Consensus Folding of Unaligned RNA Sequences Revisited
Vineet Bafna, Department of CSE, University of California, San Diege, La Jolla, CA 92093-0404 USA, vbafna at cs dot ucsd dot edu
Haixu Tang, School of Informatics, Indiana University, Bloomington, IN 47408-3912 USA, htang at indiana dot edu
Shaojie Zhang*, Department of CSE, University of California, San Diege, La Jolla, CA 92093-0404 USA, shzhang at cs dot ucsd dot edu
*Current address: School of EECS, University of Central Florida, Orlando, FL 32816-2362 USA, shzhang at cs dot ucf dot edu
Abstract
As one of the earliest problems in computational biology, RNA secondary structure prediction (sometimes referred to as “RNA folding”) problem has attracted attention again, thanks to the recent discoveries of many novel non-coding RNA molecules. The two common approaches to this problem are de novo prediction of RNA secondary structure based on energy minimization and the consensus folding approach (computing the common secondary structure for a set of unaligned RNA sequences). Consensus folding algorithms work
well when the correct seed alignment is part of the input to the problem. However, seed alignment itself is a challenging problem for diverged RNA families. In this paper, we propose a novel framework to predict the common secondary structure for unaligned RNA
sequences. By matching putative stacks in RNA sequences, we make use of both primary sequence information and thermodynamic stability for prediction at the same time. We show that our method can predict the correct common RNA secondary structures even when we are given only a limited number of unaligned RNA sequences, and it outperforms current algorithms in sensitivity and accuracy.
Citation
Vineet Bafna, Haixu Tang and Shaojie Zhang, "Consensus folding of unaligned
RNA sequences revisited",
Journal of Computational Biology, Vol. 13, No. 2, page 283-295, 2006.
Pubmed
Vineet Bafna, Haixu Tang and Shaojie Zhang, "Consensus folding of unaligned
RNA sequences revisited",
In RECOMB 2005: Proceedings of the 9th annual international conference on res
earch in
computational molecular biology, 2005. SpringerLink
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