Parallel RNA secondary structure prediction using stochastic context-free grammars: Research Articles

Authors:
Tong Liu;Bertil Schmidt
Affiliations:
School of Computer Engineering, Nanyang Technological University, Singapore 639798;School of Computer Engineering, Nanyang Technological University, Singapore 639798
Venue:
Concurrency and Computation: Practice & Experience - Third IEEE International Workshop on High Performance Computational Biology (HiCOMB 2004)
Year:
2005

Citing 0
Cited 3

Fine-grained parallel application specific computing for RNA secondary structure prediction using SCFGS on FPGA

CASES '09 Proceedings of the 2009 international conference on Compilers, architecture, and synthesis for embedded systems
Fine-grained parallel RNA secondary structure prediction using SCFGs on FPGA

Parallel Computing
Hardware-Accelerated RNA Secondary-Structure Alignment

ACM Transactions on Reconfigurable Technology and Systems (TRETS)

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Abstract

With the growing number of known RNA genes efficient and accurate computational analysis of RNA sequences is becoming increasingly important. Stochastic context-free grammars (SCFGs) are used as a popular tool to model RNA secondary structures. However, algorithms for aligning a RNA sequence to a SCFG are highly compute-intensive. This has so far limited applications of SCFGs to relatively small problem sizes. In this paper we present the design of a parallel RNA sequence-structure alignment algorithm. Its implementation on parallel systems leads to significant runtime savings. This makes it possible to compute sequence-structure alignments of even the largest RNAs such as small subunit ribosomal rRNAs and long subunit ribosomal rRNAs in reasonable time. Copyright © 2005 John Wiley & Sons, Ltd.