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An RNA secondary structure prediction method based on minimum and suboptimal free energy structures. (English) Zbl 1343.92377
Summary: The function of an RNA-molecule is mainly determined by its tertiary structures. And its secondary structure is an important determinant of its tertiary structure. The comparative methods usually give better results than the single-sequence methods. Based on minimum and suboptimal free energy structures, the paper presents a novel method for predicting conserved secondary structure of a group of related RNAs. In the method, the information from the known RNA structures is used as training data in a SVM (support vector machine) classifier. Our method has been tested on the benchmark dataset given by T. Puton et al. [“CompaRNA: a server for continuous benchmarking of automated methods for RNA secondary structure prediction”, Nucl. Acid. Res. 41, No. 7, 4307–4323 (2013; doi:10.1093/nar/gkt101)]. The results show that the average sensitivity of our method is higher than that of other comparative methods such as CentroidAlifold, MXScrana, RNAalifold, and TurboFold.
MSC:
92D20 Protein sequences, DNA sequences
68T05 Learning and adaptive systems in artificial intelligence
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