An Integrated Approach for Identification of Functionally Similar MicroRNAs in Colorectal Cancer.

Colorectal cancer (CRC) is one of the most prevalent cancers around the globe. However, the molecular reasons for pathogenesis of CRC is still poorly understood. Recently, role of microRNAs or miRNAs in the initiation and progression of CRC has been studied. MicroRNAs are small, endogenous non-coding RNAs found in plants, animals, and some viruses, which function in RNA silencing and post-transcriptional regulation of gene expression. Their role in CRC development is studied and are found to be potential biomarkers in diagnosis and treatment of CRC. Therefore, identification of functionally similar CRC related miRNAs may help in the development of prognostic tool. In this regard, this paper presents a new algorithm, called Sim. It is an integrative approach for identification of functionally similar miRNAs associated with CRC. It integrates judiciously the information of miRNA expression data and miRNA-miRNA functionally synergistic network data. The functional similarity is calculated based on both miRNA expression data and miRNA-miRNA functionally synergistic network data. The effectiveness of the proposed method in comparison to other related methods are shown on four CRC miRNA data sets. The proposed method selected more significant miRNAs related to CRC as compared to other related methods.