Statistical evaluation of improvement in RNA secondary structure prediction.

ABSTRACT: With discovery of diverse roles for RNA, its centrality in cellular functions has become increasingly apparent. A number of algorithms have been developed to predict RNA secondary structure. Their performance has been benchmarked by comparing structure predictions to reference secondary structures. Generally, algorithms are compared against each other and one is selected as best without statistical testing to determine whether the improvement is significant. In this work, it is demonstrated that the prediction accuracies of methods correlate with each other over sets of sequences. One possible reason for this correlation is that many algorithms use the same underlying principles. A set of benchmarks published previously for programs that predict a structure common to three or more sequence

SUBMITTER: Xu Z 

PROVIDER: S-EPMC3287165 | biostudies-literature | 2012 Feb

REPOSITORIES: biostudies-literature