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相关概念视频

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Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
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Cell size is a significant factor impacting cellular design, function, and fitness. There exists some internal coordination by which cells double their masses before division, thus, achieving homeostasis. Coordination between cell growth and proliferation depends on the checkpoints in between cell cycle phases. Loss of coordination or failure in the checkpoint mechanism can drive the cell to uncontrolled growth and loss of cellular function. Like dividing cells that coordinate cellular growth,...
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Fluid mechanics model studies often utilize scaled-down systems to predict fluid behavior in full-scale environments, such as river flows, dam spillways, and structures interacting with open surfaces. Maintaining Froude number similarity in river models is crucial, as it replicates surface flow features like wave patterns and velocities.
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Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least...
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[细胞过程的数学建模]

Yan Zhu1,2, Jibin Sun1,2,3

  • 1Systems Biology Center, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin 300308, China.

Sheng wu gong cheng xue bao = Chinese journal of biotechnology
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PubMed
概括
此摘要是机器生成的。

本综述巩固了模拟细胞过程的数学模型,这些模型对于推进生物制造和工程生物的发展至关重要. 它详细介绍了理解细胞动态和优化生物生产系统的框架.

关键词:
生物制造 生物制造 生物制造细胞过程是细胞的过程.数学建模的数学建模系统生物学 系统生物学整个细胞模型的全细胞模型.

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科学领域:

  • 生物技术和合成生物学
  • 计算生物学和生物信息学
  • 生物化学工程 生物化学工程

背景情况:

  • 生物制造利用工程细胞进行生物化学品,生物制药,生物燃料和生物材料的可持续生产.
  • 准确的计算模型对于设计和构建有效的工程细胞至关重要.
  • 高通量技术和人工智能的进步使大规模的生物数据采集成为可能,改善了细胞动态的理解.

研究的目的:

  • 系统地审查用于细胞建模的数学框架.
  • 批判性地评估各种数学范式在不同环境中的适用性.
  • 检查开发综合全细胞模型的进展情况.

主要方法:

  • 评估普遍存在的数学范式:网络拓分析,随机过程和动力方程.
  • 对特定细胞过程 (生长,分裂,形态发生,DNA复制,转录,新陈代谢,信号转导,定数感应) 的建模策略的分类.
  • 通过整合多种细胞过程来开发全细胞模型的最新进展.

主要成果:

  • 关于细胞建模的数学框架的总结,包括网络拓,随机过程和运动方程.
  • 关键细胞功能的建模方法的分类.
  • 讨论整合的全细胞建模策略.

结论:

  • 数学模型对于精确模拟细胞过程至关重要,增强对分子机制的理解.
  • 本综述巩固了关于细胞建模的知识,以帮助设计和优化用于生物制造的工程生物.
  • 解决数据稀缺性和计算复杂性等挑战是未来进步的关键.