学术报告
题 目: Opportunities and Challenges in Computational TCR Repertoire Analysis
Lyda Hill Department of Bioinformatics and Department of Immunology，UT Southwestern Medical Center
地 点: ZOOM线上报告
Meeting ID: 910 9636 7823
Password：cqbcqb
主持人: 曾泽贤 研究员
摘 要:
The T cell repertoire is the collection of all the different T cell clones in the immune system. Due to the critical roles that T cells play in multiple diseases, understanding the dynamics and signatures of the T cell repertoire has become increasingly important. There is a growing consensus that TCR repertoire could be serving as the next important biomarker for disease diagnosis and prognosis. However, due to the hyper-diversity of the T cell receptors and the lack of knowledge of their antigen-specificities, the analysis of the TCR repertoire is parable to reading a book without words. Hence, extracting meaningful information from the TCR repertoire of healthy/diseased individuals has become one of the top priorities. Our lab is committed to developing novel computational methods to investigate human TCR repertoires. In this talk, I will cover three of our recent methods, iSMART (Zhang et al., 2020, Clinical Cancer Research), DeepCAT (Beshnova et al., 2020, Science Translational Medicine) and GIANA (Zhang et al., 2021, Nature Communications), and progressively illustrate how we developed a novel diagnostic biomarker out of the TCR repertoire data for early cancer and other disease detections.
Dr. Li received his bachelor’s degree in physics from Peking University, China (2009), and developed a fascination with complex, yet highly organized biological systems. He then pursued a PhD degree in Bioinformatics at the University of Michigan, Ann Arbor, under the supervision of Dr. Jun Li. He joined the Dr. Xiaole Shirley Liu lab at Dana-Farber Cancer Institute for a postdoctoral fellowship, where he was jointly supervised by Drs. Shirley Liu and Jun S. Liu at Harvard Department of Statistics. Li’s research interests are in developing novel bioinformatics methods for investigating high-throughput genomics data to understand disease etiology and biological processes, with a particular interest in cancer. In 2017, Li joined UT Southwestern Medical Center to continue his research in cancer genomics and computational cancer immunology.
