The importance of accurate and fast predictions of multiple alignments for RNA sequences has increased due to recent findings about functional non-coding RNAs. Recent studies suggest that maximizing the expected accuracy of predictions will be useful for many problems in bioinformatics.
Researchers at the Mizuho Information & Research Institute designed a novel estimator for multiple alignments of structured RNAs, based on maximizing the expected accuracy of predictions. First, they define the maximum expected accuracy (MEA) estimator for pairwise alignment of RNA sequences. This maximizes the expected sum-of-pairs score (SPS) of a predicted alignment under a probability distribution of alignments given by marginalizing the Sankoff model. Then, by approximating the MEA estimator, they obtain an estimator whose time complexity is O(L(3)+c(2)dL(2)) where L is the length of input sequences and both c and d are constants independent of L. The proposed estimator can handle uncertainty of secondary structures and alignments that are obstacles in Bioinformatics because it considers all the secondary structures and all the pairwise alignments as input sequences. Moreover, they integrate the probabilistic consistency transformation (PCT) on alignments into the proposed estimator. Computational experiments using six benchmark datasets indicate that the proposed method achieved a favorable SPS and was the fastest of many state-of-the-art tools for multiple alignments of structured RNAs.
AVAILABILITY: The software called CentroidAlign, which is an implementation of the algorithm in this article, is freely available at: http://www.ncrna.org/software/centroidalign/
- Hamada M, Sato K, Kiryu H, Mituyama T, Asai K. (2009) CentroidAlign: fast and accurate aligner for structured RNAs by maximizing expected sum-of-pairs score. Bioinformatics 25(24), 3236-43. [article]