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Microbial Growth Measurement: Indirect Methods

Microbial Growth Measurement: Indirect Methods

Estimating microbial growth is essential for understanding population dynamics and environmental adaptations. Indirect methods provide valuable insights by measuring parameters such as turbidity, metabolic activity, and biomass, enabling efficient and reproducible assessments.During exponential growth, microbial cells scatter light proportionally to their biomass, a principle used in turbidity measurements. About one million cells per milliliter produce detectable scattering, which a...

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Updated: Sep 16, 2025

Kinetic Visualization of Single-Cell Interspecies Bacterial Interactions

Kinetic Visualization of Single-Cell Interspecies Bacterial Interactions

Published on: August 5, 2020

将微生物动力学转化为量化反应和可测试的假设,使用Kinbiont.

Fabrizio Angaroni¹, Alberto Peruzzi¹, Edgar Z Alvarenga²

¹Computational Biology Research Centre, Human Technopole, Milan, Italy.

Nature communications

|July 11, 2025

概括

Kinbiont是一个新的开源工具,使用动态模型和机器学习来分析微生物生长数据. 它帮助研究人员了解微生物对环境变化的反应,加速科学发现.

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Saccharomyces cerevisiae Exponential Growth Kinetics in Batch Culture to Analyze Respiratory and Fermentative Metabolism

Saccharomyces cerevisiae Exponential Growth Kinetics in Batch Culture to Analyze Respiratory and Fermentative Metabolism

Published on: September 30, 2018

An In Vitro Single-Molecule Imaging Assay for the Analysis of Cap-Dependent Translation Kinetics

An In Vitro Single-Molecule Imaging Assay for the Analysis of Cap-Dependent Translation Kinetics

Published on: September 15, 2020

相关实验视频

Last Updated: Sep 16, 2025

Kinetic Visualization of Single-Cell Interspecies Bacterial Interactions

Kinetic Visualization of Single-Cell Interspecies Bacterial Interactions

Published on: August 5, 2020

Saccharomyces cerevisiae Exponential Growth Kinetics in Batch Culture to Analyze Respiratory and Fermentative Metabolism

Saccharomyces cerevisiae Exponential Growth Kinetics in Batch Culture to Analyze Respiratory and Fermentative Metabolism

Published on: September 30, 2018

An In Vitro Single-Molecule Imaging Assay for the Analysis of Cap-Dependent Translation Kinetics

An In Vitro Single-Molecule Imaging Assay for the Analysis of Cap-Dependent Translation Kinetics

Published on: September 15, 2020

科学领域:

微生物学微生物学
计算生物学计算生物学
系统生物学系统生物学

背景情况:

量化方法对于了解微生物对环境变化的反应至关重要,解决抗生素耐药性和优化生物生产等挑战.
分析复杂的微生物生长数据集以获得可操作的见解仍然是微生物学中的一个重大障碍.

研究的目的:

介绍Kinbiont,一个开源计算工具,旨在将动态建模与机器学习集成为数据驱动的微生物发现.
为将微生物动力学数据转化为可解释和可测试的假设提供一个框架.

主要方法:

Kinbiont采用了三个模块管道:数据预处理,基于模型的参数推断 (使用用户定义或内置模型),以及可解释的机器学习以进行条件对参数映射.
该工具在各种数据集上进行了基准测试,包括二氧化生长,乙醇生物生产,菌-细菌相互作用和抗生素抑制试验.

主要成果:

基因生物成功分析了各种微生物生长数据集,证明了其多功能性.
该工具自动识别了控制微生物反应的数学关系,正如经典的营养限制实验和抗生素测试所显示的那样.
使用Kinbiont进行的大规模生态毒理学查显示了对环境压力因素的生长阶段特定敏感性.

结论:

Kinbiont有效地将复杂的微生物动力学数据转化为可理解的生物见解.
这个工具作为一个强大的平台,加速研究和现代微生物学假设的生成.
Kinbiont通过将实验条件与推断的生物参数联系起来,促进了数据驱动的发现.