Suppr超能文献

案例研究:机理网络模型在系统毒理学中的作用

Case study: the role of mechanistic network models in systems toxicology.

作者信息

Hoeng Julia, Talikka Marja, Martin Florian, Sewer Alain, Yang Xiang, Iskandar Anita, Schlage Walter K, Peitsch Manuel C

机构信息

Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland.

Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland.

出版信息

Drug Discov Today. 2014 Feb;19(2):183-92. doi: 10.1016/j.drudis.2013.07.023. Epub 2013 Aug 9.

Abstract

Twenty first century systems toxicology approaches enable the discovery of biological pathways affected in response to active substances. Here, we briefly summarize current network approaches that facilitate the detailed mechanistic understanding of the impact of a given stimulus on a biological system. We also introduce our network-based method with two use cases and show how causal biological network models combined with computational methods provide quantitative mechanistic insights. Our approach provides a robust comparison of the transcriptional responses in different experimental systems and enables the identification of network-based biomarkers modulated in response to exposure. These advances can also be applied to pharmacology, where the understanding of disease mechanisms and adverse drug effects is imperative for the development of efficient and safe treatment options.

摘要

21世纪的系统毒理学方法能够发现活性物质作用下受影响的生物途径。在此,我们简要总结当前的网络方法,这些方法有助于深入理解给定刺激对生物系统的影响机制。我们还通过两个应用案例介绍了我们基于网络的方法,并展示了因果生物网络模型与计算方法如何结合以提供定量的机制见解。我们的方法对不同实验系统中的转录反应进行了有力比较,并能够识别因暴露而受到调节的基于网络的生物标志物。这些进展也可应用于药理学领域,在该领域,对疾病机制和药物不良反应的理解对于开发高效且安全的治疗方案至关重要。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验