DocumentCode :
2319237
Title :
Combining genetic oscillators and switches using evolutionary algorithms
Author :
Thomas, Spencer Angus ; Jin, Yaochu
Author_Institution :
Dept. of Comput., Univ. of Surrey, Guildford, UK
fYear :
2012
fDate :
9-12 May 2012
Firstpage :
28
Lastpage :
34
Abstract :
It is hypothesised that complex biological gene regulatory networks can be evolved from simple networks through modularisation, duplication and specialisation processes. However, the biological mechanisms of this process remain elusive and little work has been done to verify this hypothesis in a computational environment. This paper aims to couple two simple regulatory motifs, one toggle switch and one self-sustained oscillator using an evolutionary algorithm, which can be seen as a computational simulation of natural evolution. We have successfully evolved several complex dynamics for two different connections arrangements between the oscillator and toggle switch networks in a master/slave set up, which confirms the previously reported results achieved manually. Our results indicate that generating complex dynamics by coupling of simple motifs using simulated evolutionary mechanisms is methodologically feasible and more efficient, which can be seen as an indirect and partial verification of the above hypothesis.
Keywords :
genetic algorithms; genetics; oscillators; complex biological gene regulatory networks; duplication; evolutionary algorithms; genetic oscillators; genetic switches; master-slave set up; modularisation; self-sustained oscillator; specialisation; toggle switch; Biology; Control systems; Couplings; Customer relationship management; Equations; Limit-cycles; Oscillators;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence in Bioinformatics and Computational Biology (CIBCB), 2012 IEEE Symposium on
Conference_Location :
San Diego, CA
Print_ISBN :
978-1-4673-1190-8
Type :
conf
DOI :
10.1109/CIBCB.2012.6217207
Filename :
6217207
Link To Document :
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