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Prediction of Apoptosis Protein Subcellular Localization with Multilayer Sparse Coding and Oversampling Approach

The prediction of apoptosis protein subcellular localization plays an important role in understanding the progress in cell proliferation and death. Recently computational approaches to this issue have become very popular, since the traditional biological experiments are so costly and time-consuming...

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Autores principales: Chen, Xingjian, Hu, Xuejiao, Yi, Wenxin, Zou, Xiang, Xue, Wei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6374881/
https://www.ncbi.nlm.nih.gov/pubmed/30834257
http://dx.doi.org/10.1155/2019/2436924
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author Chen, Xingjian
Hu, Xuejiao
Yi, Wenxin
Zou, Xiang
Xue, Wei
author_facet Chen, Xingjian
Hu, Xuejiao
Yi, Wenxin
Zou, Xiang
Xue, Wei
author_sort Chen, Xingjian
collection PubMed
description The prediction of apoptosis protein subcellular localization plays an important role in understanding the progress in cell proliferation and death. Recently computational approaches to this issue have become very popular, since the traditional biological experiments are so costly and time-consuming that they cannot catch up with the growth rate of sequence data anymore. In order to improve the prediction accuracy of apoptosis protein subcellular localization, we proposed a sparse coding method combined with traditional feature extraction algorithm to complete the sparse representation of apoptosis protein sequences, using multilayer pooling based on different sizes of dictionaries to integrate the processed features, as well as oversampling approach to decrease the influences caused by unbalanced data sets. Then the extracted features were input to a support vector machine to predict the subcellular localization of the apoptosis protein. The experiment results obtained by Jackknife test on two benchmark data sets indicate that our method can significantly improve the accuracy of the apoptosis protein subcellular localization prediction.
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spelling pubmed-63748812019-03-04 Prediction of Apoptosis Protein Subcellular Localization with Multilayer Sparse Coding and Oversampling Approach Chen, Xingjian Hu, Xuejiao Yi, Wenxin Zou, Xiang Xue, Wei Biomed Res Int Research Article The prediction of apoptosis protein subcellular localization plays an important role in understanding the progress in cell proliferation and death. Recently computational approaches to this issue have become very popular, since the traditional biological experiments are so costly and time-consuming that they cannot catch up with the growth rate of sequence data anymore. In order to improve the prediction accuracy of apoptosis protein subcellular localization, we proposed a sparse coding method combined with traditional feature extraction algorithm to complete the sparse representation of apoptosis protein sequences, using multilayer pooling based on different sizes of dictionaries to integrate the processed features, as well as oversampling approach to decrease the influences caused by unbalanced data sets. Then the extracted features were input to a support vector machine to predict the subcellular localization of the apoptosis protein. The experiment results obtained by Jackknife test on two benchmark data sets indicate that our method can significantly improve the accuracy of the apoptosis protein subcellular localization prediction. Hindawi 2019-01-30 /pmc/articles/PMC6374881/ /pubmed/30834257 http://dx.doi.org/10.1155/2019/2436924 Text en Copyright © 2019 Xingjian Chen et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Chen, Xingjian
Hu, Xuejiao
Yi, Wenxin
Zou, Xiang
Xue, Wei
Prediction of Apoptosis Protein Subcellular Localization with Multilayer Sparse Coding and Oversampling Approach
title Prediction of Apoptosis Protein Subcellular Localization with Multilayer Sparse Coding and Oversampling Approach
title_full Prediction of Apoptosis Protein Subcellular Localization with Multilayer Sparse Coding and Oversampling Approach
title_fullStr Prediction of Apoptosis Protein Subcellular Localization with Multilayer Sparse Coding and Oversampling Approach
title_full_unstemmed Prediction of Apoptosis Protein Subcellular Localization with Multilayer Sparse Coding and Oversampling Approach
title_short Prediction of Apoptosis Protein Subcellular Localization with Multilayer Sparse Coding and Oversampling Approach
title_sort prediction of apoptosis protein subcellular localization with multilayer sparse coding and oversampling approach
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6374881/
https://www.ncbi.nlm.nih.gov/pubmed/30834257
http://dx.doi.org/10.1155/2019/2436924
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