Predicting RNA Structure Using Mutual Information View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2005-03

AUTHORS

Eva Freyhult, Vincent Moulton, Paul Gardner

ABSTRACT

BACKGROUND: With the ever-increasing number of sequenced RNAs and the establishment of new RNA databases, such as the Comparative RNA Web Site and Rfam, there is a growing need for accurately and automatically predicting RNA structures from multiple alignments. Since RNA secondary structure is often conserved in evolution, the well known, but underused, mutual information measure for identifying covarying sites in an alignment can be useful for identifying structural elements. This article presents MIfold, a MATLAB toolbox that employs mutual information, or a related covariation measure, to display and predict conserved RNA secondary structure (including pseudoknots) from an alignment. RESULTS: We show that MIfold can be used to predict simple pseudoknots, and that the performance can be adjusted to make it either more sensitive or more selective. We also demonstrate that the overall performance of MIfold improves with the number of aligned sequences for certain types of RNA sequences. In addition, we show that, for these sequences, MIfold is more sensitive but less selective than the related RNAalifold structure prediction program and is comparable with the COVE structure prediction package. CONCLUSION: MIfold provides a useful supplementary tool to programs such as RNA Structure Logo, RNAalifold and COVE, and should be useful for automatically generating structural predictions for databases such as Rfam. More... »

PAGES

53-59

Identifiers

URI

http://scigraph.springernature.com/pub.10.2165/00822942-200504010-00006

DOI

http://dx.doi.org/10.2165/00822942-200504010-00006

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1041856769

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/16000013


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