- Title
- An effective method for evolving reaction networks in synthetic biochemical systems
- Creator
- Dinh, Huy Q.; Aubert, Nathanael; Noman, Nasimul; Fujii, Teruo; Rondelez, Yannick; Iba, Hitoshi
- Relation
- IEEE Transactions on Evolutionary Computation Vol. 19, Issue 3, p. 374-386
- Publisher Link
- http://dx.doi.org/10.1109/TEVC.2014.2326863
- Publisher
- Institute of Electrical and Electronics Engineers (IEEE)
- Resource Type
- journal article
- Date
- 2015
- Description
- In this paper, we introduce our approach for evolving reaction networks. It is an efficient derivative of the neuroevolution of augmenting topologies algorithm directed at the evolution of biochemical systems or molecular programs. Our method addresses the problem of meaningful crossovers between two chemical reaction networks of different topologies. It also builds on features such as speciation to speed up the search, to the point where it can deal with complete, realistic mathematical models of the biochemical processes. We demonstrate this framework by evolving credible biochemical answers to challenging autonomous molecular problems: in vitro batch oscillatory networks that match specific oscillation shapes. Our experimental results suggest that the search space is efficiently covered and that, by using crossover and preserving topological innovations, significant improvements in performance can be obtained for the automatic design of molecular programs.
- Subject
- topology; biochemistry; molecular biophysics; physiological models
- Identifier
- http://hdl.handle.net/1959.13/1338714
- Identifier
- uon:28084
- Identifier
- ISSN:1089-778X
- Rights
- © 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.
- Language
- eng
- Full Text
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