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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...

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Detalles Bibliográficos
Autores principales: Yu, Lulu, Zhang, Yusen, Gutman, Ivan, Shi, Yongtang, Dehmer, Matthias
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2017
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.
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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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