通过对基于物理模型的贝叶斯优化来逆向工程形态生成
bioRxiv : the preprint server for biology
|September 4, 2023
概括
我们使用高斯过程回归 (GPR) 开发了一个贝叶斯优化框架,通过从成像数据推断细胞力分布来预测器官形状. 这种方法成功逆向工程形态发生并确定影响器官发育的关键机械因素.
科学领域:
- 发展生物学 发展生物学
- 系统生物学 系统生物学
- 计算生物学 计算生物学
背景情况:
- 器官的形状和大小由复杂的细胞信号和机械相互作用来决定.
- 预测器官生成需要了解细胞内和细胞间的力量,但校准基于物理的模型是具有挑战性的.
- 系统和合成生物学旨在确定器官发育的最佳相互作用.
结论:
- 该框架准确地从成像数据中逆向工程器官形态发生.
- 它提供了关于表皮细胞发育和疾病的机械基础的见解.
- 该方法可扩展到任何器官系统,适用于实时控制多细胞系统.
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