Evolving noisy oscillatory dynamics in genetic regulatory networks
Leier, Andre, Kuo, P. Dwight, Banzhaf, Wolfgang, & Burrage, Kevin (2006) Evolving noisy oscillatory dynamics in genetic regulatory networks. In Collet, Pierre, Tomassini, Marco, Ebner, Marc, Gustafson, Steven, & Ekart, Aniko (Eds.) Lecture Notes in Computer Science : Genetic Programming, Springer, Budapest, pp. 290-299.
We introduce a genetic programming (GP) approach for evolving genetic networks that demonstrate desired dynamics when simulated as a discrete stochastic process. Our representation of genetic networks is based on a biochemical reaction model including key elements such as transcription, translation and post-translational modifications. The stochastic, reaction-based GP system is similar but not identical with algorithmic chemistries. We evolved genetic networks with noisy oscillatory dynamics. The results show the practicality of evolving particular dynamics in gene regulatory networks when modelled with intrinsic noise.
Citation countsare sourced monthly fromand citation databases.
These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science generally from 1980 onwards.
Citations counts from theindexing service can be viewed at the linked Google Scholar™ search.
|Item Type:||Conference Paper|
|Keywords:||Computer Science, Theory & Methods, Stochastic Simulation, Escherichia-coli, Expression, Evolution, Cells|
|Divisions:||Past > QUT Faculties & Divisions > Faculty of Science and Technology|
Past > Schools > Mathematical Sciences
|Deposited On:||19 Sep 2011 08:23|
|Last Modified:||01 Mar 2012 00:36|
Repository Staff Only: item control page