Perl

MicroRNAs are a family of ~22 nt small RNAs that can regulate gene expression at the post-transcriptional level. Identification of these molecules and their targets can aid understanding of regulatory processes. Recently, HTS has become a common identification method but there are two major limitations associated with the technique. Firstly, the method has low efficiency, with typically less than 1 in 10,000 sequences representing miRNA reads and secondly the method preferentially targets highly expressed miRNAs.

Next generation sequencing (NGS) techniques have been widely used to document the small ribonucleic acids (RNAs) implicated in a variety of biological, physiological and pathological processes. An integrated computational tool is needed for handling and analysing the enormous datasets from small RNA deep sequencing approach.

MicroRNAs (miRNAs) are approximately 20- to 22-nt long endogenous RNA sequences that play a critical role in the regulation of gene expression in eukaryotic genomes. Confident identification of miRNA targets is vital to understand their functions. Currently available computational algorithms for miRNA target prediction have diverse degrees of sensitivity and specificity and as a consequence each predicted target generally requires experimental confirmation.

MicroRNAs (miRNAs) have been implicated to play key roles in normal physiological functions, and altered expression of specific miRNAs has been associated with a number of diseases. It is of great interest to understand their roles and a prerequisite for such study is the ability to comprehensively and accurately assess the levels of the entire repertoire of miRNAs in a given sample. It has been shown that some miRNAs frequently have sequence variations termed isomirs.