CryoNet

CryoNet is a new fully differentiable neural network based method to directly identify the 3D atomic model from cryo-EM density map. CryoNet takes the cryo-EM density map and the corresponding sequence as the input, and learns the matches through the a transformer and generates the full atomic model. CryoNet is fast and accurate. Here we provide a demo to show how it works.

One minute Video Demo.

Welcome to give us feedback CryoNet@cryonet.ai or (Kui Xu: xukui@tsinghua.edu.cn).

Reference

A2-Net: Molecular Structure Estimation from Cryo-EM Density Volumes , Kui Xu, Zhe Wang, Jianping Shi, Hongsheng Li and Qiangfeng Cliff Zhang, (2019), the 33rd AAAI Conference on Artificial Intelligence (AAAI), 33, 1230-1237