Parallel information theory based construction of gene regulatory networks

Authors:
Jaroslaw Zola;Maneesha Aluru;Srinivas Aluru
Affiliations:
Department of Electrical and Computer Engineering, Iowa State University, Ames, IA;Department of Genetics, Cellular, and Developmental Biology, Iowa State University, Ames, IA;Department of Electrical and Computer Engineering, Iowa State University, Ames, IA
Venue:
HiPC'08 Proceedings of the 15th international conference on High performance computing
Year:
2008

Citing 4
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Abstract

We present a parallel method for construction of gene regulatorynetworks from large-scale gene expression data. Our method integratesmutual information, data processing inequality and statisticaltesting to detect significant dependencies between genes, and efficientlyexploits parallelism inherent in such computations. We present a novelmethod to carry out permutation testing for assessing statistical significancewhile reducing its computational complexity by a factor of Θ(n2),where n is the number of genes. Using both synthetic and known regulatorynetworks, we show that our method produces networks of qualitysimilar to ARACNE, a widely used mutual information based method.We present a parallelization of the algorithm that, for the first time, allowsconstruction of whole genome networks from thousands of microarrayexperiments using rigorous mutual information based methodology.We report the construction of a 15,147 gene network of the plant Arabidopsisthaliana from 2,996 microarray experiments on a 2,048-CPUBlue Gene/L in 45 minutes, thus addressing a grand challenge problemin the NSF Arabidopsis 2010 initiative.