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Bioreactor Controls-III01:22

Bioreactor Controls-III

Strain improvement is a foundational strategy in industrial microbiology aimed at maximizing microbial productivity, particularly because natural isolates typically yield commercially valuable products in very low concentrations. Although optimizing the culture medium and environmental conditions can improve yields, these adjustments are inherently limited by the organism’s genetic potential. As a result, the focus shifts toward genetic modifications to enhance biosynthetic capacity. The...
Production of Alcohol01:27

Production of Alcohol

Continuous fermentation is a key strategy in industrial ethanol production, particularly when efficiency, scalability, and high yields are essential. This approach allows for uninterrupted operation and optimized resource utilization. The primary feedstock, corn starch, undergoes enzymatic hydrolysis facilitated by α-amylase and glucoamylase. These enzymes break down the starch into fermentable sugars such as glucose, which are readily assimilated by fermentative microorganisms.Fermentation...

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相关实验视频

Updated: Jun 3, 2026

ODELAY: A Large-scale Method for Multi-parameter Quantification of Yeast Growth
11:19

ODELAY: A Large-scale Method for Multi-parameter Quantification of Yeast Growth

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人工蜂群算法用于估计酵母发酵途径的动力参数.

Ahmad Muhaimin Ismail1, Muhammad Akmal Remli2,3, Yee Wen Choon2,3

  • 1Artificial Intelligence and Bioinformatics Research Group, Faculty of Computing, Universiti Teknologi Malaysia, 81310 Skudai, Johor, Malaysia.

Journal of integrative bioinformatics
|June 21, 2023
PubMed
概括

准确的动力参数对于系统生物学模型至关重要. 人工蜂群 (ABC) 算法有效地估计了Saccharomyces cerevisiae发酵途径的这些参数,提高了模拟的准确性.

关键词:
人工蜂群算法的人工蜂群算法人工智能的人工智能是人工智能.生物信息学是一种生物信息学.数据科学数据科学发酵途径的发酵途径参数估计的参数估计.

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科学领域:

  • 系统生物学 系统生物学
  • 代谢工程是代谢工程.
  • 计算生物学 计算生物学

背景情况:

  • 准确的运动参数对于模拟系统生物学中的体内生物过程至关重要.
  • 对于复杂的生物模型的参数估计,如Saccharomyces cerevisiae发酵途径,由于模型的非线性和无法直接测量运动参数而具有挑战性.

研究的目的:

  • 提出和评估人工蜂群 (ABC) 算法,用于估计Saccharomyces cerevisiae发酵途径中的动力参数.
  • 为了获得更准确的动力参数值,以改进体内过程的模拟.

主要方法:

  • 使用了人工蜂群 (ABC) 算法,这是一种以自然为灵感的优化技术.
  • 应用了ABC算法来估计Saccharomyces cerevisiae发酵途径中一个关键代谢物的六个参数.
  • 将ABC算法的性能与其他估计算法的性能进行比较.

主要成果:

  • 与其他估计算法相比,ABC算法表现出卓越的性能.
  • 由ABC估计的动力参数值对于模拟模型来说更准确.
  • 大多数估计的动力参数与实验数据密切匹配.

结论:

  • 人工蜂群 (ABC) 算法是复杂生物模型中参数估计的有效工具.
  • 使用ABC精确的动力参数估计提高了Saccharomyces cerevisiae发酵途径系统生物学模拟的可靠性.
  • 这种方法可以导致更精确地理解和优化代谢过程.