English(EN) CytoWave: Perturbation-Centric Pretraining for Single-Cell Response Prediction

CytoWave框架增强单细胞基因扰动响应预测

作者 PulseAugur 编辑部 · [1 个来源] · 2026-11-02 00:00

研究人员开发了CytoWave，一个旨在提高基因扰动后单细胞基因表达变化预测能力的新预训练框架。该方法解决了现有方法面临的泛化挑战，这些方法由于实验条件和生物背景的差异，在不同数据集和物种之间常常表现不佳。CytoWave采用两阶段训练过程：首先，通过在未扰动细胞上进行掩码基因表达恢复来学习参考细胞状态；其次，利用控制状态和扰动信号预测扰动基因表达，并纳入对比目标以对齐潜在表示。评估表明CytoWave在预测细胞响应方面表现有效且一致。 AI

影响该框架通过提高预测基因修饰细胞响应的准确性，有望推动药物发现和基因功能研究。

排序理由该条目描述了一篇关于特定生物预测任务新颖框架的科学论文。[lever_c_demoted from research: ic=1 ai=1.0]

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Hugging Face Daily Papers TIER_1 English(EN) · 2026-11-02 00:00

CytoWave：以扰动为中心的单细胞反应预测预训练

Predicting gene expression under perturbations from single-cell data is a fundamental task for modeling cellular responses, with applications in discovering gene function and designing therapeutics. However, existing methods often struggle to generalize across datasets due to dif…

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CytoWave：以扰动为中心的单细胞反应预测预训练

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