6 papers
Simulation-to-real transfer learning for infrared spectroscopic chemical sensing and analysis from molecules to complex samples
Yusen Tan, Yixuan Chen, Zheng Fang +8
Infrared (IR) spectroscopy is widely used for chemical sensing, but extracting reliable chemical information from spectra remains challenging. Conventional interpretation is labor-…
A large-scale foundation model enables simulation-to-real adaptation for nuclear magnetic resonance-based molecular structure analysis
Chen Yang, Zheng Fang, Hanyu Sun +7
Nuclear Magnetic Resonance (NMR) spectroscopy is a powerful tool for molecular structure analysis, and spectral artificial intelligence offers great potential for its rapid and aut…
Rethinking Genomic Modeling Through Optical Character Recognition
Hongxin Xiang, Pengsen Ma, Yunkang Cao +4
Recent genomic foundation models largely adopt large language model architectures that treat DNA as a one-dimensional token sequence. However, exhaustive sequential reading is stru…
Enhancing Molecular Property Prediction with Knowledge from Large Language Models
Peng Zhou, Lai Hou Tim, Zhixiang Cheng +4
Predicting molecular properties is a critical component of drug discovery. Recent advances in deep learning, particularly Graph Neural Networks (GNNs), have enabled end-to-end lear…
ImageDDI: Image-enhanced Molecular Motif Sequence Representation for Drug-Drug Interaction Prediction
Yuqin He, Tengfei Ma, Chaoyi Li +6
To mitigate the potential adverse health effects of simultaneous multi-drug use, including unexpected side effects and interactions, accurately identifying and predicting drug-drug…
EDBench: Large-Scale Electron Density Data for Molecular Modeling
Hongxin Xiang, Ke Li, Mingquan Liu +7
Existing molecular machine learning force fields (MLFFs) generally focus on the learning of atoms, molecules, and simple quantum chemical properties (such as energy and force), but…