Please use this identifier to cite or link to this item: http://localhost:8080/xmlui/handle/123456789/2581
Title: MicroRNA–mRNA interaction network using TSK-type recurrent neural fuzzy network
Authors: Vineetha, S
Chandra Shekara Bhat, C
Sumam Mary, Idicula
Keywords: MicroRNA
Microarray data
MicroRNA–mRNA Interaction Network
TSK-type recurrent neural fuzzy network
Fuzzy logic
Issue Date: 20-Dec-2012
Publisher: Elsevier
Citation: Gene 515 (2013) 385–390
Abstract: MicroRNAs are short non-coding RNAs that can regulate gene expression during various crucial cell processes such as differentiation, proliferation and apoptosis. Changes in expression profiles of miRNA play an important role in the development of many cancers, including CRC. Therefore, the identification of cancer related miRNAs and their target genes are important for cancer biology research. In this paper, we applied TSK-type recurrent neural fuzzy network (TRNFN) to infer miRNA–mRNA association network from paired miRNA, mRNA expression profiles of CRC patients. We demonstrated that the method we proposed achieved good performance in recovering known experimentally verified miRNA–mRNA associations. Moreover, our approach proved successful in identifying 17 validated cancer miRNAs which are directly involved in the CRC related pathways. Targeting such miRNAs may help not only to prevent the recurrence of disease but also to control the growth of advanced metastatic tumors. Our regulatory modules provide valuable insights into the pathogenesis of cancer.
Appears in Collections:2013

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