通过使用DoseRider在途径水平上建模omics剂量反应
Pablo Monfort-Lanzas1,2, Johanna M Gostner1, Hubert Hackl2
1Institute of Medical Biochemistry, Biocenter, Medical University Innsbruck, 6020 Innsbruck, Austria.
Computational and structural biotechnology journal
|April 17, 2025
概括
DoseRider是一款新的网络应用程序和R包,用于分析omics数据,以建模剂量反应关系并确定生物暴露极限. 它为复杂曲线引入了趋势变化剂量 (TCD),帮助毒理学和药理学研究.
科学领域:
- 药物遗传学和毒物遗传学
- 计算生物学和生物信息学
- 分子毒理学 分子毒理学
背景情况:
- 对于药理学和毒理学的机制性见解,Omics数据生成至关重要.
- 非线性剂量反应关系需要强大的建模来推断生物暴露极限.
- 目前用于剂量反应建模的工具往往缺乏全面的途径级分析.
研究的目的:
- 介绍DoseRider,一个用于对OMIC数据的剂量反应建模的Web应用程序和R包.
- 为了使基准剂量 (BMD) 在生物途径或特征水平的评估.
- 提出一种趋势变化剂量 (TCD) 的新概念,用于表征复杂的剂量反应效应.
主要方法:
- 开发DoseRider,一个用户友好的Web应用程序和R包.
- 利用通用混合效应模型用于线性和非线性剂量反应建模.
- 集成的多omics数据 (RNA测序,代谢学) 与路径和基因组注释.
- 将DoseRider应用于从双AF (BPAF) 治疗的MCF-7细胞中的RNA测序数据.
主要成果:
- DoseRider成功地分析了定制并提供了跨物种的多omics数据.
- 证明了与BPAF治疗数据的可用性,确定了对雌激素敏感基因的0.2μM的BMD.
- 确定了BPAF的0.003μM的最低趋势变化剂量 (TCD1),表明了早期的生物效应.
结论:
- DoseRider提供了一个全面的平台,用于使用OMIC数据进行剂量反应建模和BMD评估.
- 引入TCD为理解复杂的剂量反应现象提供了一个新的指标.
- DoseRider适用于药物基因组学,毒物基因组学和更广泛的生物研究应用.
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