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OCLSTM: Optimized convolutional and long short-term memory neural network model for protein secondary structure prediction
Protein secondary structure prediction is extremely important for determining the spatial structure and function of proteins. In this paper, we apply an optimized convolutional neural network and long short-term memory neural network models to protein secondary structure prediction, which is called...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7857624/ https://www.ncbi.nlm.nih.gov/pubmed/33534819 http://dx.doi.org/10.1371/journal.pone.0245982 |
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author | Zhao, Yawu Liu, Yihui |
author_facet | Zhao, Yawu Liu, Yihui |
author_sort | Zhao, Yawu |
collection | PubMed |
description | Protein secondary structure prediction is extremely important for determining the spatial structure and function of proteins. In this paper, we apply an optimized convolutional neural network and long short-term memory neural network models to protein secondary structure prediction, which is called OCLSTM. We use an optimized convolutional neural network to extract local features between amino acid residues. Then use the bidirectional long short-term memory neural network to extract the remote interactions between the internal residues of the protein sequence to predict the protein structure. Experiments are performed on CASP10, CASP11, CASP12, CB513, and 25PDB datasets, and the good performance of 84.68%, 82.36%, 82.91%, 84.21% and 85.08% is achieved respectively. Experimental results show that the model can achieve better results. |
format | Online Article Text |
id | pubmed-7857624 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-78576242021-02-11 OCLSTM: Optimized convolutional and long short-term memory neural network model for protein secondary structure prediction Zhao, Yawu Liu, Yihui PLoS One Research Article Protein secondary structure prediction is extremely important for determining the spatial structure and function of proteins. In this paper, we apply an optimized convolutional neural network and long short-term memory neural network models to protein secondary structure prediction, which is called OCLSTM. We use an optimized convolutional neural network to extract local features between amino acid residues. Then use the bidirectional long short-term memory neural network to extract the remote interactions between the internal residues of the protein sequence to predict the protein structure. Experiments are performed on CASP10, CASP11, CASP12, CB513, and 25PDB datasets, and the good performance of 84.68%, 82.36%, 82.91%, 84.21% and 85.08% is achieved respectively. Experimental results show that the model can achieve better results. Public Library of Science 2021-02-03 /pmc/articles/PMC7857624/ /pubmed/33534819 http://dx.doi.org/10.1371/journal.pone.0245982 Text en © 2021 Zhao, Liu http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Zhao, Yawu Liu, Yihui OCLSTM: Optimized convolutional and long short-term memory neural network model for protein secondary structure prediction |
title | OCLSTM: Optimized convolutional and long short-term memory neural network model for protein secondary structure prediction |
title_full | OCLSTM: Optimized convolutional and long short-term memory neural network model for protein secondary structure prediction |
title_fullStr | OCLSTM: Optimized convolutional and long short-term memory neural network model for protein secondary structure prediction |
title_full_unstemmed | OCLSTM: Optimized convolutional and long short-term memory neural network model for protein secondary structure prediction |
title_short | OCLSTM: Optimized convolutional and long short-term memory neural network model for protein secondary structure prediction |
title_sort | oclstm: optimized convolutional and long short-term memory neural network model for protein secondary structure prediction |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7857624/ https://www.ncbi.nlm.nih.gov/pubmed/33534819 http://dx.doi.org/10.1371/journal.pone.0245982 |
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