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理解肾脏疾病:跨物种调控网络的整合。

Understanding kidney disease: toward the integration of regulatory networks across species.

机构信息

Department of Internal Medicine, Division of Nephrology, University of Michigan, Ann Arbor, MI 48109-0680, USA.

出版信息

Semin Nephrol. 2010 Sep;30(5):512-9. doi: 10.1016/j.semnephrol.2010.07.008.

DOI:10.1016/j.semnephrol.2010.07.008
PMID:21044762
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC2989742/
Abstract

Animal models have long been useful in investigating both normal and abnormal human physiology. Systems biology provides a relatively new set of approaches to identify similarities and differences between animal models and human beings that may lead to a more comprehensive understanding of human kidney pathophysiology. In this review, we briefly describe how genome-wide analyses of mouse models have helped elucidate features of human kidney diseases, discuss strategies to achieve effective network integration, and summarize currently available web-based tools that may facilitate integration of data across species. The rapid progress in systems biology and orthology, as well as the advent of web-based tools to facilitate these processes, now make it possible to take advantage of knowledge from distant animal species in targeted identification of regulatory networks that may have clinical relevance for human kidney diseases.

摘要

动物模型在研究正常和异常人类生理学方面一直很有用。系统生物学提供了一组相对较新的方法,可以识别动物模型和人类之间的相似之处和差异,从而更全面地了解人类肾脏生理学。在这篇综述中,我们简要描述了全基因组分析小鼠模型如何帮助阐明人类肾脏疾病的特征,讨论了实现有效网络整合的策略,并总结了目前可用的基于网络的工具,这些工具可能有助于跨物种整合数据。系统生物学和同源性的快速发展,以及促进这些过程的基于网络的工具的出现,使得现在有可能利用来自遥远动物物种的知识,有针对性地识别可能对人类肾脏疾病具有临床相关性的调节网络。