Yinghao Cao

This study introduces PreCSenM, a machine learning model that quantifies cellular senescence and identifies HDAC inhibitors as senescence inducers in lung adenocarcinoma.

SMART improves formula assignment in spatial metabolomics by using a database and regression model, achieving 92.4% accuracy in mouse embryo imaging.

SCSA automatically annotates cell types in scRNA-seq data using a score model combining DEGs and marker confidence, achieving high precision in real datasets.

This study presents the first high-quality genome assembly of Antirrhinum majus, revealing evolutionary relationships and genetic architectures of complex traits.