系统生物学方法有助于促进跨物种比较的解释

IF 4.6
Bonnie V. Dougherty, Jason A. Papin
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引用次数: 5

摘要

生物知识从动物模型到人类的翻译是治疗学发展的重要一步,但有效的翻译仍然存在局限性。系统生物学通过数据驱动的模型(如依赖于数据学习模式的方法)和生物过程的机制驱动模型(如药代动力学模型)提供了理解物种之间翻译的局限性的方法。在这里,我们描述了数据驱动和机制驱动的系统生物学方法的最新进展,以更好地理解从动物模型到人类的翻译的局限性。这两种建模方法各有优缺点,但仍然为模型系统和人类之间的转换提供了关键的生物学见解(图1)。所提出的方法不仅识别了不同模式生物之间的差异,而且还提供了识别共享生物标志物和独特生物学见解的机会。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Systems biology approaches help to facilitate interpretation of cross-species comparisons

Translation of biological knowledge from animal models to humans is an important step in the development of therapeutics, but there remain limitations for effective translation. Systems biology offers approaches to understand the limitations for translation between species through data-driven models, such as methods that rely on learning patterns from data, and mechanism-driven models of biological processes, such as pharmacokinetic models. Here, we describe recent advances in both data-driven and mechanism-driven systems biology approaches to better understand limitations to translation from animal models to humans. Both approaches to modeling have their strengths and weaknesses but still provide key biological insight for translating between model systems and humans (Fig. 1). The presented methods not only identify differences between different model organisms but also provide opportunities to identify shared biomarkers and unique biological insight.

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来源期刊
Current opinion in toxicology
Current opinion in toxicology Toxicology, Biochemistry
CiteScore
8.50
自引率
0.00%
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审稿时长
64 days
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