A parallel strategy for predicting the secondary structure of polycistronic microRNAs

Authors:
Dianwei Han;Guiliang Tang;Jun Zhang
Affiliations:
Department of Computer Science, University of Kentucky, Anderson Hall 773 FPAT, Lexington, KY 40506-0046, USA;Department of Plant and Soil Sciences, University of Kentucky, 1401 University Drive, Lexington, KY 40546-0236, USA;Department of Computer Science, University of Kentucky, Anderson Hall 773 FPAT, Lexington, KY 40506-0046, USA
Venue:
International Journal of Bioinformatics Research and Applications
Year:
2013

Citing 4
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Solving large FPT problems on coarse-grained parallel machines

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A novel method for MicroRNA secondary structure prediction using a bottom-up algorithm

Proceedings of the 47th Annual Southeast Regional Conference

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Abstract

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.