Improving RNA secondary structure prediction using direct coupling analysis

doi:10.1088/1674-1056/ab889d

Abstract Secondary structures of RNAs are the basis of understanding their tertiary structures and functions and so their predictions are widely needed due to increasing discovery of noncoding RNAs. In the last decades, a lot of methods have been proposed to predict RNA secondary structures but their accuracies encountered bottleneck. Here we present a method for RNA secondary structure prediction using direct coupling analysis and a remove-and-expand algorithm that shows better performance than four existing popular multiple-sequence methods. We further show that the results can also be used to improve the prediction accuracy of the single-sequence methods.

Keywords: RNA secondary structure structure prediction direct coupling analysis

Received: 23 March 2020
Revised: 08 April 2020
Accepted manuscript online:

PACS:	87.15.bd	(Secondary structure)
	87.14.gn	(RNA)
	87.15.A-	(Theory, modeling, and computer simulation)

Fund: Project supported by the National Natural Science Foundation of China (Grant No. 31570722).

Corresponding Authors: Yi Xiao
E-mail: yxiao@hust.edu.cn

Cite this article:

Xiaoling He(何小玲), Jun Wang(王军), Jian Wang(王剑), Yi Xiao(肖奕) Improving RNA secondary structure prediction using direct coupling analysis 2020 Chin. Phys. B 29 078702

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Improving RNA secondary structure prediction using direct coupling analysis

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