We are a disease-oriented and data-driven computational biology laboratory at The University of Texas at Austin, based in the Department of Biomedical Engineering with affiliations to the Oden Institute for Computational Engineering & Sciences. We develop bioinformatics tools for next-generation sequencing data analysis and machine learning algorithms for large-scale biomedical data interpretation.
Projects
- Develop machine learning algorithms for single-cell data analysis (Nature Biotechnology 2018, 2022; Nature Machine Intelligence 2023; Cell Genomics 2025; Cancer Discovery 2026)
- Tumor progression and treatment resistance (Clinical Cancer Research 2020, 2021; PNAS 2020; Nature Communications 2021)
- Cancer Immunotherapy (Nature 2022)
- Predictive Medicine (Nature Communications 2022)
- Aging (Immunity & Ageing 2024)
Recent News
- 09/2026 A study led by our PhD student Canping Chen on tumor-cell MHC class II in pancreatic ductal adenocarcinoma is accepted by Cancer Immunology Research — a multidisciplinary collaboration running from a clinical trial biopsy observation, through million-cell public data mining, to experimental validation in mouse models.
- 04/2026 scSurvival, our tool for single-cell survival analysis, is published in Cancer Discovery and featured in an NIH News Release.