An Algorithmic Game-Theory Approach for Coarse-Grain Prediction of RNA 3D Structure
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Research Article: Novel features for identifying A-minors in three-dimensional RNA molecules
Computational Biology and Chemistry
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We present an algorithm for automatically predicting the topological family of any RNA three-way junction, given only the information from the secondary structure: the sequence and the Watson-Crick pairings. The parameters of the algorithm have been determined on a data set of 33 three-way junctions whose 3D conformation is known. We applied the algorithm on 53 other junctions and compared the predictions to the real shape of those junctions. We show that the correct answer is selected out of nine possible configurations 64% of the time. Additionally, these results are noticeably improved if homology information is used. The resulting software, Cartaj, is available online and downloadable (with source) at: http://cartaj.lri.fr.