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相关概念视频

Uncertainty: Overview00:59

Uncertainty: Overview

995
In analytical chemistry, we often perform repetitive measurements to detect and minimize inaccuracies caused by both determinate and indeterminate errors. Despite the cares we take, the presence of random errors means that repeated measurements almost never have exactly the same magnitude. The collective difference between these measurements - observed values - and the estimated or expected value is called uncertainty. Uncertainty is conventionally written after the estimated or expected value.
995

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蛋白质结晶模型的In Vitro/In Silico集成不确定性量化方法.

Daniele Pessina1,2, Jorge Calderon De Anda3, Claire Heffernan3

  • 1Department of Chemical Engineering, Imperial College London, London SW7 2AZ, United Kingdom.

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概括

这项研究提出了一种用于蛋白质结晶建模的新方法,提高了准确性并减少了实验. 它通过解决参数估计挑战来增强生物制造的计算模型.

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科学领域:

  • 生物技术是生物技术.
  • 化学工程是化学工程的重要组成部分.
  • 结晶科学 结晶科学

背景情况:

  • 蛋白质结晶是复杂的,阻碍了生物制造过程的强化.
  • 当前的计算模型需要准确的参数估计来进行实验验证.
  • 非线性模型结构和不准确的过程分析技术阻碍了有效的参数估计.

研究的目的:

  • 开发和验证用于抗溶剂批量蛋白质结晶的基于模型的参数化方法.
  • 提高生物工艺开发的计算模型的准确性.
  • 为解决非线性结晶系统参数估计方面的挑战.

主要方法:

  • 开发了一种经过实验验证的,以模型为驱动的,用于批量蛋白质结晶的参数化方法.
  • 采用全球灵敏度分析来确定参数识别能力和最佳测量点.
  • 利用近似贝叶斯计算和蒙特卡洛模拟来估计参数不确定性和传播.

主要成果:

  • 在有限的离线数据下成功估计了批量蛋白质结晶系统的参数.
  • 在新的实验条件下验证了该方法,证明了它的稳定性.
  • 量化参数和输出不确定性,突出了非线性模型特定方法的需要.

结论:

  • 提出的方法提高了蛋白质结晶中的计算模型的可靠性.
  • 准确的参数估计对于通过工艺强化推进生物制造至关重要.
  • 量身定制的方法对于处理非线性系统中的参数不确定性至关重要.