贝叶斯推断的癌细胞的表型可塑性基于动态模型的时间细胞比例数据的贝叶斯推断
Shuli Chen1,2, Yuman Wang2, Da Zhou2
1School of Mathematics, Sun Yat-sen University, Guangzhou, Guangdong, China.
Biometrical journal. Biometrische Zeitschrift
|April 29, 2025
概括
我们开发了一个贝叶斯统计框架,使用时间数据检测癌细胞的可塑性. 这种方法量化了癌症干细胞和非干癌细胞之间的动态相互转换,这对于理解瘤发育至关重要.
科学领域:
- 在瘤学瘤学.
- 生物统计学 生物统计学
- 计算生物学 计算生物学
背景情况:
- 癌症组织表现出层次组织,癌症干细胞驱动瘤生长.
- 癌细胞的可塑性,干细胞和非干细胞之间的相互转化,具有显著的兴趣,但难以检测.
- 了解癌细胞的可塑性对于开发有效的癌症疗法至关重要.
研究的目的:
- 提出一个新的贝叶斯统计框架来推断癌细胞的现型可塑性.
- 利用癌症干细胞比例的时间数据来量化细胞动态.
- 提供一种强大的方法来分析经验数据中的癌细胞可塑性.
主要方法:
- 开发了一个随机模型来捕捉动态细胞行为.
- 应用贝叶斯分析来仔细检查从科尔莫戈罗夫前置方程中衍生的动量方程.
- 在非线性普通微分方程模型中引入了一种改进的欧勒法,用于参数估计.
主要成果:
- 广泛的模拟验证了拟议方法的有效性.
- 该框架成功推断了癌细胞的表型可塑性.
- 应用于SW620结肠癌细胞系数据,结果与实验发现一致.
结论:
- 提出的贝叶斯框架有效量化了癌细胞的可塑性.
- 这种方法为癌症研究中的时间数据分析提供了有价值的工具.
- 研究结果支持这种方法在辨别和测量瘤中动态细胞相互转换中的实用性.
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