Inference of gene regulatory network using modified genetic algorithm
ISB '10 Proceedings of the International Symposium on Biocomputing
Genetic Networks and Soft Computing
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
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Living organisms regulate the expression of genes using complex interactions of transcription factors, messenger RNA and active protein products. Due to their complexity, gene-regulatory networks are not fully understood, however, various modeling approaches can he used to gain insight into their function and operation. This paper describes an ongoing study to use evolutionary algorithms to create computational models of gene-regulatory networks based on observed microarray data. Because of the computational requirements of this approach (which requires the discovery of gene network topologies), it is critical that it is implemented on a computing platform capable of delivering significant compute power. We discuss how this can be achieved using distributed and grid computing technology. In particular we investigate how Condor and JavaSpaces technology is suited to the requirements of our modeling approach.