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Comprehensive evaluations on five single-cell perturbation datasets demonstrate that URFPert out-performs state-of-the-art methods in unseen perturbation regimes, providing a powerful tool for interpreting.
Comprehensive evaluations on five single-cell perturbation datasets demonstrate that URFPert outperforms state-of-the-art methods in unseen perturbation regimes, providing a powerful tool for interpreting regulatory mechanisms.
Experimental results show that DeMixPert effectively captures heterogeneous single-cell perturbation responses and achieves superior performance across unseen-perturbation settings.
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