Lei Xie

Ultrafast and Accurate Selection of High-Quality Protein Complex Models from Large-Scale Prediction

This paper introduces DeepUMQA-Selection, a framework for efficiently selecting high-quality protein complex models from large candidate pools, showing improved performance and speed.

Highly Accurate Estimation of the Fold Accuracy of Protein Structural Models

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.

MViewEMA: Efficient Global Accuracy Estimation for Protein Complex Structural Models Using Multi-View Representation Learning

MViewEMA improves protein complex model accuracy estimation with multi-view representation learning, achieving higher efficiency and performance than previous methods.

Physical-aware model accuracy estimation for protein complex using deep learning method

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.