8 papers
P2P: Cross-View Population Denoising for Unpaired Single-Cell Perturbation Response Prediction
Haojie Yang, Ran Su
AIVC (AI Virtual Cell) is a learned simulator of cellular behavior across conditions. Predicting how a cell population responds transcriptionally to a genetic perturbation is a cor…
MRFlow: Mechanism-Structured Residual Flow Matching for Virtual Cell Perturbation Prediction
Haojie Yang, Ran Su
Predicting cellular responses to chemical and genetic perturbations is a central test for AI virtual cells, yet many single-cell models reduce each condition to an average expressi…
GRIPNet: Gaussian Radial Intensity Prior Guided Architecture for Pulmonary Nodule Detection in CT
Haojie Yang, Ran Su
Lung cancer causes more deaths than any other malignancy, and low-dose CT screening is the main pathway to early diagnosis. That pathway hinges on the smallest lesions, yet nodules…
HERO: Hypothesis-Driven Evidence Retrieval from Omics for Multi-Task Breast Cancer Analysis
Xiangyu Li, Ran Su
Matched multi-omics can improve WSI-based biomarker and prognosis prediction, but most existing pipelines use omics as a paral lel feature stream or textual context rather than as…
GCE-MIL: Faithful and Recoverable Evidence for Multiple Instance Learning in Whole-Slide Imaging
Xiangyu Li, Ran Su
Multiple instance learning (MIL) is the standard approach for whole-slide image (WSI) classification and survival prediction, where attention-based models ag gregate patch features…
Spatial Blindness in Whole-Slide Multiple Instance Learning
Xiangyu Li, Ran Su
Whole-slide MIL models are often called context-aware once graphs, Transform ers, or state-space modules are placed above patch embeddings. We show that this label can be deceptive…
CDI-DTI: A Strong Cross-domain Interpretable Drug-Target Interaction Prediction Framework Based on Multi-Strategy Fusion
Xiangyu Li, Haojie Yang, Kaimiao Hu +3
Accurate prediction of drug-target interactions (DTI) is pivotal for drug discovery, yet existing methods often fail to address challenges like cross-domain generalization, cold-st…
M3ST-DTI: A multi-task learning model for drug-target interactions based on multi-modal features and multi-stage alignment
Xiangyu Li, Ran Su, Liangliang Liu
Accurate prediction of drug-target interactions (DTI) is pivotal in drug discovery. However, existing approaches often fail to capture deep intra-modal feature interactions or achi…