PROF. Tao Wang
I run a top computational immunology lab in UT Southwestern Medical Center. Machine learning, statistics, medicine, and biology are the four integral pillars of my interdisciplinary research program. We have been working on mining public and in-house high throughput data to achieve a deeper understanding of the mechanisms of various human diseases, with a heavy emphasis on immunological diseases, and their diagnosis, prognosis, and treatment. These approaches include, for example, modeling of T/B cell antigens and T/B cell receptor sequences (molecular level), profiling immune cell infiltrates in bulk tissues and analyses of single cell profiling (scRNA-seq, spatially resolved transcriptomics, and CyTOF) data (cellular level), and integrative analyses of genomics data with electronic medical record data (patient level). The ultimate goal of our lab is to impact the prognosis and treatment of patients suffering from various diseases, through modeling of high dimensional data, especially genomics data.
Research Interests
Mapping the Functional Landscape of T Cell Receptor Repertoire by Single T Cell Transcriptomics
Learn moreDeep learning-based prediction of the T cell receptor-antigen binding specificity
Learn moreMapping Cellular Interactions from Spatially Resolved Transcriptomics Data
Learn moreSelected Publications
MORE PULICATIONSMapping Cellular Interactions from Spatially Resolved Transcriptomics Data. Nature Methods. 2024.
Netie: Inferring the evolution of neoantigen-T cell interactions in tumors. Nature Methods. 2022 publisher's website
Benisse for Interpreting the B Cell Receptor Repertoire with Single Cell Gene Expression. Nature Machine Intelligence. 2022.
Deep learning-based prediction of the T cell receptor-antigen binding specificity. Nature Machine Intelligence. 2021. publisher's website
Mapping the Functional Landscape of T Cell Receptor Repertoire by Single T Cell Transcriptomics. Nature Methods. 2020. publisher's website
Tumor Neoantigenicity Assessment with CSiN Score Incorporates Clonality and Immunogenicity to Predict Immunotherapy Outcomes. Science Immunology. 2020. publisher's website
News
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