J E Tabaska1, R B Cary, H N Gabow, G D Stormo. 1. 1Department of Molecular, Cellular and Developmental Biology and 2Department of Computer Science, University of Colorado, Boulder, CO 80309, USA.
Abstract
MOTIVATION: Recently, we described a Maximum Weighted Matching (MWM) method for RNA structure prediction. The MWM method is capable of detecting pseudoknots and other tertiary base-pairing interactions in a computationally efficient manner (Cary and Stormo, Proceedings of the Third International Conference on Intelligent Systems for Molecular Biology, pp. 75-80, 1995). Here we report on the results of our efforts to improve the MWM method's predictive accuracy, and show how the method can be extended to detect base interactions formerly inaccessible to automated RNA modeling techniques. RESULTS: Improved performance in MWM structure prediction was achieved in two ways. First, new ways of calculating base pair likelihoods have been developed. These allow experimental data and combined statistical and thermodynamic information to be used by the program. Second, accuracy was improved by developing techniques for filtering out spurious base pairs predicted by the MWM program. We also demonstrate here a means by which the MWM folding method may be used to detect the presence of base triples in RNAs. AVAILABILITY: http://www.cshl.org/mzhanglab/tabaska/j axpage. html CONTACT: tabaska@cshl.org
MOTIVATION: Recently, we described a Maximum Weighted Matching (MWM) method for RNA structure prediction. The MWM method is capable of detecting pseudoknots and other tertiary base-pairing interactions in a computationally efficient manner (Cary and Stormo, Proceedings of the Third International Conference on Intelligent Systems for Molecular Biology, pp. 75-80, 1995). Here we report on the results of our efforts to improve the MWM method's predictive accuracy, and show how the method can be extended to detect base interactions formerly inaccessible to automated RNA modeling techniques. RESULTS: Improved performance in MWM structure prediction was achieved in two ways. First, new ways of calculating base pair likelihoods have been developed. These allow experimental data and combined statistical and thermodynamic information to be used by the program. Second, accuracy was improved by developing techniques for filtering out spurious base pairs predicted by the MWM program. We also demonstrate here a means by which the MWM folding method may be used to detect the presence of base triples in RNAs. AVAILABILITY: http://www.cshl.org/mzhanglab/tabaska/j axpage. html CONTACT: tabaska@cshl.org
Authors: Peter Clote; Stefan Dobrev; Ivan Dotu; Evangelos Kranakis; Danny Krizanc; Jorge Urrutia Journal: J Math Biol Date: 2011-12-10 Impact factor: 2.259