5 papers
Multi-Scale Protein Structure Modelling with Geometric Graph U-Nets
Chang Liu, Vivian Li, Linus Leong +3
Geometric Graph Neural Networks (GNNs) and Transformers have become state-of-the-art for learning from 3D protein structures. However, their reliance on message passing prevents th…
Omics-scale polymer computational database transferable to real-world artificial intelligence applications
Ryo Yoshida, Yoshihiro Hayashi, Hidemine Furuya +103
Developing large-scale foundational datasets is a critical milestone in advancing artificial intelligence (AI)-driven scientific innovation. However, unlike AI-mature fields such a…
HeFS: Helper-Enhanced Feature Selection via Pareto-Optimized Genetic Search
Yusi Fan, Tian Wang, Zhiying Yan +8
Feature selection is a combinatorial optimization problem that is NP-hard. Conventional approaches often employ heuristic or greedy strategies, which are prone to premature converg…
MolProphecy: Bridging Medicinal Chemists' Knowledge and Molecular Pre-Trained Models via a Multi-Modal Framework
Jianping Zhao, Qiong Zhou, Tian Wang +8
MolProphecy is a human-in-the-loop (HITL) multi-modal framework designed to integrate chemists' domain knowledge into molecular property prediction models. While molecular pre-trai…
DeepSelective: Interpretable Prognosis Prediction via Feature Selection and Compression in EHR Data
Ruochi Zhang, Qian Yang, Xiaoyang Wang +10
The rapid accumulation of Electronic Health Records (EHRs) has transformed healthcare by providing valuable data that enhance clinical predictions and diagnoses. While conventional…