Network Biology: Exploring Methylation Features in Cancer through Machine Learning

Despite the growing understanding of DNA methylation’s role in cancer biology, many existing studies focus on analyzing individual methylation sites or predefined gene sets, leaving the interactions between co-methylated regions largely unexplored. In this study, we apply a network-based approach to

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Publication Details

Published
2025-01-01
DOI
https://doi.org/10.4108/eai.21-11-2024.2354642
Primary Topic
Bioinformatics and Genomic Networks
Type
article
Field-Weighted Citation Impact
0.00

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article

Network Biology: Exploring Methylation Features in Cancer through Machine Learning

Yao Sun, Zihan Wang, Hongji Zhu, Shanghua Jing
Bioinformatics and Genomic Networks
article

Network Biology: Exploring Methylation Features in Cancer through Machine Learning

Yao Sun, Zihan Wang, Hongji Zhu, Shanghua Jing
article en

Abstract

Despite the growing understanding of DNA methylation’s role in cancer biology, many existing studies focus on analyzing individual methylation sites or predefined gene sets, leaving the interactions between co-methylated regions largely unexplored. In this study, we apply a network-based approach to

University of Cambridge
Zero hunger
Openalex Percentile: Top 95%
Bioinformatics and Genomic Networks
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Network Biology: Exploring Methylation Features in Cancer through Machine Learning — Yao Sun, Zihan Wang, et al. · (2025) | TGRS Research Map | TGRS