title: Evaluating influence of microRNA in reconstructing gene regulatory networks.
abstract: Gene regulatory network (GRN) consists of interactions between transcription factors (TFs) and target genes (TGs). Recently, it has been observed that micro RNAs (miRNAs) play a significant part in genetic interactions. However, current microarray technologies do not capture miRNA expression levels. To overcome this, we propose a new technique to reverse engineer GRN from the available partial microarray data which contains expression levels of TFs and TGs only. Using S-System model, the approach is adapted to cope with the unavailability of information about the expression levels of miRNAs. The versatile Differential Evolutionary algorithm is used for optimization and parameter estimation. Experimental studies on four in silico networks, and a real network of Saccharomyces cerevisiae called IRMA network, show significant improvement compared to traditional S-System approach.
authors.affiliation: Gippsland School of Information Technology, Monash University, Victoria, Australia ; National ICT Australia (NICTA), VRL, Melbourne, Australia.
authors.forename: Ahsan Raja
authors.initials: AR
authors.lastname: Chowdhury
authors.affiliation: Gippsland School of Information Technology, Monash University, Victoria, Australia ; National ICT Australia (NICTA), VRL, Melbourne, Australia.
authors.forename: Madhu
authors.initials: M
authors.lastname: Chetty
authors.affiliation: Gippsland School of Information Technology, Monash University, Victoria, Australia.
authors.forename: Nguyen Xuan
authors.initials: NX
authors.lastname: Vinh
keywords: Gene regulatory network; Microarray; microRNA