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Applying knowledge-driven mechanistic inference to toxicogenomics.
Toxicology in Vitro ( IF 3.2 ) Pub Date : 2020-05-06 , DOI: 10.1016/j.tiv.2020.104877
Ignacio J Tripodi 1 , Tiffany J Callahan 2 , Jessica T Westfall 3 , Nayland S Meitzer 4 , Robin D Dowell 5 , Lawrence E Hunter 6
Affiliation  

When considering toxic chemicals in the environment, a mechanistic, causal explanation of toxicity may be preferred over a statistical or machine learning-based prediction by itself. Elucidating a mechanism of toxicity is, however, a costly and time-consuming process that requires the participation of specialists from a variety of fields, often relying on animal models. We present an innovative mechanistic inference framework (MechSpy), which can be used as a hypothesis generation aid to narrow the scope of mechanistic toxicology analysis. MechSpy generates hypotheses of the most likely mechanisms of toxicity, by combining a semantically-interconnected knowledge representation of human biology, toxicology and biochemistry with gene expression time series on human tissue. Using vector representations of biological entities, MechSpy seeks enrichment in a manually curated list of high-level mechanisms of toxicity, represented as biochemically- and causally-linked ontology concepts. Besides predicting the canonical mechanism of toxicity for many well-studied compounds, we experimentally validated some of our predictions for other chemicals without an established mechanism of toxicity. This mechanistic inference framework is an advantageous tool for predictive toxicology, and the first of its kind to produce a mechanistic explanation for each prediction. MechSpy can be modified to include additional mechanisms of toxicity, and is generalizable to other types of mechanisms of human biology.

中文翻译:

将知识驱动的机械推理应用于毒理学。

在考虑环境中的有毒化学物质时,对毒​​性的机械因果解释可能比单独基于统计或机器学习的预测更受欢迎。然而,阐明毒性机制是一个昂贵且耗时的过程,需要来自各个领域的专家的参与,通常依赖于动物模型。我们提出了一种创新的机械推理框架 (MechSpy),可用作假设生成辅助工具,以缩小机械毒理学分析的范围。MechSpy 通过将人类生物学、毒理学和生物化学的语义互连知识表示与人体组织的基因表达时间序列相结合,生成最可能的毒性机制的假设。使用生物实体的向量表示,MechSpy 在手动策划的高级毒性机制列表中寻求丰富,这些机制表示为与生化和因果相关的本体概念。除了预测许多经过充分研究的化合物的典型毒性机制外,我们还通过实验验证了我们对其他化学物质的一些预测,但没有确定的毒性机制。这种机械推理框架是预测毒理学的一个有利工具,也是同类中第一个为每个预测产生机械解释的工具。MechSpy 可以修改为包括额外的毒性机制,并且可以推广到其他类型的人类生物学机制。除了预测许多经过充分研究的化合物的典型毒性机制外,我们还通过实验验证了我们对其他化学物质的一些预测,但没有确定的毒性机制。这种机械推理框架是预测毒理学的一个有利工具,也是同类中第一个为每个预测产生机械解释的工具。MechSpy 可以修改为包括额外的毒性机制,并且可以推广到其他类型的人类生物学机制。除了预测许多经过充分研究的化合物的典型毒性机制外,我们还通过实验验证了我们对其他化学物质的一些预测,但没有确定的毒性机制。这种机械推理框架是预测毒理学的一个有利工具,也是同类中第一个为每个预测产生机械解释的工具。MechSpy 可以修改为包括额外的毒性机制,并且可以推广到其他类型的人类生物学机制。
更新日期:2020-05-06
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