A parallel strategy for predicting the secondary structure of polycistronic microRNAs

The biogenesis of a functional microRNA is largely dependent on the secondary structure of the microRNA precursor (pre-miRNA). Recently, it has been shown that microRNAs are present in the genome as the form of polycistronic transcriptional units in plants and animals. It will be important to design efficient computational methods to predict such structures for microRNA discovery and its applications in gene silencing. In this paper, we propose a parallel algorithm based on the master-slave architecture to predict the secondary structure from an input sequence. We conducted some experiments to verify the effectiveness of our parallel algorithm. The experimental results show that our algorithm is able to produce the optimal secondary structure of polycistronic microRNAs.