论文标题
衰老的复杂计算模型的潜力
The potential for complex computational models of aging
论文作者
论文摘要
可以量化活生物体衰老期间损伤和失调的逐渐积累。即便如此，衰老过程还是复杂的，并且具有多个相互作用的生理尺度 - 从分子到细胞到整个组织。面对这种复杂性，我们可以通过使用计算模型来显着提高对衰老的理解，以模拟现实的健康轨迹和死亡率。为此，它们必须是系统级模型，这些模型结合了与年龄相关变化的可测量方面之间的相互作用。为了在衰老过程中纳入个体变异性，模型必须是随机的。为了有用，它们也应该具有预测性，因此必须通过大量老龄化个体人群的数据拟合或参数化。从这个角度来看，我们概述了我们去过的地方，我们的身在哪里以及希望与这种衰老计算模型一起使用。我们的重点是数据驱动的系统级模型以及它们在衰老研究中的巨大潜力。
The gradual accumulation of damage and dysregulation during the aging of living organisms can be quantified. Even so, the aging process is complex and has multiple interacting physiological scales -- from the molecular to cellular to whole tissues. In the face of this complexity, we can significantly advance our understanding of aging with the use of computational models that simulate realistic individual trajectories of health as well as mortality. To do so, they must be systems-level models that incorporate interactions between measurable aspects of age-associated changes. To incorporate individual variability in the aging process, models must be stochastic. To be useful they should also be predictive, and so must be fit or parameterized by data from large populations of aging individuals. In this perspective, we outline where we have been, where we are, and where we hope to go with such computational models of aging. Our focus is on data-driven systems-level models, and on their great potential in aging research.
