Department of Biomedical Engineering, Georgia Institute of Technology and Emory University Medical School, Atlanta, GA 30332-0535, USA.
Pharmacopsychiatry. 2012 May;45 Suppl 1:S22-30. doi: 10.1055/s-0032-1304653. Epub 2012 May 7.
Two grand challenges have been declared as premier goals of computational systems biology. The first is the discovery of network motifs and design principles that help us understand and rationalize why biological systems are organized in the manner we encounter them rather than in a different fashion. The second goal is the development of computational models supporting the investigation of complex systems, in particular, as simulation platforms in personalized medicine and predictive health. Interestingly, most published systems models in biology contain between a handful and a few dozen variables. They are usually too complicated for systemic analyses of organizing principles, but they are at the same time too coarse to allow reliable simulations of diseases. While it may thus appear that the modeling efforts of the past have missed the declared targets of systems biology, we argue in this article that midsized mesoscopic models are excellent starting points for pursuing both goals in computational systems biology.
两个重大挑战被宣布为计算系统生物学的首要目标。第一个是发现网络基元和设计原则，帮助我们理解和合理化为什么生物系统以我们遇到的方式组织，而不是以不同的方式组织。第二个目标是开发支持复杂系统研究的计算模型，特别是作为个性化医学和预测健康的模拟平台。有趣的是，生物学中大多数已发表的系统模型包含几个到几十个变量。它们通常过于复杂，无法进行组织原则的系统分析，但同时又过于粗糙，无法对疾病进行可靠的模拟。因此，尽管过去的建模工作似乎没有达到系统生物学的既定目标，但我们在本文中认为，中等规模的介观模型是追求计算系统生物学这两个目标的绝佳起点。
