Abstract
Noisy nature of microarray data and platform bias has urged the need of cross-platform Gene Regulatory Network (GRN) fusion. This is, however, a difficult task because gene expressions generated from different platforms are not directly comparable. This paper presents Coalesce GRN (CGRN) Reconstruction framework which integrates cross-platform GRN to remove platform and experimental bias using Dempster Shafer theory of evidence. The proposed model mimics inherent fuzzy nature of gene co-regulation by using fuzzy logic and automatically determines model parameters. The CGRN was used to find common cancer related regulatory links in ten different datasets generated by different microarray platforms, including cDNA and Affymetrix arrays. The experimental results have demonstrated that CGRN can be applied effectively for the fusion of cross-platform gene networks.
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