As miRNA regulate mRNA expression and its biological function was a hot research domain in these years, so we chose this topic as our job. We proposed SMESE, a novel miRNA target prediction tool created specifically for the reproductive system. The performance of SMESE was validated by experiment, and outperforms than other algorithms greatly.

SMESE (seed type, seed match number, hybrid energy, mRNA structure and expression data are used as the parameters for the prediction tools) is developed to find the relationship between miRNAs and their targeted genes. This algorithm combines both sequence- and expression-derived information, and it is constructed based on logistic regression model (LRM) and support vector machine (SVMs)