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Discriminating Origin Tissues of Tumor Cell Lines by Methylation Signatures and Dys-Methylated Rules
DNA methylation is an essential epigenetic modification for multiple biological processes. DNA methylation in mammals acts as an epigenetic mark of transcriptional repression. Aberrant levels of DNA methylation can be observed in various types of tumor cells. Thus, DNA methylation has attracted cons...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7264161/ https://www.ncbi.nlm.nih.gov/pubmed/32528944 http://dx.doi.org/10.3389/fbioe.2020.00507 |
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author | Zhang, Shiqi Zeng, Tao Hu, Bin Zhang, Yu-Hang Feng, Kaiyan Chen, Lei Niu, Zhibin Li, Jianhao Huang, Tao Cai, Yu-Dong |
author_facet | Zhang, Shiqi Zeng, Tao Hu, Bin Zhang, Yu-Hang Feng, Kaiyan Chen, Lei Niu, Zhibin Li, Jianhao Huang, Tao Cai, Yu-Dong |
author_sort | Zhang, Shiqi |
collection | PubMed |
description | DNA methylation is an essential epigenetic modification for multiple biological processes. DNA methylation in mammals acts as an epigenetic mark of transcriptional repression. Aberrant levels of DNA methylation can be observed in various types of tumor cells. Thus, DNA methylation has attracted considerable attention among researchers to provide new and feasible tumor therapies. Conventional studies considered single-gene methylation or specific loci as biomarkers for tumorigenesis. However, genome-scale methylated modification has not been completely investigated. Thus, we proposed and compared two novel computational approaches based on multiple machine learning algorithms for the qualitative and quantitative analyses of methylation-associated genes and their dys-methylated patterns. This study contributes to the identification of novel effective genes and the establishment of optimal quantitative rules for aberrant methylation distinguishing tumor cells with different origin tissues. |
format | Online Article Text |
id | pubmed-7264161 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-72641612020-06-10 Discriminating Origin Tissues of Tumor Cell Lines by Methylation Signatures and Dys-Methylated Rules Zhang, Shiqi Zeng, Tao Hu, Bin Zhang, Yu-Hang Feng, Kaiyan Chen, Lei Niu, Zhibin Li, Jianhao Huang, Tao Cai, Yu-Dong Front Bioeng Biotechnol Bioengineering and Biotechnology DNA methylation is an essential epigenetic modification for multiple biological processes. DNA methylation in mammals acts as an epigenetic mark of transcriptional repression. Aberrant levels of DNA methylation can be observed in various types of tumor cells. Thus, DNA methylation has attracted considerable attention among researchers to provide new and feasible tumor therapies. Conventional studies considered single-gene methylation or specific loci as biomarkers for tumorigenesis. However, genome-scale methylated modification has not been completely investigated. Thus, we proposed and compared two novel computational approaches based on multiple machine learning algorithms for the qualitative and quantitative analyses of methylation-associated genes and their dys-methylated patterns. This study contributes to the identification of novel effective genes and the establishment of optimal quantitative rules for aberrant methylation distinguishing tumor cells with different origin tissues. Frontiers Media S.A. 2020-05-26 /pmc/articles/PMC7264161/ /pubmed/32528944 http://dx.doi.org/10.3389/fbioe.2020.00507 Text en Copyright © 2020 Zhang, Zeng, Hu, Zhang, Feng, Chen, Niu, Li, Huang and Cai. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Bioengineering and Biotechnology Zhang, Shiqi Zeng, Tao Hu, Bin Zhang, Yu-Hang Feng, Kaiyan Chen, Lei Niu, Zhibin Li, Jianhao Huang, Tao Cai, Yu-Dong Discriminating Origin Tissues of Tumor Cell Lines by Methylation Signatures and Dys-Methylated Rules |
title | Discriminating Origin Tissues of Tumor Cell Lines by Methylation Signatures and Dys-Methylated Rules |
title_full | Discriminating Origin Tissues of Tumor Cell Lines by Methylation Signatures and Dys-Methylated Rules |
title_fullStr | Discriminating Origin Tissues of Tumor Cell Lines by Methylation Signatures and Dys-Methylated Rules |
title_full_unstemmed | Discriminating Origin Tissues of Tumor Cell Lines by Methylation Signatures and Dys-Methylated Rules |
title_short | Discriminating Origin Tissues of Tumor Cell Lines by Methylation Signatures and Dys-Methylated Rules |
title_sort | discriminating origin tissues of tumor cell lines by methylation signatures and dys-methylated rules |
topic | Bioengineering and Biotechnology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7264161/ https://www.ncbi.nlm.nih.gov/pubmed/32528944 http://dx.doi.org/10.3389/fbioe.2020.00507 |
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