celular de Plantas, Consejo Superior de Investigaciones Científicas-Universidad Politécnica de Valencia, 46022 València, Spain. guirodta@ibmcp.upv.es
Carrera
Javier
J
Elena
Santiago F
SF
D032701:Biomimetics / Q000379:methods*; D002477:Cells / Q000378:metabolism; D019295:Computational Biology / Q000379:methods*; D019143:Evolution, Molecular; D053263:Gene Regulatory Networks