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MicroRNA-mRNA interaction network using TSK-type recurrent neural fuzzy network

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dc.contributor.author Vineetha, S
dc.contributor.author Chandra Shekara Bhat, C
dc.contributor.author Idicula, M S
dc.date.accessioned 2014-01-27T04:42:20Z
dc.date.available 2014-01-27T04:42:20Z
dc.date.issued 2013
dc.identifier.citation Gene 515(2):385-390;25 Feb 2013 en_US
dc.identifier.uri http://ir.niist.res.in:8080/jspui/handle/123456789/1151
dc.description.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. en_US
dc.language.iso en en_US
dc.publisher Elsevier en_US
dc.subject Microarray data en_US
dc.subject Cancer en_US
dc.subject Apoptosis en_US
dc.subject MicroRNA en_US
dc.subject MicroRNA-mRNA Interaction Network en_US
dc.subject TSK-type recurrent neural fuzzy network en_US
dc.subject Fuzzy logic en_US
dc.title MicroRNA-mRNA interaction network using TSK-type recurrent neural fuzzy network en_US
dc.type Article en_US


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