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


Autoria(s): Chandra, Shekara Bhat C; Sumam, Mary Idicula; Vineetha, S
Data(s)

17/07/2014

17/07/2014

20/12/2012

Resumo

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

Gene 515 (2013) 385–390

Cochin University of Science and Technology

Identificador

http://dyuthi.cusat.ac.in/purl/4097

Idioma(s)

en

Publicador

Elsevier

Palavras-Chave #MicroRNA #Microarray data #MicroRNA–mRNA Interaction Network #TSK-type recurrent neural fuzzy network #Fuzzy logic
Tipo

Article