Zhenlong Wang

The paper creates a single-cell atlas of amniote brains to study cell type diversification and identifies species-specific gene expression patterns and novel cell subtypes.

CLCluster uses contrastive learning with multi-omics data to cluster cancer subtypes, showing improved performance over existing methods and identifying AS events linked to patient survival.

The paper introduces iHypoxia, a database compiling protein expression dynamics under hypoxia across mammals, revealing enriched drug targets and PTMs.

dSCOPE predicts sequence segments critical for liquid-liquid phase separation (SCOPEs) using a random forest model trained on curated experimental data, showing enrichment in post-translational modifications and cancer mutations.