Protein structure prediction based on BN-GRU method-Reference-Cited by-同舟云学术

Protein structure prediction based on BN-GRU method

Published:2020-08-11 Issue:06 Volume:18 Page:2050045
ISSN:0219-6913
Container-title:International Journal of Wavelets, Multiresolution and Information Processing
language:en
Short-container-title:Int. J. Wavelets Multiresolut Inf. Process.

Author:

Yang Lina¹²,Wei Pu¹²^ORCID,Zhong Cheng¹²,Li Xichun³,Tang Yuan Yan⁴

Affiliation:

1. School of Computer, Electronics and Information, Guangxi University, Nanning 530004, P. R. China

2. Guangxi Colleges and Universities Key Laboratory of Parallel and Distributed Computing, Nanning 530004, P. R. China

3. Guangxi Normal University for Nationalities, Chongzuo 532200, P. R. China

4. Beihang University, Beijing Advanced Innovation Center for Big Data and Brain Computing (BDBC), Beijing, P. R. China

Abstract

The spatial structure of the protein reflects the biological function and activity mechanism. Predicting the secondary structure of a protein is the basis content for predicting its spatial structure. Traditional methods based on statistics and sequential patterns do not achieve higher accuracy. In this paper, the application of BN-GRU neural network in protein structure prediction is discussed. The main idea is to construct a Gated Recurrent Unit (GRU) neural network. The GRU neural network can learn long-term dependencies. It can handle long sequences better than traditional methods. Based on this, BN is combined with GRU to construct a new network. Position Specific Scoring Matrix (PSSM) is used to associate with other features to build a completely new feature set. It can be proved that the application of BN on GRU can improve the accuracy of the results. The idea in this paper can also be applied to the analysis of similarity of other sequences.

Publisher

World Scientific Pub Co Pte Lt

Subject

Applied Mathematics,Information Systems,Signal Processing

Link

https://www.worldscientific.com/doi/pdf/10.1142/S0219691320500459

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