We develop computational and statistical solutions for the analysis of high-dimensional molecular data in various contexts of biomedical research. Our research topics include

• Ultrahigh-dimensional network inference and interpretable integration of multi-omics data in biological experiments and clinical studies

• Harmonizing information between bulk omics data and single cell-level omics data

• Mapping molecular concentration changes between tissues and circulation in biomarker discovery

• Application of sequencing and mass spectrometry-based omics technologies in clinical and food science research

• Development of novel informatics tools for large-scale untargeted and targeted mass spectrometry (MS) data processing in metabolomics and lipidomics

To see examples of our work, check out the CSSB LAB GitHub page!