Squidiff:使用扩散模型预测细胞发育和对干扰的反应
Siyu He1,2,3, Yuefei Zhu1, Daniel Naveed Tavakol1
1Department of Biomedical Engineering, Columbia University, New York, NY, USA.
Nature methods
|November 3, 2025
概括
新的扩散模型Squidiff预测了细胞在分化,基因扰动和药物反应期间的细胞转录组变化. 这个工具有助于理解细胞命运和疾病机制.
科学领域:
- 计算生物学 计算生物学
- 基因组学就是基因组学.
- 系统生物学 系统生物学
背景情况:
- 单细胞测序揭示了细胞异质性和对刺激的反应.
- 跨细胞类型的转录组变化和疾病机制的映射是具有挑战性的.
研究的目的:
- 介绍Squidiff,一个基于扩散模型的生成框架.
- 在各种环境条件下预测不同细胞类型的转录组变化.
- 促进在体查和假设生成用于细胞命运决定.
主要方法:
- 使用基于扩散模型的生成框架 (Squidiff).
- 集成的连续解读和语义特征学习.
- 将模型应用于细胞分化,基因扰动和药物反应预测.
主要成果:
- 在多个生物场景中证明了Squidiff的稳健性.
- 成功模拟了血管有机体发育和细胞对刺激的反应.
- 通过时间和条件,实现了高分辨率的转录组景观的预测.
结论:
- 鱼使得分子景观和细胞状态过渡的片选.
- 促进生物研究的快速假设生成.
- 提供了关于细胞命运决定的监管原则的见解.
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