Evolving genetic regulatory networks performing as stochastic switches
Leier, Andre & Burrage, Kevin (2006) Evolving genetic regulatory networks performing as stochastic switches. In Hoche, Susanne, Memmott, Jane, Monk, Nick, & Nurnberger, Andreas (Eds.) Contributions of the Symposium on Network Analysis in Natural Sciences and Engineering, part of AISB'06: Adaption in Artificial and Biological Systems, Bristol, England, pp. 63-70.
Recent studies have shown that small genetic regulatory networks (GRNs) can be evolved in silico displaying certain dynamics in the underlying mathematical model. It is expected that evolutionary approaches can help to gain a better understanding of biological design principles and assist in the engineering of genetic networks. To take the stochastic nature of GRNs into account, our evolutionary approach models GRNs as biochemical reaction networks based on simple enzyme kinetics and simulates them by using Gillespie’s stochastic simulation algorithm (SSA). We have already demonstrated the relevance of considering intrinsic stochasticity by evolving GRNs that show oscillatory dynamics in the SSA but not in the ODE regime. Here, we present and discuss first results in the evolution of GRNs performing as stochastic switches.
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|Item Type:||Conference Paper|
|Additional Information:||Paper is on page 150 of proceedings link above|
|Divisions:||Past > QUT Faculties & Divisions > Faculty of Science and Technology
Past > Schools > Mathematical Sciences
|Copyright Owner:||Copyright 2006 please consult authors|
|Deposited On:||28 Sep 2011 02:03|
|Last Modified:||28 Sep 2011 02:10|
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