- Title
- Evaluating influence of microRNA in reconstructing gene regulatory networks
- Creator
- Chowdhury, Ahsan; Chetty, Madhu; Nguyen, Vinh
- Date
- 2015
- Type
- Text; Journal article
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/157243
- Identifier
- vital:11540
- Identifier
-
https://doi.org/10.1007/s11571-013-9265-x
- Identifier
- ISSN:1871-4099
- Identifier
- https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4012069/
- 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.
- Relation
- Cognitive neurodynamics Vol. 8, no. 3 (2015), p. 251-9
- Rights
- Copyright Springer
- Rights
- Open Access
- Rights
- This metadata is freely available under a CCO license
- Subject
- Gene Regulatory Network; GRN; Microarray; Microrna; 0606 Physiology; 1116 Medical Physiology; 1702 Cognitive Science
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