Lin Xu Lab

Dr. Lin Xu is an Assistant Professor in the Peter O’Donnell Jr. School of Public Health and the Department of Pediatrics at UT Southwestern Medical Center. With a Ph.D. in Biostatistics and Bioinformatics from Cornell University, he has developed expertise in the integrated analysis of high-dimensional datasets, machine learning, Bayesian modeling, and bioinformatics algorithms. His postdoctoral training expanded his expertise to include clinical medicine and cancer biology.

His lab has developed multiple bioinformatics algorithms and deep learning models to identify new disease genes and therapeutic targets (e.g., Xu et al. Cell Reports (2019), Huang et al. Nature (2020), Lu et al. Nature Machine Intelligence (2022), Chai et al. Nature Medicine (2022), Takahiko et al. Science Translational Medicine (2022) (Cover Story), Shi et al. Cancer Cell (2022), Lebek et al. Science (2023), Xu et al. Nature Communications (2023), Zhu et al. Cancer Cell (2023), Zhang et al. Journal of Clinical Investigation (2023), He et al. Nature Communications (2023), Yu et al. Nature Communications (2023), Santos et al. Nature Communications (2023), Li et al. Nature Communications (2023), Wei et al. Cell (2023), Hernandez et al. PNAS (2024), Hu L et al. Mol Cell (2024), Eglenen-Polat et al. Nature Communications (2024), Lin CC et al. Nature Communications (2024), Xu L. et al. Nature Communications (2024), Venkateswaran N. Nature Communications (2024)). His lab’s research has been published in a series of high-impact journals, including Nature, Science, Cell, Nature Medicine, Cancer Cell, Molecular Cell, Elife, PNAS, Nature Machine Intelligence, Nature Communications, Nature Metabolism, Science Translational Medicine, Science Advance, Genes & Development, Cell Reports, Journal of Clinical Investigation, Cancer Research, Circulation, Circulation Research, and Developmental Cell. Since establishing his lab at UT Southwestern in November 2021, he has published 71 research papers, with 11 as co-/corresponding authors.

With extensive experience in data science, his research was funded from various funding sources, including the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), National Cancer Institute (NCI), National Heart, Lung, and Blood Institute (NHLBI), National Human Genome Research Institute (NHGRI), National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS), Cancer Prevention and Research Institute of Texas (CPRIT), U.S. Department of Defense (DoD), Hyundai Foundation, Children’s Cancer Fund, Sam Day Foundation, Rally Foundation, and Andrew McDonough B+ Foundation.