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Protein Sequence Comparison Based on Physicochemical Properties and the Position-Feature Energy Matrix
We develop a novel position-feature-based model for protein sequences by employing physicochemical properties of 20 amino acids and the measure of graph energy. The method puts the emphasis on sequence order information and describes local dynamic distributions of sequences, from which one can get a...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5385872/ https://www.ncbi.nlm.nih.gov/pubmed/28393857 http://dx.doi.org/10.1038/srep46237 |
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author | Yu, Lulu Zhang, Yusen Gutman, Ivan Shi, Yongtang Dehmer, Matthias |
author_facet | Yu, Lulu Zhang, Yusen Gutman, Ivan Shi, Yongtang Dehmer, Matthias |
author_sort | Yu, Lulu |
collection | PubMed |
description | We develop a novel position-feature-based model for protein sequences by employing physicochemical properties of 20 amino acids and the measure of graph energy. The method puts the emphasis on sequence order information and describes local dynamic distributions of sequences, from which one can get a characteristic B-vector. Afterwards, we apply the relative entropy to the sequences representing B-vectors to measure their similarity/dissimilarity. The numerical results obtained in this study show that the proposed methods leads to meaningful results compared with competitors such as Clustal W. |
format | Online Article Text |
id | pubmed-5385872 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-53858722017-04-12 Protein Sequence Comparison Based on Physicochemical Properties and the Position-Feature Energy Matrix Yu, Lulu Zhang, Yusen Gutman, Ivan Shi, Yongtang Dehmer, Matthias Sci Rep Article We develop a novel position-feature-based model for protein sequences by employing physicochemical properties of 20 amino acids and the measure of graph energy. The method puts the emphasis on sequence order information and describes local dynamic distributions of sequences, from which one can get a characteristic B-vector. Afterwards, we apply the relative entropy to the sequences representing B-vectors to measure their similarity/dissimilarity. The numerical results obtained in this study show that the proposed methods leads to meaningful results compared with competitors such as Clustal W. Nature Publishing Group 2017-04-10 /pmc/articles/PMC5385872/ /pubmed/28393857 http://dx.doi.org/10.1038/srep46237 Text en Copyright © 2017, The Author(s) http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Article Yu, Lulu Zhang, Yusen Gutman, Ivan Shi, Yongtang Dehmer, Matthias Protein Sequence Comparison Based on Physicochemical Properties and the Position-Feature Energy Matrix |
title | Protein Sequence Comparison Based on Physicochemical Properties and the Position-Feature Energy Matrix |
title_full | Protein Sequence Comparison Based on Physicochemical Properties and the Position-Feature Energy Matrix |
title_fullStr | Protein Sequence Comparison Based on Physicochemical Properties and the Position-Feature Energy Matrix |
title_full_unstemmed | Protein Sequence Comparison Based on Physicochemical Properties and the Position-Feature Energy Matrix |
title_short | Protein Sequence Comparison Based on Physicochemical Properties and the Position-Feature Energy Matrix |
title_sort | protein sequence comparison based on physicochemical properties and the position-feature energy matrix |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5385872/ https://www.ncbi.nlm.nih.gov/pubmed/28393857 http://dx.doi.org/10.1038/srep46237 |
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