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Cognitive Neurodynamics
Erschienen in: Cognitive Neurodynamics 3/2014

01.06.2014 | Brief Communication

Evaluating influence of microRNA in reconstructing gene regulatory networks

verfasst von: Ahsan Raja Chowdhury, Madhu Chetty, Nguyen Xuan Vinh

Erschienen in: Cognitive Neurodynamics | Ausgabe 3/2014

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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.
Vorheriger Artikel Exponential synchronization of memristive Cohen–Grossberg neural networks with mixed delays
Nächster Artikel Convergence analysis of fully complex backpropagation algorithm based on Wirtinger calculus

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Metadaten
Titel
Evaluating influence of microRNA in reconstructing gene regulatory networks
verfasst von
Ahsan Raja Chowdhury
Madhu Chetty
Nguyen Xuan Vinh
Publikationsdatum
01.06.2014
Verlag
Springer Netherlands
Erschienen in
Cognitive Neurodynamics / Ausgabe 3/2014
Print ISSN: 1871-4080
Elektronische ISSN: 1871-4099
DOI
https://doi.org/10.1007/s11571-013-9265-x

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