贝叶斯网络与不良结果途径 (AOP) 网络之间的联系以及如何使用它来预测药物毒性
Dong Wang1, Ayako Suzuki2, Weida Tong1
1Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, AR, USA.
Drug discovery today
|April 5, 2025
概括
不良结果路径 (AOPs) 在数学上与贝叶斯网络 (BNs) 相一致. 纳入BN属性简化了毒性模型,提高了药物诱导肝损伤评估的效率.
科学领域:
- 计算毒理学计算毒理学
- 系统生物学 系统生物学
- 药理学 药理学是指药理学的学科.
背景情况:
- 负面结果路径 (AOP) 和贝叶斯网络 (BNs) 分享有针对性的非循环图 (DAG) 表示.
- 缺乏对AOP网络与BNs一致性的实证验证.
- 关键的BN属性,如马尔科夫毯子,在AOP框架中未得到充分利用.
研究的目的:
- 为了验证AOP网络和BNs之间的数学一致性.
- 探索这种一致性对毒性建模的影响.
- 为了证明将BN物业集成到AOPs中的好处.
主要方法:
- 对AOP网络和BN数学结构进行比较分析.
- 将贝叶斯网络原则应用于AOPs.
- 关于药物诱导的肝毒性的案例研究.
主要成果:
- 在AOP网络和BNs之间确认了数学一致性.
- 证明了纳入BN属性简化了AOP模型.
- 展示了用于毒性预测的增强模型效率.
结论:
- 在数学上,AOP网络相当于BNs.
- 整合BN属性优化了AOPs用于毒性建模.
- 这种整合提供了一种更有效的方法来理解化学风险.
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