Knudsen-Hein algorithm for predicting structure of aligned RNA sequences
Bioinformatics. 1999 Jun;15(6):446-54.
RNA secondary structure prediction using stochastic context-free grammars and
evolutionary history.
Knudsen B, Hein J.
Department of Genetics and Ecology, The Institute of Biological Sciences,
University of Aarhus, Building 550, Ny Munkegade, 8000 Aarhus C, Denmark.
bk@imf.au.dk
MOTIVATION: Many computerized methods for RNA secondary structure prediction
have been developed. Few of these methods, however, employ an evolutionary
model, thus relevant information is often left out from the structure
determination. This paper introduces a method which incorporates evolutionary
history into RNA secondary structure prediction. The method reported here is
based on stochastic context-free grammars (SCFGs) to give a prior probability
distribution of structures. RESULTS: The phylogenetic tree relating the
sequences can be found by maximum likelihood (ML) estimation from the model
introduced here. The tree is shown to reveal information about the structure,
due to mutation patterns. The inclusion of a prior distribution of RNA
structures ensures good structure predictions even for a small number of related
sequences. Prediction is carried out using maximum a posteriori estimation (MAP)
estimation in a Bayesian approach. For small sequence sets, the method performs
very well compared to current automated methods.
Publication Types:
Research Support, Non-U.S. Gov't
PMID: 10383470 [PubMed - indexed for MEDLINE]
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