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Alignment-free similarity analysis for protein sequences based on fuzzy integral
Sequence comparison is an essential part of modern molecular biology research. In this study, we estimated the parameters of Markov chain by considering the frequencies of occurrence of the all possible amino acid pairs from each alignment-free protein sequence. These estimated Markov chain paramete...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6391537/ https://www.ncbi.nlm.nih.gov/pubmed/30808983 http://dx.doi.org/10.1038/s41598-019-39477-8 |
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author | Saw, Ajay Kumar Tripathy, Binod Chandra Nandi, Soumyadeep |
author_facet | Saw, Ajay Kumar Tripathy, Binod Chandra Nandi, Soumyadeep |
author_sort | Saw, Ajay Kumar |
collection | PubMed |
description | Sequence comparison is an essential part of modern molecular biology research. In this study, we estimated the parameters of Markov chain by considering the frequencies of occurrence of the all possible amino acid pairs from each alignment-free protein sequence. These estimated Markov chain parameters were used to calculate similarity between two protein sequences based on a fuzzy integral algorithm. For validation, our result was compared with both alignment-based (ClustalW) and alignment-free methods on six benchmark datasets. The results indicate that our developed algorithm has a better clustering performance for protein sequence comparison. |
format | Online Article Text |
id | pubmed-6391537 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-63915372019-03-01 Alignment-free similarity analysis for protein sequences based on fuzzy integral Saw, Ajay Kumar Tripathy, Binod Chandra Nandi, Soumyadeep Sci Rep Article Sequence comparison is an essential part of modern molecular biology research. In this study, we estimated the parameters of Markov chain by considering the frequencies of occurrence of the all possible amino acid pairs from each alignment-free protein sequence. These estimated Markov chain parameters were used to calculate similarity between two protein sequences based on a fuzzy integral algorithm. For validation, our result was compared with both alignment-based (ClustalW) and alignment-free methods on six benchmark datasets. The results indicate that our developed algorithm has a better clustering performance for protein sequence comparison. Nature Publishing Group UK 2019-02-26 /pmc/articles/PMC6391537/ /pubmed/30808983 http://dx.doi.org/10.1038/s41598-019-39477-8 Text en © The Author(s) 2019 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Saw, Ajay Kumar Tripathy, Binod Chandra Nandi, Soumyadeep Alignment-free similarity analysis for protein sequences based on fuzzy integral |
title | Alignment-free similarity analysis for protein sequences based on fuzzy integral |
title_full | Alignment-free similarity analysis for protein sequences based on fuzzy integral |
title_fullStr | Alignment-free similarity analysis for protein sequences based on fuzzy integral |
title_full_unstemmed | Alignment-free similarity analysis for protein sequences based on fuzzy integral |
title_short | Alignment-free similarity analysis for protein sequences based on fuzzy integral |
title_sort | alignment-free similarity analysis for protein sequences based on fuzzy integral |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6391537/ https://www.ncbi.nlm.nih.gov/pubmed/30808983 http://dx.doi.org/10.1038/s41598-019-39477-8 |
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