Dong Liu

This paper introduces DeepUMQA-Global, a deep learning framework for estimating protein structure model accuracy, which outperforms existing methods in correlation metrics and consensus rankings.

DeepAssembly2 improves protein complex structure prediction using domain-domain interactions and integrates new features and models to enhance accuracy.

This paper introduces DeepUMQA-PA, a deep learning method to estimate residue-wise quality scores for protein complex models, showing improvements over existing methods on benchmark datasets.

SPDesign designs protein sequences using structural sequence profiles and ultrafast shape recognition, outperforming existing methods in sequence recovery and structural accuracy.

This paper introduces DeepAssembly, a method for predicting multi-domain protein and complex structures using inter-domain interactions, achieving higher accuracy than AlphaFold2 on multi-domain targets.