RAmiRNA: Software suite for generation of SVM-based prediction models of mature miRNAs

MicroRNAs (miRNAs) are short endogenous non-coding RNA molecules that regulate protein coding gene expression in animals, plants, fungi, algae and viruses through the RNA interference pathway. By virtue of their base complementarity, mature miRNAs stop the process of translation, thus acting as one of the important molecules in vivo. Attempts to predict precursor-miRNAs and mature miRNAs have been achieved in a significant number of model organisms but development of prediction models aiming at relatively less studied organisms are rare. In this work, we provide a suite of standalone softwares called RAmiRNA (RAdicalmiRNA detector), to solve the problem of custom development of prediction models for mature miRNAs using support vector machine (SVM) learning. RAmiRNA could be used to develop SVM based model for prediction of mature miRNAs in an organism or a group of organisms in a UNIX based local machine. Additionally RAmiRNA generates training accuracy for a quick estimation of prediction ability of generated model.