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Updated: Jun 19, 2025

Author Spotlight: Alignment of Synchronized Time-Series Data Using the Characterizing Loss of Cell Cycle Synchrony Model for Cross-Experiment Comparisons
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Author Spotlight: Alignment of Synchronized Time-Series Data Using the Characterizing Loss of Cell Cycle Synchrony Model for Cross-Experiment Comparisons

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两者之间的距离:比较随机模型与时间序列数据的算法方法

Brock D Sherlock1,2, Marko A A Boon2, Maria Vlasiou3

  • 1School of Mathematics and Statistics, University of New South Wales, Sydney, NSW, 2052, Australia.

Bulletin of mathematical biology
|July 26, 2024
PubMed
概括

这项研究确定了强大的距离指标,用于将随机模型与实验数据进行比较. 像Wasserstein-1这样的集成距离测量比离散测量更好地用于参数推断和模型验证,特别是在杂的,随时间变化的生物数据中.

关键词:
演变分布之间的距离.距离指标 距离指标多个实验多个实验.时间序列数据数据时间序列数据.

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