从基因调节网络中剖析可逆和不可逆的单细胞状态过渡
Daniel A Ramirez1,2, Mingyang Lu3,4
1Center for Theoretical Biological Physics, Northeastern University, Boston, MA, 02115, USA.
Molecular systems biology
|February 9, 2026
概括
我们开发了一种新的计算方法,即使用跨细胞相关性 (STICCC) 的状态过渡推断,以利用基因表达数据预测细胞状态过渡. STICCC揭示了基因调节网络如何驱动这些动态细胞变化.
科学领域:
- 计算生物学 计算生物学
- 系统生物学 系统生物学
- 基因组学就是基因组学.
背景情况:
- 了解细胞状态转换在生物学中至关重要.
- 基因调节机制控制着这些动态过程.
- 现有的方法,如伪时间和RNA速度提供有限的见解.
研究的目的:
- 开发一种用于预测细胞状态转换的新型计算方法.
- 在单细胞分辨率下推断可逆和不可逆的细胞命运决定.
- 为了将基因调节相互作用与系统动态联系起来.
主要方法:
- 使用跨细胞相关性 (STICCC) 方法进行状态过渡推断.
- 利用单细胞基因表达数据和基因调控相互作用.
- 利用基因表达时间延迟推断过去和未来的状态.
主要成果:
- STICCC准确地预测了细胞状态的转变.
- 推断向量场捕捉了吸引力盆地和不可逆转的流量.
- 揭示了网络相互作用对细胞命运决定的影响.
结论:
- STICCC提供了超越伪时间和RNA速度的补充见解.
- 该方法增强了对细胞状态转换中的基因调节的理解.
- STICCC是研究动态生物系统的一个有价值的工具.
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