Multiplying insights from perturbation experiments: predicting new perturbation combinations
Graphical Abstract 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 p...
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| Format: | Article |
| Language: | English |
| Published: |
Springer Nature
2023-05-01
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| Series: | Molecular Systems Biology |
| Online Access: | https://doi.org/10.15252/msb.202311667 |
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