DocumentCode :
2319314
Title :
Quantitative analysis of redundancy in evolution of developmental systems
Author :
Schramm, Lisa ; Jin, Yaochu ; Sendhoff, Bernhard
Author_Institution :
Tech. Univ. Darmstadt, Darmstadt, Germany
fYear :
2012
fDate :
9-12 May 2012
Firstpage :
61
Lastpage :
68
Abstract :
Redundancy is believed to play a key role in robustness and evolvability of biological systems. This paper investigates the influence of redundancy on the evolutionary performance of a gene regulatory network governing a cellular growth process. Extensive simulation results suggest that, for the developmental model studied in this work, maintaining sufficient redundancy helps to improve the ability of the evolutionary algorithm to achieve better performance. To examine the change of redundancy during the evolutionary process and its relationship to evolutionary performance, we propose a quantitative definition for measuring different aspects of redundancy, namely, structural redundancy, functional redundancy and functional proximity. Our results show that evolution attempts to increase the functional redundancy after pruning of redundant genes if the evolution is under a larger selection pressure. It is also interesting to notice that an increase in functional proximity enhances the evolutionary performance.
Keywords :
cellular biophysics; complex networks; evolution (biological); genetics; molecular biophysics; molecular configurations; GRN evolutionary performance; biological system evolvability; biological system robustness; cellular growth process; developmental system evolution; evolutionary algorithm; evolutionary process; functional proximity; functional redundancy; gene regulatory network; redundancy quantitative analysis; structural redundancy; Biological cells; Biological system modeling; Computational modeling; Evolution (biology); Genetics; Redundancy; development; gene regulatory network; redundancy;
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.2012.6217212
Filename :
6217212
Link To Document :
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