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Iscience
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March 25, 2024
Exploring an accurate machine learning model to quickly estimate stability of diverse energetic materials
Qiaolin Gou, Jing Liu, Haoming Su, et al.
Journal of Chemical Information and Modeling
|
March 8, 2022
An Interpretable Convolutional Neural Network Framework for Analyzing Molecular Dynamics Trajectories: a Case Study on Functional States for G-Protein-Coupled Receptors
Chuan Li, Jiangting Liu, Jianfang Chen, et al.
Journal of Chemical Information and Modeling
|
August 23, 2022
Correlated RNN Framework to Quickly Generate Molecules with Desired Properties for Energetic Materials in the Low Data Regime
Chuan Li, Chenghui Wang, Ming Sun, et al.
Nature Communications
|
April 11, 2026
LaMGen: LLM-based 3D molecular generation for multi-target drug design
Qun Su, Qiaolin Gou, Hui Zhang, et al.
The Journal of Physical Chemistry Letters
|
June 16, 2025
LumiCharge: Spherical Harmonic Convolutional Networks for Atomic Charge Prediction in Drug Discovery
Qun Su, Hui Zhang, Qiaolin Gou, et al.
Chemical Science
|
February 26, 2025
Robust protein-ligand interaction modeling through integrating physical laws and geometric knowledge for absolute binding free energy calculation
Qun Su, Jike Wang, Qiaolin Gou, et al.
Journal of Chemical Information and Modeling
|
June 18, 2025
ChargeNet: E(3) Equivariant Graph Attention Network for Atomic Charge Prediction
Qiaolin Gou, Qun Su, Jike Wang, et al.
Nature Communications
|
March 7, 2026
A scalable and quantum-accurate foundation model for biomolecular force fields via linearly tensorized quadrangle attention
Qun Su, Kai Zhu, Qiaolin Gou, et al.
Chemical Science
|
December 12, 2024
3DSMILES-GPT: 3D molecular pocket-based generation with token-only large language model
Jike Wang, Hao Luo, Rui Qin, et al.
Journal of the American Chemical Society
|
January 13, 2026
MetalloDock: Decoding Metalloprotein-Ligand Interactions via Physics-Aware Deep Learning for Metalloprotein Drug Discovery
Hui Zhang, Xujun Zhang, Qun Su, et al.
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of 2
Search research articles
Search
Showing results (1-10 of 11) with videos related to
Sort By:
Page
of 2
Iscience
|
March 25, 2024
Exploring an accurate machine learning model to quickly estimate stability of diverse energetic materials
Qiaolin Gou, Jing Liu, Haoming Su, et al.
Journal of Chemical Information and Modeling
|
March 8, 2022
An Interpretable Convolutional Neural Network Framework for Analyzing Molecular Dynamics Trajectories: a Case Study on Functional States for G-Protein-Coupled Receptors
Chuan Li, Jiangting Liu, Jianfang Chen, et al.
Journal of Chemical Information and Modeling
|
August 23, 2022
Correlated RNN Framework to Quickly Generate Molecules with Desired Properties for Energetic Materials in the Low Data Regime
Chuan Li, Chenghui Wang, Ming Sun, et al.
Nature Communications
|
April 11, 2026
LaMGen: LLM-based 3D molecular generation for multi-target drug design
Qun Su, Qiaolin Gou, Hui Zhang, et al.
The Journal of Physical Chemistry Letters
|
June 16, 2025
LumiCharge: Spherical Harmonic Convolutional Networks for Atomic Charge Prediction in Drug Discovery
Qun Su, Hui Zhang, Qiaolin Gou, et al.
Chemical Science
|
February 26, 2025
Robust protein-ligand interaction modeling through integrating physical laws and geometric knowledge for absolute binding free energy calculation
Qun Su, Jike Wang, Qiaolin Gou, et al.
Journal of Chemical Information and Modeling
|
June 18, 2025
ChargeNet: E(3) Equivariant Graph Attention Network for Atomic Charge Prediction
Qiaolin Gou, Qun Su, Jike Wang, et al.
Nature Communications
|
March 7, 2026
A scalable and quantum-accurate foundation model for biomolecular force fields via linearly tensorized quadrangle attention
Qun Su, Kai Zhu, Qiaolin Gou, et al.
Chemical Science
|
December 12, 2024
3DSMILES-GPT: 3D molecular pocket-based generation with token-only large language model
Jike Wang, Hao Luo, Rui Qin, et al.
Journal of the American Chemical Society
|
January 13, 2026
MetalloDock: Decoding Metalloprotein-Ligand Interactions via Physics-Aware Deep Learning for Metalloprotein Drug Discovery
Hui Zhang, Xujun Zhang, Qun Su, et al.
Page
of 2