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相关概念视频

Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...
Generation Time01:22

Generation Time

Bacterial generation time, the period required for a bacterial population to double during its exponential growth phase, serves as a critical measure of microbial growth dynamics under optimal conditions. This parameter varies significantly across bacterial species and can be influenced by factors such as temperature, pH, and the availability of nutrients. For example, Escherichia coli can achieve a generation time of approximately 20 minutes, while Mycobacterium tuberculosis exhibits a much...

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相关实验视频

Updated: Jun 25, 2026

Live Imaging Followed by Single Cell Tracking to Monitor Cell Biology and the Lineage Progression of Multiple Neural Populations
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从单细胞基因组学数据的轨迹推断,使用过程时间模型.

Meichen Fang1, Gennady Gorin1,2, Lior Pachter1,3

  • 1Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, California, United States of America.

PLoS computational biology
|January 21, 2025
PubMed
概括
此摘要是机器生成的。

我们介绍了Chronocell,这是一种从单细胞转录组数据推断生物过程时间的新方法. 这种方法提供了一个生物物理上有意义的替代 pseudotime,改善动态洞察细胞过程.

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科学领域:

  • 单细胞生物学 单细胞生物学
  • 计算生物学是一种计算生物学.
  • 系统生物学 系统生物学

背景情况:

  • 单细胞转录学捕捉了细胞状态,但使用"伪时间"对细胞进行排序缺乏物理意义.
  • 现有的方法难以处理离散的细胞群和连续的细胞状态转换.

研究的目的:

  • 从单细胞数据中推断"处理时间"的原则建模方法.
  • 介绍Chronocell,一个用于生物物理轨迹推断的计算工具.
  • 提供一种将轨迹推断和集群结合的方法.

主要方法:

  • 使用生物物理模型制定细胞状态转换.
  • 推断隐性变量代表生物物理过程中的时间.
  • 实现可识别参数推断的Chronocell模型.

主要成果:

  • 时代细胞成功地在连续和离散细胞状态之间进行插曲.
  • 对各种数据集的分析揭示了在过程时间的不同细胞分布.
  • 降解率的参数估计与代谢标记数据保持一致.

结论:

  • 克罗诺细胞为分析单细胞动态提供了一个生物物理上有意义的框架.
  • 该方法有助于评估数据集的适用性和理解生物时间.
  • 准确的过程时间推断取决于数据集质量和模型评估.