Xiuwen Liu

ProDCoNN-server predicts and designs protein sequences from 3D structures using deep learning models, offering fast and accurate results with visualization tools.

This study estimates the designability of real proteins using a deep neural network model and validates the results with AlphaFold2 and RoseTTAFold.

This paper introduces two deep learning models for protein loop modeling that improve accuracy without relying on multiple sequence alignments.

The paper applies AlphaFold to predict stability changes of engineered proteins and estimates the designability of a real protein structure.