9 citations · 25 across the 11 of their papers we have counts for
11 papers
Learning the PTM Code through a Coarse-to-Fine, Mechanism-Aware Framework
Jingjie Zhang, Hanqun Cao, Zijun Gao +8
Post-translational modifications (PTMs) form a combinatorial "code" that regulates protein function, yet deciphering this code - linking modified sites to their catalytic enzymes -…
ProteinAE: Protein Diffusion Autoencoders for Structure Encoding
Shaoning Li, Le Zhuo, Yusong Wang +5
Developing effective representations of protein structures is essential for advancing protein science, particularly for protein generative modeling. Current approaches often grappl…
Pretraining a Foundation Model for Small-Molecule Natural Products
Yuheng Ding, Bo Qiang, Shaoning Li +8
Natural products, as metabolites from microorganisms, animals, or plants, exhibit diverse biological activities, making them crucial for drug discovery. Nowadays, existing deep lea…
Neural PM: A Long-Range Interaction Modeling Enhancer for Geometric GNNs
Yusong Wang, Chaoran Cheng, Shaoning Li +5
Geometric graph neural networks (GNNs) have emerged as powerful tools for modeling molecular geometry. However, they encounter limitations in effectively capturing long-range inter…
Design of Ligand-Binding Proteins with Atomic Flow Matching
Junqi Liu, Shaoning Li, Chence Shi +2
Designing novel proteins that bind to small molecules is a long-standing challenge in computational biology, with applications in developing catalysts, biosensors, and more. Curren…
Improving AlphaFlow for Efficient Protein Ensembles Generation
Shaoning Li, Mingyu Li, Yusong Wang +4
Investigating conformational landscapes of proteins is a crucial way to understand their biological functions and properties. AlphaFlow stands out as a sequence-conditioned generat…
Flow: Frame-to-Frame Coarse-grained Molecular Dynamics with SE(3) Guided Flow Matching
Shaoning Li, Yusong Wang, Mingyu Li +4
Molecular dynamics (MD) is a crucial technique for simulating biological systems, enabling the exploration of their dynamic nature and fostering an understanding of their functions…
An ensemble of VisNet, Transformer-M, and pretraining models for molecular property prediction in OGB Large-Scale Challenge @ NeurIPS 2022
Yusong Wang, Shaoning Li, Zun Wang +4
In the technical report, we provide our solution for OGB-LSC 2022 Graph Regression Task. The target of this task is to predict the quantum chemical property, HOMO-LUMO gap for a gi…
ViSNet: an equivariant geometry-enhanced graph neural network with vector-scalar interactive message passing for molecules
Yusong Wang, Shaoning Li, Xinheng He +6
Geometric deep learning has been revolutionizing the molecular modeling field. Despite the state-of-the-art neural network models are approaching ab initio accuracy for molecular p…
Relevance-Aware Anomalous Users Detection in Social Network via Graph Neural Network
Yangyang Li, Yipeng Ji, Shaoning Li +6
Anomalous users detection in social network is an imperative task for security problems. Motivated by the great power of Graph Neural Networks(GNNs), many current researches adopt…
An Anomaly Event Detection Method Based on GNN Algorithm for Multi-data Sources
Yipeng Ji, Jingyi Wang, Shaoning Li +3
Anomaly event detection is crucial for critical infrastructure security(transportation system, social-ecological sector, insurance service, government sector etc.) due to its abili…