Abstract
Reconstruction of gene networks has become an important activity in Systems Biology. The potential for better methods of drug discovery and of disease diagnosis hinge upon our understanding of the interaction networks between the genes. Evolutionary methods are proving to be successful in such problems and a number of such methods have been proposed. However, all these methods are based on processing of genotypic information. We have presented an evolutionary algorithm for reconstructing gene networks from expression data using phenotypic interactions, thereby avoiding the need for an explicit objective function. Specifically, we have also extended the basic phenomic algorithm to perform multiobjective optimization for gene network reconstruction. We have applied this novel algorithm to the yeast sporulation dataset and validated it by comparing the results to the links found between genes of the yeast genome at the SGD database.
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D’Souza, R.G.L., Sekaran, K.C., Kandasamy, A. (2012). A Multiobjective Phenomic Algorithm for Inference of Gene Networks. In: Suzuki, J., Nakano, T. (eds) Bio-Inspired Models of Network, Information, and Computing Systems. BIONETICS 2010. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 87. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32615-8_42
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DOI: https://doi.org/10.1007/978-3-642-32615-8_42
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