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.
