Foundation models offer a promising paradigm for modeling spatial transcriptomics, but capturing tissue context over cellular graphs makes training at scale challenging. We introduce spaGFM, a graph foundation model that serializes cellular neighborhoods through random walks to generate transformer-compatible represent...
Yu Zhong, Fei He, Xiao-Jie Jin et al.· Research Square· 0 citations
Multi-omics technologies, coupled with AI technologies, have the potential to enable the systematic investigation of complex cancer microbiome biology by uncovering informative patterns and associations across complementary datasets. Here, we review existing and emerging cancer microbiome data, discuss the development,...
Yu-Han Sun, Olivia J. Cheng, A. Ma et al.· Genome Biology· 0 citations
Metastasis remains the leading cause of cancer-related mortality, yet predicting future metastasis is a major clinical challenge due to the lack of validated biomarkers and effective assessment methods. Here, we present EmitGCL, a deep-learning framework that accurately predicts future metastasis and its corresponding...
Xiaoying Wang, Maoteng Duan, Anthony J. Snyder et al.· Nature Communications· 0 citations
Metastasis remains the leading cause of cancer-related mortality, yet predicting future metastasis is a major clinical challenge due to the lack of validated biomarkers and effective assessment methods. Here, we present EmitGCL, a deep-learning framework that accurately predicts future metastasis and its corresponding...
Xiaoying Wang, Maoteng Duan, Po-Lan Su et al.· bioRxiv· 0 citations
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