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RNA Flexibility Prediction With Sequence Profile and Predicted Solvent Accessibility.

Authors :
Wei, Hong
Wang, Boling
Yang, Jianyi
Gao, Jianzhao
Source :
IEEE/ACM Transactions on Computational Biology & Bioinformatics; Sep/Oct2021, Vol. 18 Issue 5, p2017-2022, 6p
Publication Year :
2021

Abstract

Structural flexibility plays an essential role in many biological processes. B-factor is an important indicator to measure the flexibility of protein or RNA structures. Many methods were developed to predict protein B-factors, but few studies have been done for RNA B-factor prediction. In this paper, we proposed a new method RNAbval to predict RNA B-factors using random forest. The method was developed using a comprehensive set of features, including the sequence profile and predicted solvent accessibility. RNAbval achieved an improvement of 9.2-20.5 percent over the state-of-the-art method on two benchmark test datasets. The proposed method is available at http://yanglab.nankai.edu.cn/RNAbval/. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
15455963
Volume :
18
Issue :
5
Database :
Complementary Index
Journal :
IEEE/ACM Transactions on Computational Biology & Bioinformatics
Publication Type :
Academic Journal
Accession number :
153762931
Full Text :
https://doi.org/10.1109/TCBB.2019.2956496