Improving the accuracy of predicting secondary structure for aligned RNA sequences.

ABSTRACT: Considerable attention has been focused on predicting the secondary structure for aligned RNA sequences since it is useful not only for improving the limiting accuracy of conventional secondary structure prediction but also for finding non-coding RNAs in genomic sequences. Although there exist many algorithms of predicting secondary structure for aligned RNA sequences, further improvement of the accuracy is still awaited. In this article, toward improving the accuracy, a theoretical classification of state-of-the-art algorithms of predicting secondary structure for aligned RNA sequences is presented. The classification is based on the viewpoint of maximum expected accuracy (MEA), which has been successfully applied in various problems in bioinformatics. The classification reveals several d

SUBMITTER: Hamada M 

PROVIDER: S-EPMC3025558 | biostudies-literature | 2011 Jan

REPOSITORIES: biostudies-literature