Unsupervisedly Prompting AlphaFold2 for Few-Shot Learning of Accurate Folding Landscape and Protein Structure Prediction

2 code implementations • 20 Aug 2022 • Jun Zhang, Sirui Liu, Mengyun Chen, Haotian Chu, Min Wang, Zidong Wang, Jialiang Yu, Ningxi Ni, Fan Yu, Diqing Chen, Yi Isaac Yang, Boxin Xue, Lijiang Yang, YuAn Liu, Yi Qin Gao

Data-driven predictive methods which can efficiently and accurately transform protein sequences into biologically active structures are highly valuable for scientific research and medical development.

Denoising Few-Shot Learning +2

PSP: Million-level Protein Sequence Dataset for Protein Structure Prediction

2 code implementations • 24 Jun 2022 • Sirui Liu, Jun Zhang, Haotian Chu, Min Wang, Boxin Xue, Ningxi Ni, Jialiang Yu, Yuhao Xie, Zhenyu Chen, Mengyun Chen, YuAn Liu, Piya Patra, Fan Xu, Jie Chen, Zidong Wang, Lijiang Yang, Fan Yu, Lei Chen, Yi Qin Gao

We provide in addition the benchmark training procedure for SOTA protein structure prediction model on this dataset.

Protein Structure Prediction

Deep Reinforcement Learning of Transition States

no code implementations • 13 Nov 2020 • Jun Zhang, Yao-Kun Lei, Zhen Zhang, Xu Han, Maodong Li, Lijiang Yang, Yi Isaac Yang, Yi Qin Gao

Combining reinforcement learning (RL) and molecular dynamics (MD) simulations, we propose a machine-learning approach (RL$^\ddag$) to automatically unravel chemical reaction mechanisms.

reinforcement-learning Reinforcement Learning (RL)

A Perspective on Deep Learning for Molecular Modeling and Simulations

no code implementations • 25 Apr 2020 • Jun Zhang, Yao-Kun Lei, Zhen Zhang, Junhan Chang, Maodong Li, Xu Han, Lijiang Yang, Yi Isaac Yang, Yi Qin Gao

Deep learning is transforming many areas in science, and it has great potential in modeling molecular systems.