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首页> 外文期刊>Progress in Biophysics and Molecular Biology: An International Review Journal >On the limitations of standard statistical modeling in biological systems: A full Bayesian approach for biology
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On the limitations of standard statistical modeling in biological systems: A full Bayesian approach for biology

机译:关于标准统计学模型在生物系统中的局限性:生物学的完整贝叶斯方法

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摘要

One of the most important scientific challenges today is the quantitative and predictive understanding of biological function. Classical mathematical and computational approaches have been enormously successful in modeling inert matter, but they may be inadequate to address inherent features of biological systems. We address the conceptual and methodological obstacles that lie in the inverse problem in biological systems modeling. We introduce a full Bayesian approach (FBA), a theoretical framework to study biological function, in which probability distributions are conditional on biophysical information that physically resides in the biological system that is studied by the scientist
机译:当今最重要的科学挑战之一是对生物学功能的定量和预测性理解。经典的数学和计算方法在对惰性物质进行建模方面已经取得了巨大的成功,但它们可能不足以解决生物系统的固有特征。我们解决了生物系统建模逆问题中的概念和方法上的障碍。我们介绍了完整的贝叶斯方法(FBA),这是一个研究生物学功能的理论框架,其中概率分布取决于科学家实际研究的生物系统中存在的生物物理信息

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