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DV-Curve Representation of Protein Sequences and Its Application

Based on the detailed hydrophobic-hydrophilic(HP) model of amino acids, we propose dual-vector curve (DV-curve) representation of protein sequences, which uses two vectors to represent one alphabet of protein sequences. This graphical representation not only avoids degeneracy, but also has good visu...

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Detalles Bibliográficos
Autores principales: Deng, Wei, Luan, Yihui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4034481/
https://www.ncbi.nlm.nih.gov/pubmed/24899916
http://dx.doi.org/10.1155/2014/203871
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author Deng, Wei
Luan, Yihui
author_facet Deng, Wei
Luan, Yihui
author_sort Deng, Wei
collection PubMed
description Based on the detailed hydrophobic-hydrophilic(HP) model of amino acids, we propose dual-vector curve (DV-curve) representation of protein sequences, which uses two vectors to represent one alphabet of protein sequences. This graphical representation not only avoids degeneracy, but also has good visualization no matter how long these sequences are, and can reflect the length of protein sequence. Then we transform the 2D-graphical representation into a numerical characterization that can facilitate quantitative comparison of protein sequences. The utility of this approach is illustrated by two examples: one is similarity/dissimilarity comparison among different ND6 protein sequences based on their DV-curve figures the other is the phylogenetic analysis among coronaviruses based on their spike proteins.
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spelling pubmed-40344812014-06-04 DV-Curve Representation of Protein Sequences and Its Application Deng, Wei Luan, Yihui Comput Math Methods Med Research Article Based on the detailed hydrophobic-hydrophilic(HP) model of amino acids, we propose dual-vector curve (DV-curve) representation of protein sequences, which uses two vectors to represent one alphabet of protein sequences. This graphical representation not only avoids degeneracy, but also has good visualization no matter how long these sequences are, and can reflect the length of protein sequence. Then we transform the 2D-graphical representation into a numerical characterization that can facilitate quantitative comparison of protein sequences. The utility of this approach is illustrated by two examples: one is similarity/dissimilarity comparison among different ND6 protein sequences based on their DV-curve figures the other is the phylogenetic analysis among coronaviruses based on their spike proteins. Hindawi Publishing Corporation 2014 2014-05-08 /pmc/articles/PMC4034481/ /pubmed/24899916 http://dx.doi.org/10.1155/2014/203871 Text en Copyright © 2014 W. Deng and Y. Luan. https://creativecommons.org/licenses/by/3.0/ 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
Deng, Wei
Luan, Yihui
DV-Curve Representation of Protein Sequences and Its Application
title DV-Curve Representation of Protein Sequences and Its Application
title_full DV-Curve Representation of Protein Sequences and Its Application
title_fullStr DV-Curve Representation of Protein Sequences and Its Application
title_full_unstemmed DV-Curve Representation of Protein Sequences and Its Application
title_short DV-Curve Representation of Protein Sequences and Its Application
title_sort dv-curve representation of protein sequences and its application
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4034481/
https://www.ncbi.nlm.nih.gov/pubmed/24899916
http://dx.doi.org/10.1155/2014/203871
work_keys_str_mv AT dengwei dvcurverepresentationofproteinsequencesanditsapplication
AT luanyihui dvcurverepresentationofproteinsequencesanditsapplication