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Xi Hu^1,2,3, Yuwei Shi^1,2,3, Suk Hang Cheng^1,2,3

¹Centre for Novostics, Hong Kong Science Park, Pak Shek Kok, Hong Kong SAR, China.

Communications biology

|April 14, 2025

概括

一个新的混合人工智能模型,HK模型2,通过单分子测序显著改善了对DNA基基修饰的检测,例如使用5-甲基细胞素. 这种多功能工具增强了癌症等疾病的液体活检应用.

科学领域:

计算生物学计算生物学
基因组学就是基因组学.
人工智能在医学中的应用

背景情况:

之前的工作引入了整体运动模型 (HK模型1),一个卷积神经网络 (CNN) 用于通过单分子实时测序 (SMRT) 来检测5-甲基素 (5mC).
对于检测DNA表观遗传修饰的更准确和多功能方法的需求对于推进诊断和理解生物过程至关重要.

研究的目的:

通过将CNN与变压器层集成来开发一个改进的AI模型 (HK模型2),以改进DNA基基修饰检测.
用SMRT测序评估HK模型2在检测5-甲基细胞因子 (5mC),5-基甲基细胞因子 (5hmC) 和N6-甲基亚丁素 (6mA) 的性能.
评估HK模型2在临床应用中的实用性,特别是通过无细胞DNA (cfDNA) 分析检测肝细胞癌 (HCC).

主要方法:

构建一个混合深度学习模型 (HK模型2),结合卷积神经网络 (CNN) 和变压器架构.
使用SMRT测序数据进行性能评估,重点关注接收器运行特征曲线 (AUC) 下的区域,以检测基调更改.
应用HK模型2分析cfDNA中的5mC模式用于肝细胞癌检测和cfDNA末端分析中的6mA模式.

主要成果:

在5mC检测中,HK模型2实现了0.99的显著改善的AUC,而之前的HK模型1的AUC为0.91.
该模型成功检测到其他基基修饰,包括5-基甲基细胞素 (5hmC) 和N6-甲基氨酸 (6mA).
对cfDNA的分析显示,使用5mC模式检测肝细胞癌患者的AUC为0.97. 6mA检测促进了cfDNA末端和染色质结构的分析.

结论:

香港模型2代表了使用SMRT测序的AI驱动DNA基基修饰检测的实质性进步.
该模型的多功能性使其适用于各种表观遗传分析和液体活检诊断,包括癌症检测.
香港模型2增强了SMRT测序对各种基因组和表观基因组研究以及临床应用的实用性.

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