Abstract
The design of genetic networks has been studied for implementing desired biological systems, and in particular, some researchers have proposed automatic design methods using optimization techniques. However, it is difficult to implement genetic networks designed by previous methods due to overly simplified model descriptions whose parameters are infeasible in the real world. Additionally, the methods do not ensure robustness against parameter perturbation. In this paper, we propose a two-stage design method and a fitness function evaluating robustness to create genetic networks which can be implemented experimentally. Further, we suggest the knowledge about robust network structures from results of optimization.
Original language | English |
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Title of host publication | 2015 IEEE Congress on Evolutionary Computation, CEC 2015 - Proceedings |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 1596-1603 |
Number of pages | 8 |
ISBN (Electronic) | 9781479974924 |
DOIs | |
Publication status | Published - Sept 10 2015 |
Event | IEEE Congress on Evolutionary Computation, CEC 2015 - Sendai, Japan Duration: May 25 2015 → May 28 2015 |
Other
Other | IEEE Congress on Evolutionary Computation, CEC 2015 |
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Country/Territory | Japan |
City | Sendai |
Period | 5/25/15 → 5/28/15 |
All Science Journal Classification (ASJC) codes
- Computer Science Applications
- Computational Mathematics