Yuguang Li

MsPBRsP: Multi-scale Protein Binding Residues Prediction Using Language Model

MsPBRsP predicts protein binding residues using a language model without MSA tools, achieving higher accuracy and faster performance than existing methods.

A Structure-based B-cell Epitope Prediction Model Through Combing Local and Global Features

The paper proposes a deep learning model that combines local and global features to predict B-cell epitopes, showing improved performance over existing methods.

Protein-Protein Interaction Site Prediction Based on Attention Mechanism and Convolutional Neural Networks

This study introduces AttCNNPPISP, a model combining attention mechanisms and CNNs to predict protein-protein interaction sites, showing improved performance over existing methods.

Leveraging Sequential and Spatial Neighbors Information by Using CNNs Linked With GCNs for Paratope Prediction

The paper introduces a method combining CNNs and GCNs to predict paratope residues in antibodies by integrating sequence and spatial information.

A Sequence-based Antibody Paratope Prediction Model Through Combing Local-Global Information and Partner Features

This paper proposes a sequence-based method for predicting antibody paratopes by integrating local-global sequence information and partner antigen features, achieving better performance than existing methods.