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在结肠直肠癌器官中基因调节网络的贝叶斯模型

Huijun Gao, Dongxu Lei, Songlin Zhuang

IEEE transactions on cybernetics

|November 12, 2025

概括

这项研究引入了一个新的贝叶斯框架来分析结直肠瘤有机体中的基因表达. 该方法揭示了基因调节网络,为癌症进展和个性化治疗提供了洞察力.

科学领域:

计算生物学计算生物学
基因组学就是基因组学.
癌症研究癌症研究

背景情况:

结肠直肠癌是一个重大的全球健康挑战.
瘤有机体 (瘤体) 是有价值的生物模型,因为它们能够模仿人类组织的复杂性.
由于细胞异质性和时间变化,分析瘤中的基因表达是很困难的.

研究的目的:

开发一个全面的贝叶斯框架来建模结直肠瘤中的基因表达动态.
识别驱动瘤进展的基因调节网络 (GRNs).
用先进的统计方法增强复杂生物系统的分析.

主要方法:

一种非参数的迪里克莱特过程混合模型 (DPMM) 用于通过时间表达模式将基因聚集在一起.
使用Horseshoe+先验的稀疏回归方案用于从聚类基因中构建GRNs.
该框架旨在处理来自瘤发育轨迹的高维基因表达数据.

主要成果:

提出的贝叶斯框架有效地模拟了结直肠瘤中的基因表达动态.
通过构建GRNs,阐明了导致瘤进展的关键调节机制.
该方法在捕捉数据中的复杂,高维关系方面表现强.

结论:

开发的贝叶斯框架为分析瘤中的基因表达提供了一个强大的工具.
获得的见解可以为结直肠癌的个性化治疗策略提供信息.
这项研究强调了贝叶斯方法在解开复杂的生物过程中的有用性.

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