Multiplying insights from perturbation experiments: predicting new perturbation combinations

被引：1
|
作者：
Welch, Joshua [1 ]
机构：
[1] Univ Michigan, Ann Arbor, MI 48109 USA
来源：
MOLECULAR SYSTEMS BIOLOGY | 2023年 / 19卷 / 06期
关键词：
D O I：
10.15252/msb.202311667
中图分类号：
Q5 [生物化学]; Q7 [分子生物学];
学科分类号：
071010 ; 081704 ;
摘要：
Experimentally exploring the effect of all perturbation combinations is not feasible. In their recent study, Theis and colleagues (Lotfollahi et al, 2023) present an approach that uses deep generative models to predict the effects of new perturbations from high‐throughput single perturbation experiments.[graphic not available: see fulltext]
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