Wenxing Li

The paper examines how different amino acid substitutions at the same KIF1A residue lead to distinct clinical and molecular outcomes in KIF1A-associated neurological disorders.

DeltaSplice predicts splicing-altering mutations and alternative splicing from genomic sequences, outperforming existing methods and identifying disease-related variants in neurodevelopmental disorders.

Scm6A is a machine learning method for single-cell m6A quantification, validated against m6A-seq and showing strong correlation in T-cells and disease samples.

The paper reports clinical phenotypes and longitudinal adaptive function in KIF1A-associated neurological disorder and correlates them with computational predictions of genotype severity.

The paper identifies a specific CD8+ T cell phenotype in severe COVID-19 linked to Th17 response and immunothrombosis using multi-omics data.

The paper predicts anti-HIV compounds and identifies novel human targets for anti-HIV therapy using a prediction tool and enrichment analysis.

The paper develops a web server to predict anti-HIV activity of compounds and identifies 7 approved drugs repurposed as anti-HIV agents.