Surveying computational algorithms for identification of miRNA–mRNA regulatory modules

Abstract

MicroRNAs (miRNAs) are small non-coding RNA that target gene expression at post-transcriptional level. To understand the molecular basis of miRNA regulation, it is essential to identify reliable miRNA target mRNAs and miRNA–mRNA functional networks. Several computational algorithms and tools are widely used for discovering miRNA–mRNA regulatory modules. We have comprehensively reviewed thirty-two tools and databases that were developed over the past decade. Our in-depth survey considers all significant features including underlying methodologies in each tool for basis of miRNA–mRNA functional module discovery. Current miRNA–mRNA functional module identification tools utilizes sequence based prediction, graph theory combined with Bayesian network, probabilistic and rule learning methods. Further we discuss ease of use, availability, and suitability of these methods, and provide an overview of recent computational algorithms used in miRNA–mRNA regulatory module identification.