Title :
Bio-inspired reverse engineering of regulatory networks
Author :
Santini, Cristina Costa ; Tufte, Gunnar ; Haddow, Pauline
Author_Institution :
Dept. of Comput. & Inf. Sci. (IDI), Norwegian Univ. of Sci. & Technol. (NTNU), Trondheim
Abstract :
Regulatory networks are complex networks. This paper addresses the challenge of modelling these networks. The Boolean representation is chosen and supported as a suitable representation for an abstract approach. In in-silico experiments, two different bio-inspired techniques are applied to the reverse engineering of a Boolean regulatory network: as a search method a Genetic Algorithm is applied and an indirect method based on Artificial Development and tuned to this application, is proposed. Both methods are challenged at reverse engineering a known network - the yeast cell-cycle network model. Presented results show that they are both successful in reverse engineering the considered network.
Keywords :
Boolean functions; biology computing; genetic algorithms; search problems; Boolean regulatory network; Boolean representation; artificial development; bioinspired reverse engineering; complex networks; genetic algorithm; search method; yeast cell-cycle network; Biological system modeling; Complex networks; Crosstalk; Fungi; Genetic algorithms; Humans; Reverse engineering; Search methods; Signal processing; Systems biology;
Conference_Titel :
Evolutionary Computation, 2009. CEC '09. IEEE Congress on
Conference_Location :
Trondheim
Print_ISBN :
978-1-4244-2958-5
Electronic_ISBN :
978-1-4244-2959-2
DOI :
10.1109/CEC.2009.4983283