Prediction of RNA secondary structure by maximizing pseudo-expected accuracy

Background: Recent studies have revealed the importance of considering the entire distribution of possible secondary structures in RNA secondary structure predictions; therefore, a new type of estimator is proposed including the maximum expected accuracy (MEA) estimator. The MEA-based estimators have been designed to maximize the expected accuracy of the base-pairs and have achieved the highest level of accuracy. Those methods, however, do not give the single best prediction of the structure, but employ parameters to control the trade-off between the sensitivity and the positive predictive value (PPV). It is unclear what parameter value we should use, and even the well-trained default parameter value does not, in general, give the best result in popular accuracy measures to each RNA sequence. Results: Instead of using the expected values of the popular accuracy measures for RNA secondary structure prediction, which is difficult to be calculated, the pseudo-expected accuracy, which can...

• Type: Journal
• Year: 2010
• Where: BMCBI
• Authors: Michiaki Hamada, Kengo Sato, Kiyoshi Asai
• Keywords: BMCBI 2010, Business, Pseudo-expected Accuracy, Rna Sequence, Secondary Structures