Biosciences, TNO Quality of Life, Zeist, The Netherlands.
PLoS Comput Biol. 2009 Nov;5(11):e1000554. doi: 10.1371/journal.pcbi.1000554. Epub 2009 Nov 26.
The use of computational modeling and simulation has increased in many biological fields, but despite their potential these techniques are only marginally applied in nutritional sciences. Nevertheless, recent applications of modeling have been instrumental in answering important nutritional questions from the cellular up to the physiological levels. Capturing the complexity of today's important nutritional research questions poses a challenge for modeling to become truly integrative in the consideration and interpretation of experimental data at widely differing scales of space and time. In this review, we discuss a selection of available modeling approaches and applications relevant for nutrition. We then put these models into perspective by categorizing them according to their space and time domain. Through this categorization process, we identified a dearth of models that consider processes occurring between the microscopic and macroscopic scale. We propose a "middle-out" strategy to develop the required full-scale, multilevel computational models. Exhaustive and accurate phenotyping, the use of the virtual patient concept, and the development of biomarkers from "-omics" signatures are identified as key elements of a successful systems biology modeling approach in nutrition research--one that integrates physiological mechanisms and data at multiple space and time scales.
计算建模和模拟在许多生物领域的应用日益增多,但尽管这些技术具有潜力,但在营养科学中它们的应用却微乎其微。然而,最近的建模应用在回答从细胞到生理水平的重要营养问题方面发挥了重要作用。要捕捉当今重要营养研究问题的复杂性,就需要建模在考虑和解释广泛不同时空尺度的实验数据时真正具有综合性。在这篇综述中,我们讨论了一些与营养相关的可用建模方法和应用。然后,我们根据它们的空间和时间域对这些模型进行分类,从而更深入地了解这些模型。通过这个分类过程,我们发现缺乏考虑微观和宏观尺度之间发生的过程的模型。我们提出了一种“从中间到两端”的策略,以开发所需的全尺度、多层次计算模型。全面准确的表型分析、虚拟患者概念的使用以及从“组学”特征开发生物标志物被确定为营养研究中系统生物学建模方法成功的关键要素——这种方法将多个时空尺度的生理机制和数据整合在一起。