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 Lu1,2
1Center for Theoretical Biological Physics, Northeastern University, Boston, MA 02115, USA.
bioRxiv : the preprint server for biology
|September 11, 2024
概括
我们开发了一种新的计算方法,STICCC,使用基因表达数据来预测细胞状态过渡. 这种方法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:
- 细胞状态转换是生物过程的基础.
- 了解管理这些转型的监管机制至关重要.
- 目前用于分析细胞动态的现有方法存在局限性.
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) 方法开发了状态过渡推断.
- 利用单细胞基因表达数据和基因调控相互作用.
- 杆基因表达时间延迟,以推断过去和未来的细胞状态.
主要成果:
- 使用矢量场,STICCC准确地预测细胞状态转换.
- 该方法捕捉了细胞动态中的吸引和不可逆转流动的盆地.
- STICCC提供了关于网络相互作用如何影响细胞命运决策的见解.
结论:
- STICCC提供了对伪时间和RNA速度方法的补充见解.
- 该方法增强了我们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.
关键词:
基因调控网络 (GRN) 是一种基因调控网络.RNA的速度RNA的速度吸引力的盆地吸引力.细胞状态过渡的转变.一个不可逆转的过渡期.一个单细胞的RNA-seqq.系统生物学 系统生物学时间延迟时间延迟更多相关视频
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