DocumentCode :
167318
Title :
Neutral graph of regulatory Boolean networks using evolutionary computation
Author :
Ruz, Gonzalo A. ; Goles, Eric
Author_Institution :
Fac. de Ing. y Cienc., Univ. Adolfo Ibanez, Santiago, Chile
fYear :
2014
fDate :
21-24 May 2014
Firstpage :
1
Lastpage :
8
Abstract :
An evolution strategy is proposed to construct neutral graphs. The proposed method is applied to the construction of the neutral graph of Boolean regulatory networks that share the same state sequences of the cell cycle of the fission yeast. The regulatory networks in the neutral graph are analyzed, identifying characteristics of the networks which belong to the connected component of the fission yeast cell cycle network and the regulatory networks that are not in the connected component. Results show not only topological differences, but also differences in the state space between networks in the connected component and the rest of the networks in the neutral graph. It was found that regulatory networks in the fission yeast cell cycle network connected component can be mutated (change in their interaction matrices) no more than three times, if more mutations occur, then the networks leave the connected component. Comparisons with a standard genetic algorithm shows the effectiveness of the proposed evolution strategy.
Keywords :
Boolean algebra; cellular biophysics; evolution (biological); genetics; graph theory; matrix algebra; microorganisms; system theory; Boolean network state space; cell cycle state sequences; evolution strategy; evolutionary computation; fission yeast cell cycle network component connection; genetic algorithm; interaction matrix change; neutral graph construction; neutral graph regulatory network analysis; regulatory Boolean networks; regulatory network mutation; topological differences; Evolutionary computation; Genetic algorithms; Histograms; Limit-cycles; Robustness; Standards; Vectors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence in Bioinformatics and Computational Biology, 2014 IEEE Conference on
Conference_Location :
Honolulu, HI
Type :
conf
DOI :
10.1109/CIBCB.2014.6845529
Filename :
6845529
Link To Document :
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