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Updated: Jul 10, 2025

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深度学习在癌症表观遗传学中的应用通过DNA甲基化分析

Maryam Yassi^1,2, Aniruddha Chatterjee^2,3, Matthew Parry^1,4

¹Department of Mathematics and Statistics, University of Otago, Dunedin, New Zealand.

Briefings in bioinformatics

|November 20, 2023

概括

深度学习 (DL) 方法正在彻底改变表观遗传学,特别是癌症的DNA甲基化分析. 本综述探讨了DL在发现癌症生物标志物,分类,归算和生存分析中的应用,使用DNA甲基化和多组数据.

科学领域:

表观遗传学和计算生物学
基因组学和生物信息学
癌症研究癌症研究

背景情况:

基因甲基化是关键的表观遗传调节剂,涉及许多生物过程和疾病,包括癌症.
基因组规模分析技术使得DNA甲基化模式的高通量分析成为可能,为癌症的表观遗传贡献提供了洞察力.
计算方法,特别是深度学习 (DL),对于分析复杂的表观基因组数据至关重要.

结论:

深度学习为通过DNA甲基化分析推进癌症表观遗传学研究提供了强大的工具.
未来的研究应该专注于克服当前DL的局限性,并探索癌症表观基因组学的新应用.
对DNA甲基化的DL驱动的洞察力对改善癌症诊断和治疗具有重大前景.

关键词:

通过DNA甲基化.癌症表观遗传学癌症表观遗传学深度学习是一种深度学习.系统性审查系统性审查

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Epigenetic Regulation

Epigenetic Regulation

Epigenetic changes alter the physical structure of the DNA without changing the genetic sequence and often regulate whether genes are turned on or off. This regulation ensures that each cell produces only proteins necessary for its function. For example, proteins that promote bone growth are not produced in muscle cells. Epigenetic mechanisms play an essential role in healthy development. Conversely, precisely regulated epigenetic mechanisms are disrupted in diseases like cancer.
X-chromosome...