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

机译:案例研究:机械网络模型在系统毒理学中的作用

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Twenty first century systems toxicology approaches enable the discover)/ 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.
机译:二十世纪的系统毒理学方法使人们能够发现/响应活性物质而受到影响的生物途径。在这里,我们简要概述了当前的网络方法,这些方法有助于对给定刺激对生物系统的影响进行详细的机械理解。我们还将介绍基于网络的方法以及两个用例,并说明因果生物学网络模型与计算方法的结合如何提供定量的机理见解。我们的方法可以对不同实验系统中的转录反应进行可靠的比较,并可以识别响应暴露而调制的基于网络的生物标记。这些进展也可以应用于药理学,在这种药理学中,对于疾病机理和药物不良作用的了解对于开发有效和安全的治疗方法至关重要。

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