Schema: metric learning enables interpretable synthesis of heterogeneous single-cell modalities

Schema：度量学习实现了异质单细胞模态的可解释合成.

Mapping single-cell data to reference atlases by transfer learning

通过迁移学习把单细胞数据映射到参考图谱.

Stabilized mosaic single-cell data integration using unshared features

使用不共享特征进行稳定马赛克单细胞数据整合.

SADLN: Self-attention based deep learning network of integrating multi-omics data for cancer subtype recognition

SADLN：整合多组学数据用于癌症亚型识别的自注意力深度学习网络.

Efficient Generation of Paired Single-Cell Multiomics Profiles by Deep Learning

通过深度学习实现成对单细胞多组学谱的高效生成.

ScLinear predicts protein abundance at single-cell resolution

ScLinear预测单细胞分辨率的蛋白质丰度.