I am an Assistant Professor in the Department of Population and Data Sciences, as well as a member of the Quantitative Biomedical Research Center (QBRC) and the Harold C. Simmons Cancer Center at UT Southwestern Medical Center. With training in biostatistics and bioinformatics, I have a good understanding of translational research, developing predictive and prognostic biomarkers, and personalized medicine. My primary statistical expertise is in machine learning, algorithm development for processing next-generation sequencing data, prediction model building, and development of data management system. During my Ph.D. career in the Biostatistics program in Cornell University, I received comprehensive training in integrated analysis of high-dimensional datasets, machine learning, Bayesian modeling and developing bioinformatics algorithms to analyze next-generation sequencing data. During my postdoc career, I received systematic training in clinical medicine. I also have extensive experience on the analysis of clinical trials and epidemiological studies, as well as the development and maintenance of comprehensive databases.
Since I joined UT Southwestern as an Assistant Professor, my research interests are developing bioinformatics algorithms and deep learning models to identify new disease genes and therapeutic targets for human diseases, as well as development and maintenance of data management system for genomic and clinical databases. My lab’s research works have been published in a series of high-impact journals, including Nature, Elife, PNAS, Genes & Development, Cell Reports, Nature Communications, Science Immunology, Cancer Research, Clinical Cancer Research and Developmental Cell.
With extensive experience in data science, I have been the leading PI or co-PI of multiple grants from a variety of funding resources, including the National Cancer Institute (NCI), National Heart, Lung, and Blood Institute (NHLBI), Cancer Prevention and Research Institute of Texas (CPRIT), Hyundai Pediatric Cancer Foundation, Children’s Cancer Fund, Rally Foundation, Dysimmune Diseases Foundation and Andrew McDonough B+ Foundation.
- pediatric cancer, muscle defects, heart diseases, diabetes
- Dynamic Transcriptional Responses to Injury of Regenerative and Non-regenerative Cardiomyocytes Revealed by Single-Nucleus RNA Sequencing.
- Cui M, Wang Z, Chen K, Shah AM, Tan W, Duan L, Sanchez-Ortiz E, Li H, Xu L, Liu N, Bassel-Duby R, Olson EN, Dev. Cell 2020 Mar
- Twist2 amplification in rhabdomyosarcoma represses myogenesis and promotes oncogenesis by redirecting MyoD DNA binding.
- Li S, Chen K, Zhang Y, Barnes SD, Jaichander P, Zheng Y, Hassan M, Malladi VS, Skapek SX, Xu L, Bassel-Duby R, Olson EN, Liu N, Genes Dev. 2019 Apr
- SR-B1 drives endothelial cell LDL transcytosis via DOCK4 to promote atherosclerosis.
- Huang L, Chambliss KL, Gao X, Yuhanna IS, Behling-Kelly E, Bergaya S, Ahmed M, Michaely P, Luby-Phelps K, Darehshouri A, Xu L, Fisher EA, Ge WP, Mineo C, Shaul PW, Nature 2019 Apr
- DIGREM: an integrated web-based platform for detecting effective multi-drug combinations.
- Zhang M, Lee S, Yao B, Xiao G, Xu L, Xie Y Bioinformatics 2018 Oct
- Integrative Bayesian Analysis Identifies Rhabdomyosarcoma Disease Genes.
- Xu L, Zheng Y, Liu J, Rakheja D, Singleterry S, Laetsch TW, Shern JF, Khan J, Triche TJ, Hawkins DS, Amatruda JF, Skapek SX Cell Rep 2018 Jul 24 1 238-251
- as a mediator of rhabdomyosarcoma tumorigenesis.
- Kendall GC, Watson S, Xu L, LaVigne CA, Murchison W, Rakheja D, Skapek SX, Tirode F, Delattre O, Amatruda JF Elife 2018 Jun 7
- Dynamic epistasis for different alleles of the same gene.
- Xu L, Barker B, Gu Z, Proc. Natl. Acad. Sci. U.S.A. 2012 Jun 109 26 10420-5
- Genetic architecture of growth traits revealed by global epistatic interactions.
- Xu L, Jiang H, Chen H, Gu Z, Genome Biol Evol 2011 3 909-14
- Development of a Data Model and Data Commons for Germ Cell Tumors.
- Ci B, Yang DM, Krailo M, Xia C, Yao B, Luo D, Zhou Q, Xiao G, Xu L, Skapek SX, Murray MM, Amatruda JF, Klosterkemper L, Shaikh F, Faure-Conter C, Fresneau B, Volchenboum SL, Stoneham S, Lopes LF, Nicholson J, Frazier AL, Xie Y, JCO Clin Cancer Inform 2020 Jun 4 555-566
- Tumor neoantigenicity assessment with CSiN score incorporates clonality and immunogenicity to predict immunotherapy outcomes.
- Lu T, Wang S, Xu L, Zhou Q, Singla N, Gao J, Manna S, Pop L, Xie Z, Chen M, Luke JJ, Brugarolas J, Hannan R, Wang T, Sci Immunol 2020 Feb 5 44