5 citations · 10 across the 5 of their papers we have counts for
5 papers
Chem2Gen-Bench: Benchmarking Chemical-to-Genetic Translation in Perturbation Response Space
Yuxiang Lin, Ying Chen
Virtual-cell and perturbation models are increasingly used to predict cellular responses for biomedical discovery, but chemical and genetic perturbations are not automatically inte…
HyperST: Hierarchical Hyperbolic Learning for Spatial Transcriptomics Prediction
Chen Zhang, Yilu An, Ying Chen +7
Spatial Transcriptomics (ST) merges the benefits of pathology images and gene expression, linking molecular profiles with tissue structure to analyze spot-level function comprehens…
ST-Align: A Multimodal Foundation Model for Image-Gene Alignment in Spatial Transcriptomics
Yuxiang Lin, Ling Luo, Ying Chen +5
Spatial transcriptomics (ST) provides high-resolution pathological images and whole-transcriptomic expression profiles at individual spots across whole-slide scales. This setting m…
SurvMamba: State Space Model with Multi-grained Multi-modal Interaction for Survival Prediction
Ying Chen, Jiajing Xie, Yuxiang Lin +3
Multi-modal learning that combines pathological images with genomic data has significantly enhanced the accuracy of survival prediction. Nevertheless, existing methods have not ful…
Generalizable Whole Slide Image Classification with Fine-Grained Visual-Semantic Interaction
Hao Li, Ying Chen, Yifei Chen +5
Whole Slide Image (WSI) classification is often formulated as a Multiple Instance Learning (MIL) problem. Recently, Vision-Language Models (VLMs) have demonstrated remarkable perfo…