Zobrazeno 1 - 10
of 148
pro vyhledávání: '"Li, Shaoning"'
Autor:
Wang, Yusong, Cheng, Chaoran, Li, Shaoning, Ren, Yuxuan, Shao, Bin, Liu, Ge, Heng, Pheng-Ann, Zheng, Nanning
Geometric graph neural networks (GNNs) have emerged as powerful tools for modeling molecular geometry. However, they encounter limitations in effectively capturing long-range interactions in large molecular systems. To address this challenge, we intr
Externí odkaz:
http://arxiv.org/abs/2409.17622
Designing novel proteins that bind to small molecules is a long-standing challenge in computational biology, with applications in developing catalysts, biosensors, and more. Current computational methods rely on the assumption that the binding pose o
Externí odkaz:
http://arxiv.org/abs/2409.12080
Autor:
Li, Shaoning, Li, Mingyu, Wang, Yusong, He, Xinheng, Zheng, Nanning, Zhang, Jian, Heng, Pheng-Ann
Investigating conformational landscapes of proteins is a crucial way to understand their biological functions and properties. AlphaFlow stands out as a sequence-conditioned generative model that introduces flexibility into structure prediction models
Externí odkaz:
http://arxiv.org/abs/2407.12053
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 and properties. To address exploration inefficiency, emerging enhance
Externí odkaz:
http://arxiv.org/abs/2405.00751
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 given molecule on PCQM4Mv2 dataset. In the competition, we designed two
Externí odkaz:
http://arxiv.org/abs/2211.12791
Autor:
Wang, Yusong, Li, Shaoning, He, Xinheng, Li, Mingyu, Wang, Zun, Zheng, Nanning, Shao, Bin, Liu, Tie-Yan, Wang, Tong
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 property prediction, their applications, such as drug discovery and mol
Externí odkaz:
http://arxiv.org/abs/2210.16518
Anomaly event detection is crucial for critical infrastructure security(transportation system, social-ecological sector, insurance service, government sector etc.) due to its ability to reveal and address the potential cyber-threats in advance by ana
Externí odkaz:
http://arxiv.org/abs/2104.08761
Autor:
Li, Yangyang, Ji, Yipeng, Li, Shaoning, He, Shulong, Cao, Yinhao, Li, Xiong, Shi, Jun, Yang, Yangchao, Liu, Yifeng
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 GNN-based detectors to reveal the anomalous users. However, the increa
Externí odkaz:
http://arxiv.org/abs/2104.06095
Publikováno v:
In Science of the Total Environment 10 January 2024 907
Publikováno v:
In Agriculture, Ecosystems and Environment 1 February 2025 378