Title :
Evolving genetic regulatory networks for systems biology
Author_Institution :
Univ. of Kent, Canterbury
Abstract :
Recently there has been significant interest in evolving genetic regulatory networks with a user-determined behaviour. It is unclear whether or not artificial evolution of biochemical networks can be of direct benefit for or biological relevance to systems biology. This article highlights some pitfalls when concluding from artificially evolved genetic regulatory networks to real networks. This article also gives a (brief) review of some previous attempts to evolve genetic regulatory networks with oscillatory behaviour; it also describes a new system to evolve networks and describes the networks that have been evolved. These networks seem to be very diverse sharing no apparent common motifs either with one another or with their real-life counterparts.
Keywords :
biology; genetic algorithms; artificial evolution; artificially evolved genetic regulatory networks; biochemical networks; oscillatory behaviour; systems biology; user-determined behaviour; Biological system modeling; Biology computing; Computational intelligence; Evolution (biology); Genetics; Laboratories; Process design; Software tools; Systems biology; Uncertainty;
Conference_Titel :
Evolutionary Computation, 2007. CEC 2007. IEEE Congress on
Conference_Location :
Singapore
Print_ISBN :
978-1-4244-1339-3
Electronic_ISBN :
978-1-4244-1340-9
DOI :
10.1109/CEC.2007.4424562