most citedA polarity-aware multi-relational model for the signed interaction prediction in biological networks

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5 papers

cs.LG20261 cited

A polarity-aware multi-relational model for the signed interaction prediction in biological networks

Yize Zhou, Meijie Wang, Lun Yu

Predicting signed interactions in biological networks is crucial for understanding drug mechanisms and facilitating drug repurposing. While deep graph models have demonstrated succ…

cs.LG2026

Safe Multitask Molecular Graph Networks for Vapor Pressure and Odor Threshold Prediction

Shuang Wu, Meijie Wang, Lun Yu

We investigate two important tasks in odor-related property modeling: Vapor Pressure (VP) and Odor Threshold (OP). To evaluate the model's out-of-distribution (OOD) capability, we…

cs.LG2025

BMDetect: A Multimodal Deep Learning Framework for Comprehensive Biomedical Misconduct Detection

Yize Zhou, Jie Zhang, Meijie Wang +1

Academic misconduct detection in biomedical research remains challenging due to algorithmic narrowness in existing methods and fragmented analytical pipelines. We present BMDetect,…

cs.LG2025

LengthLogD: A Length-Stratified Ensemble Framework for Enhanced Peptide Lipophilicity Prediction via Multi-Scale Feature Integration

Shuang Wu, Meijie Wang, Lun Yu

Peptide compounds demonstrate considerable potential as therapeutic agents due to their high target affinity and low toxicity, yet their drug development is constrained by their lo…

cs.LG2025

Can artificial intelligence predict clinical trial outcomes?

Shuyi Jin, Lu Chen, Hongru Ding +2

This study evaluates the performance of large language models (LLMs) and the HINT model in predicting clinical trial outcomes, focusing on metrics including Balanced Accuracy, Matt…