ScGraphTrans, a graph neural network framework that integrates functional state pseudo-labels, graph structure learning, and graph domain adaptation to improve both cell type annotation and communication inference, is proposed, offering insights into biomarker discovery and therapeutic strategies.
Yue-Chao Li, Hai-Ru You, Meng-Chao Wei et al.· IEEE transactions on computa...· 0 citations
Vision–language pretrained models, particularly CLIP, have demonstrated remarkable zero-shot transfer capabilities across various image-level tasks, catalyzing the advancement of open-vocabulary semantic segmentation (OVSS) in remote sensing (RS). However, the direct deployment of CLIP to the RS domain is inherently co...
Jiayuan Li, Zhen Wang, Xiao Sun et al.· IEEE Transactions on Geoscie...· 0 citations
Experiments on three cross-patient scRNA-seq data sets demonstrate that PathoGraph achieves stable annotation performance across 32 directed reference-to-query transfer tasks, showing competitive and stable performance compared with representative marker-based, correlation-based, and model-based annotation methods.
Yue C. Li, Mengmeng Wei, Xinfei Wang et al.· Journal of Chemical Informat...· 0 citations
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