在细胞命运规范过程中增长的动态景观和统计极限
1Princeton University, Joseph Henry Laboratories of Physics, Princeton, New Jersey 08544, USA.
Physical review. E
|August 1, 2025
概括
这项研究使用动态潜力景观模型细胞分化,揭示了在特定权衡下增长最大化策略. 它建立了一个数学框架,用于理解细胞群体生长和命运规范.
科学领域:
- 系统生物学 系统生物学
- 理论生物学的理论生物学.
- 计算生物学是一种计算生物学.
背景情况:
- 多细胞生物中的基因调节网络是复杂的,需要可解释的低维模型.
- 沃丁顿的潜在景观比喻将细胞分化视为梯度流,但其数学精度仍在争论中.
研究的目的:
- 通过数学来研究瓦丁顿关于细胞分化的潜在景观比喻是精确的限制.
- 模拟单个细胞的受控生长,形成具有特定细胞状态分布的群体.
主要方法:
- 连接随机控制理论与最佳运输.
- 在通用增长控制权权衡下分析增长最大化的监管策略.
- 开发一个框架来计算监管策略和增长曲线.
主要成果:
- 增长最大化的监管策略可以用时间依赖的潜在景观来描述.
- 一个尖的边界是指一个人群达到目标分布和大小所需的时间.
- 该框架允许在增长和差异化模型中计算监管策略和增长曲线.
结论:
- 这项研究为瓦丁顿细胞分化的潜在景观模型提供了一个数学精确的框架.
- 它将不平衡热力学,细胞决策和基于机器学习运输的采样方法联系在一起.
- 这些发现提供了关于优化细胞生长和实现特定细胞命运分布的见解.
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