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Discriminating Origin Tissues of Tumor Cell Lines by Methylation Signatures and Dys-Methylated Rules

文献类型: 外文期刊

作者: Zhang, Shiqi 1 ; Zeng, Tao 3 ; Hu, Bin 4 ; Zhang, Yu-Hang 5 ; Feng, Kaiyan 6 ; Chen, Lei 7 ; Niu, Zhibin 8 ; Li, Jianhao; 1 ;

作者机构: 1.Shanghai Univ, Sch Life Sci, Shanghai, Peoples R China

2.Univ Copenhagen, Dept Biostat, Copenhagen, Denmark

3.Shanghai Res Ctr Brain Sci & Brain Inspired Intel, Shanghai, Peoples R China

4.Guangdong Acad Agr Sci, Inst Anim Sci, State Key Lab Livestock & Poultry Breeding, Guangdong Publ Lab Anim Breeding & Nutr,Guangdong, Guangzhou, Peoples R China

5.Chinese Acad Sci, Shanghai Inst Nutr & Hlth, Shanghai Inst Biol Sci, Shanghai, Peoples R China

6.Guangdong AIB Polytech, Dept Comp Sci, Guangzhou, Peoples R China

7.Shanghai Maritime Univ, Coll Informat Engn, Shanghai, Peoples R China

8.Tianjin Univ, Coll Intelligence & Comp, Tianjin, Peoples R China

关键词: methylation signature; dys-methylated pattern; cell line; rule; classification

期刊名称:FRONTIERS IN BIOENGINEERING AND BIOTECHNOLOGY ( 影响因子:5.89; 五年影响因子:5.973 )

ISSN: 2296-4185

年卷期: 2020 年 8 卷

页码:

收录情况: SCI

摘要: 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.

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