Shijie Xu

PRIME is a deep learning framework that predicts metal-binding sites in proteins by integrating evolutionary and structural signals, achieving high accuracy across various metal ions.

This paper introduces pKALM, a deep learning model for rapid and accurate prediction of protein pKa values, achieving high speed and performance across various residues and termini.

PsiPartition improves genomic data partitioning using parameterized sorting indices and Bayesian optimization, outperforming existing methods on simulated and empirical datasets.

The paper introduces IDP-PLM, a method for predicting intrinsically disordered proteins using protein language models without relying on multiple sequence alignments, achieving state-of-the-art performance.