Integrated analysis of the miRNA-mRNA next-generation sequencing data for finding their associations in different cancer types.

Integrated analysis of the miRNA-mRNA next-generation sequencing data for finding their associations in different cancer types. Comput Biol Chem. 2019 Nov 18;:107152 Authors: Bhowmick SS, Bhattacharjee D, Rato L Abstract microRNAs (miRNAs) are short, non-coding, endogenous RNA molecule that regulates messenger RNAs (mRNAs) at the post-transcriptional level. The discovery of this regulatory relationship between miRNAs and mRNAs is an important research direction. In this regard, our method proposed an integrated approach to identify the mRNA targets of dysregulated miRNAs using next-generation sequencing data from six cancer types. For this analysis, a sensible combination of data mining tools is chosen. In particular, Random Forest, log-transformed Fold change, and Pearson correlation coefficient are considered to find the potential miRNA-mRNA pairs. During this study, we have identified six cancer-specific overlapping sets of miRNAs whose classification accuracy is always higher than 91%. Furthermore, a promising correlation signature of significantly dysregulated miRNAs and mRNAs are recognized. A comprehensive analysis found that the cumulative percentage of negative correlation coefficients is higher than its positive counterpart. Moreover, experimentally validated miRNA-target interactions databases called miRTarBase is used to validate significantly correlated mRNAs. According to our study, the smallest set of significantly dys...
Source: Computational Biology and Chemistry - Category: Bioinformatics Authors: Tags: Comput Biol Chem Source Type: research