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Two Dimensional Yau-Hausdorff Distance with Applications on Comparison of DNA and Protein Sequences
Comparing DNA or protein sequences plays an important role in the functional analysis of genomes. Despite many methods available for sequences comparison, few methods retain the information content of sequences. We propose a new approach, the Yau-Hausdorff method, which considers all translations an...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4575136/ https://www.ncbi.nlm.nih.gov/pubmed/26384293 http://dx.doi.org/10.1371/journal.pone.0136577 |
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author | Tian, Kun Yang, Xiaoqian Kong, Qin Yin, Changchuan He, Rong L. Yau, Stephen S.-T. |
author_facet | Tian, Kun Yang, Xiaoqian Kong, Qin Yin, Changchuan He, Rong L. Yau, Stephen S.-T. |
author_sort | Tian, Kun |
collection | PubMed |
description | Comparing DNA or protein sequences plays an important role in the functional analysis of genomes. Despite many methods available for sequences comparison, few methods retain the information content of sequences. We propose a new approach, the Yau-Hausdorff method, which considers all translations and rotations when seeking the best match of graphical curves of DNA or protein sequences. The complexity of this method is lower than that of any other two dimensional minimum Hausdorff algorithm. The Yau-Hausdorff method can be used for measuring the similarity of DNA sequences based on two important tools: the Yau-Hausdorff distance and graphical representation of DNA sequences. The graphical representations of DNA sequences conserve all sequence information and the Yau-Hausdorff distance is mathematically proved as a true metric. Therefore, the proposed distance can preciously measure the similarity of DNA sequences. The phylogenetic analyses of DNA sequences by the Yau-Hausdorff distance show the accuracy and stability of our approach in similarity comparison of DNA or protein sequences. This study demonstrates that Yau-Hausdorff distance is a natural metric for DNA and protein sequences with high level of stability. The approach can be also applied to similarity analysis of protein sequences by graphic representations, as well as general two dimensional shape matching. |
format | Online Article Text |
id | pubmed-4575136 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-45751362015-09-25 Two Dimensional Yau-Hausdorff Distance with Applications on Comparison of DNA and Protein Sequences Tian, Kun Yang, Xiaoqian Kong, Qin Yin, Changchuan He, Rong L. Yau, Stephen S.-T. PLoS One Research Article Comparing DNA or protein sequences plays an important role in the functional analysis of genomes. Despite many methods available for sequences comparison, few methods retain the information content of sequences. We propose a new approach, the Yau-Hausdorff method, which considers all translations and rotations when seeking the best match of graphical curves of DNA or protein sequences. The complexity of this method is lower than that of any other two dimensional minimum Hausdorff algorithm. The Yau-Hausdorff method can be used for measuring the similarity of DNA sequences based on two important tools: the Yau-Hausdorff distance and graphical representation of DNA sequences. The graphical representations of DNA sequences conserve all sequence information and the Yau-Hausdorff distance is mathematically proved as a true metric. Therefore, the proposed distance can preciously measure the similarity of DNA sequences. The phylogenetic analyses of DNA sequences by the Yau-Hausdorff distance show the accuracy and stability of our approach in similarity comparison of DNA or protein sequences. This study demonstrates that Yau-Hausdorff distance is a natural metric for DNA and protein sequences with high level of stability. The approach can be also applied to similarity analysis of protein sequences by graphic representations, as well as general two dimensional shape matching. Public Library of Science 2015-09-18 /pmc/articles/PMC4575136/ /pubmed/26384293 http://dx.doi.org/10.1371/journal.pone.0136577 Text en © 2015 Tian et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Tian, Kun Yang, Xiaoqian Kong, Qin Yin, Changchuan He, Rong L. Yau, Stephen S.-T. Two Dimensional Yau-Hausdorff Distance with Applications on Comparison of DNA and Protein Sequences |
title | Two Dimensional Yau-Hausdorff Distance with Applications on Comparison of DNA and Protein Sequences |
title_full | Two Dimensional Yau-Hausdorff Distance with Applications on Comparison of DNA and Protein Sequences |
title_fullStr | Two Dimensional Yau-Hausdorff Distance with Applications on Comparison of DNA and Protein Sequences |
title_full_unstemmed | Two Dimensional Yau-Hausdorff Distance with Applications on Comparison of DNA and Protein Sequences |
title_short | Two Dimensional Yau-Hausdorff Distance with Applications on Comparison of DNA and Protein Sequences |
title_sort | two dimensional yau-hausdorff distance with applications on comparison of dna and protein sequences |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4575136/ https://www.ncbi.nlm.nih.gov/pubmed/26384293 http://dx.doi.org/10.1371/journal.pone.0136577 |
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