Computational blueprints for cell fate programming

doi:10.1016/j.stemcr.2026.102929

2026-05-28

Pengyi Yang *

DOI：10.1016/j.stemcr.2026.102929

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细胞命运编程在疾病建模、药物发现和再生医学中的应用。基础研究建立了分化方案，但其可扩展性受组合复杂性的限制。计算方法实现了细胞注释、网络推断和轨迹分析，并已用于优先筛选细胞命运编程中的转录因子和小分子，尽管其在方案设计中的前瞻性应用仍不均衡。单细胞与空间组学、扰动筛选和深度学习拓展了预测范围，同时引入了领域漂移、可解释性和可重复性等挑战。在此，我将这些方法综合为实用计算蓝图，嵌入细胞命运编程的迭代设计-测试-学习流水线中。

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期刊

Stem Cell Reports

IF:

5.1

论文数:

2.8K

被引数:

1.1W

机构

the university of sydney

学者数:

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被引数: 0

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