推断细胞分化动力学与未观察到的祖先.
William Howard-Snyder1, Richard Zhang2, Henri Schmidt1
1Dept. of Computer Science, Princeton University, Princeton; 08544 NJ, USA.
bioRxiv : the preprint server for biology
|December 22, 2025
概括
TROUPE从血统树推断出细胞分化的地图,克服了当前方法的局限性. 这个框架准确地模拟了细胞生长和转变动态,即使是未观察到的原始细胞类型.
科学领域:
- 发展生物学 发展生物学
- 计算生物学 计算生物学
- 系统生物学 系统生物学
背景情况:
- 细胞分化地图对于理解发育至关重要,但难以确定.
- 单细胞谱系追踪提供了细胞分裂史,但不是直接的分化事件.
- 推断分化图的现有方法存在局限性,包括不切实际的假设和无法处理未观察到的细胞类型.
研究的目的:
- 引入TROUPE,一种基于概率的新框架,用于推断细胞分化和生长动态.
- 通过允许未观察到的原始细胞类型和细胞类型特定率来解决当前方法的局限性.
- 提供一个高效的算法来估计过渡和增长率,并为未观察到的类型提供一个模型选择方案.
主要方法:
- 开发了TROUPE,一种基于概率的框架,利用生物学动机的强度约束.
- 实施了一种高效的算法,用于对过渡和增长率的最大概率估计.
- 设计了一个模型选择方案,以确定未观察到的细胞类型的数量.
主要成果:
- 在模拟中,TROUPE准确地恢复了过渡和生长速度,超过了以前的方法,特别是未观察到的细胞类型.
- 该框架应用于哺乳动物树干状结构 (TLS) 的开发.
- 在标准和扰乱条件下,TROUPE计算了合理的自我更新和差异化率.
结论:
- TROUPE提供了一种强大的方法,可以从血统树推断细胞分化和生长动态.
- 该框架有效地处理未被观察到的原始细胞类型,推进发育生物学研究.
- TROUPE提供了关于细胞在发育过程中的命运决定的宝贵见解,适用于各种生物系统.
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