From the Dorothy M. Davis Heart and Lung Research Institute (D.G., T.J.H., L.E.W.).
The Ohio State University Wexner Medical Center, Columbus; Department of Biomedical Engineering, College of Engineering (D.G., T.J.H.).
Circ Res. 2018 May 25;122(11):1496-1498. doi: 10.1161/CIRCRESAHA.118.313003.
Animal models provide powerful tools for examining human disease; however, translation of findings from these models to human patients is often challenging. To this end, we discuss modern tools to support the process of selecting and validating animal models with relevance to humans. We draw from data mining and computational modeling approaches to examine how large datasets may be leveraged to identify suitable models with the greatest translational potential.
动物模型为研究人类疾病提供了强有力的工具；然而，将这些模型的研究结果转化为人类患者往往具有挑战性。为此，我们讨论了支持选择和验证与人类相关的动物模型的现代工具。我们借鉴数据挖掘和计算建模方法，研究如何利用大型数据集来识别具有最大转化潜力的合适模型。
