Research Article

Novel representation of RNA secondary structure used to improve prediction algorithms

Published: September 09, 2011
Genet. Mol. Res. 10 (3) : 1986-1998 DOI: https://doi.org/10.4238/vol10-3gmr1181
Cite this Article:
Q. Zou, C. Lin, X.Y. Liu, Y.P. Han, W.B. Li, M.Z. Guo (2011). Novel representation of RNA secondary structure used to improve prediction algorithms. Genet. Mol. Res. 10(3): 1986-1998. https://doi.org/10.4238/vol10-3gmr1181
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Abstract

We propose a novel representation of RNA secondary structure for a quick comparison of different structures. Secondary structure was viewed as a set of stems and each stem was represented by two values according to its position. Using this representation, we improved the comparative sequence analysis method results and the minimum free-energy model. In the comparative sequence analysis method, a novel algorithm independent of multiple sequence alignment was developed to improve performance. When dealing with a single-RNA sequence, the minimum free-energy model is improved by combining it with RNA class information. Secondary structure prediction experiments were done on tRNA and RNAse P RNA; sensitivity and specificity were both improved. Furthermore, software programs were developed for non-commercial use.

We propose a novel representation of RNA secondary structure for a quick comparison of different structures. Secondary structure was viewed as a set of stems and each stem was represented by two values according to its position. Using this representation, we improved the comparative sequence analysis method results and the minimum free-energy model. In the comparative sequence analysis method, a novel algorithm independent of multiple sequence alignment was developed to improve performance. When dealing with a single-RNA sequence, the minimum free-energy model is improved by combining it with RNA class information. Secondary structure prediction experiments were done on tRNA and RNAse P RNA; sensitivity and specificity were both improved. Furthermore, software programs were developed for non-commercial use.