Cognitive Neurodynamics

, Volume 8, Issue 3, pp 251–259 | Cite as

Evaluating influence of microRNA in reconstructing gene regulatory networks

  • Ahsan Raja ChowdhuryEmail author
  • Madhu Chetty
  • Nguyen Xuan Vinh
Brief Communication


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.


Gene regulatory network Microarray microRNA 



This work is supported in part by NICTA (National Information and Communication Technology Australia) research in Systems Biology flagship program.


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Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  • Ahsan Raja Chowdhury
    • 1
    • 2
    Email author
  • Madhu Chetty
    • 1
    • 2
  • Nguyen Xuan Vinh
    • 1
  1. 1.Gippsland School of Information TechnologyMonash UniversityVictoriaAustralia
  2. 2.National ICT Australia (NICTA)VRLMelbourneAustralia

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