Xudong Liu

The paper introduces dropTotal, a method for single-cell total RNA-seq that detects both coding and non-coding transcripts, and applies it to human glioma nuclei to uncover ncRNA-driven regulatory landscapes.

This paper develops a deep-learning framework to predict real-world prevalent SARS-CoV-2 mutations using in silico virus evolution and protein language models, achieving accurate predictions of future dominant mutations.

This paper introduces PepGenWOA, a generative model for bioactive peptide design that outperforms existing methods and enables efficient virtual screening.

The paper uses Mendelian randomization and FUMA to identify genetic variants and genes potentially involved in uterine leiomyoma pathogenesis using GWAS summary data.