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An Improved Binary Differential Evolution Algorithm to Infer Tumor Phylogenetic Trees
Tumourigenesis is a mutation accumulation process, which is likely to start with a mutated founder cell. The evolutionary nature of tumor development makes phylogenetic models suitable for inferring tumor evolution through genetic variation data. Copy number variation (CNV) is the major genetic mark...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5723949/ https://www.ncbi.nlm.nih.gov/pubmed/29279850 http://dx.doi.org/10.1155/2017/5482750 |
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author | Liang, Ying Liao, Bo Zhu, Wen |
author_facet | Liang, Ying Liao, Bo Zhu, Wen |
author_sort | Liang, Ying |
collection | PubMed |
description | Tumourigenesis is a mutation accumulation process, which is likely to start with a mutated founder cell. The evolutionary nature of tumor development makes phylogenetic models suitable for inferring tumor evolution through genetic variation data. Copy number variation (CNV) is the major genetic marker of the genome with more genes, disease loci, and functional elements involved. Fluorescence in situ hybridization (FISH) accurately measures multiple gene copy number of hundreds of single cells. We propose an improved binary differential evolution algorithm, BDEP, to infer tumor phylogenetic tree based on FISH platform. The topology analysis of tumor progression tree shows that the pathway of tumor subcell expansion varies greatly during different stages of tumor formation. And the classification experiment shows that tree-based features are better than data-based features in distinguishing tumor. The constructed phylogenetic trees have great performance in characterizing tumor development process, which outperforms other similar algorithms. |
format | Online Article Text |
id | pubmed-5723949 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-57239492017-12-26 An Improved Binary Differential Evolution Algorithm to Infer Tumor Phylogenetic Trees Liang, Ying Liao, Bo Zhu, Wen Biomed Res Int Research Article Tumourigenesis is a mutation accumulation process, which is likely to start with a mutated founder cell. The evolutionary nature of tumor development makes phylogenetic models suitable for inferring tumor evolution through genetic variation data. Copy number variation (CNV) is the major genetic marker of the genome with more genes, disease loci, and functional elements involved. Fluorescence in situ hybridization (FISH) accurately measures multiple gene copy number of hundreds of single cells. We propose an improved binary differential evolution algorithm, BDEP, to infer tumor phylogenetic tree based on FISH platform. The topology analysis of tumor progression tree shows that the pathway of tumor subcell expansion varies greatly during different stages of tumor formation. And the classification experiment shows that tree-based features are better than data-based features in distinguishing tumor. The constructed phylogenetic trees have great performance in characterizing tumor development process, which outperforms other similar algorithms. Hindawi 2017 2017-11-27 /pmc/articles/PMC5723949/ /pubmed/29279850 http://dx.doi.org/10.1155/2017/5482750 Text en Copyright © 2017 Ying Liang et al. https://creativecommons.org/licenses/by/4.0/ 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 Liang, Ying Liao, Bo Zhu, Wen An Improved Binary Differential Evolution Algorithm to Infer Tumor Phylogenetic Trees |
title | An Improved Binary Differential Evolution Algorithm to Infer Tumor Phylogenetic Trees |
title_full | An Improved Binary Differential Evolution Algorithm to Infer Tumor Phylogenetic Trees |
title_fullStr | An Improved Binary Differential Evolution Algorithm to Infer Tumor Phylogenetic Trees |
title_full_unstemmed | An Improved Binary Differential Evolution Algorithm to Infer Tumor Phylogenetic Trees |
title_short | An Improved Binary Differential Evolution Algorithm to Infer Tumor Phylogenetic Trees |
title_sort | improved binary differential evolution algorithm to infer tumor phylogenetic trees |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5723949/ https://www.ncbi.nlm.nih.gov/pubmed/29279850 http://dx.doi.org/10.1155/2017/5482750 |
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