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Academic Report No. 91: Application of High-Dimensional Statistical Methods in 3D Genomic Data Analysis

Time:2025-09-29 16:42

主讲人 Tian Dechao 讲座时间 October 7, 2025, 16:00-17:00 (afternoon)
讲座地点 Conference Room 303, Alumni Plaza 实际会议时间日 7
实际会议时间年月 2025.10

Academic Report of the School of Mathematical Sciences [2025] No. 091  

(High-Level University Construction Series Report No. 1113)  


Lecture Title: Application of High-Dimensional Statistical Methods in 3D Genomic Data Analysis  

Lecturer: Associate Professor Tian Dechao (School of Public Health (Shenzhen), Sun Yat-sen University)  

Lecture Time: October 7, 2025, 16:00-17:00 (afternoon)  

Venue: Conference Room 303, Alumni Plaza  

Abstract:  

The 3D structure of the genome plays a crucial role in gene regulation and cellular functions. Comparative analysis of Hi-C data and single-cell Hi-C data is essential for revealing the structure-function relationship of the genome under healthy and disease states. However, such data exhibit characteristics of high dimensionality, extreme sparsity, and strong correlation, posing significant challenges to statistical analysis. This report will introduce recent results from collaborative research, which integrate the use of random matrix theory, statistical modeling, and deep generative models. The key progress includes: (1) enhancement of extremely sparse single-cell Hi-C data; (2) differential testing for paired high-dimensional Hi-C matrices. Another independent research direction is (3) fine-tuning large language models to predict influenza activity. The report will demonstrate the application of these methods in real-world data and the scientific findings they reveal, thereby illustrating their potential in advancing genomics and public health research.  

Lecturer’s Biography:

Tian Dechao is an Associate Professor and Doctoral Supervisor in the Department of Biostatistics and Systems Biology, School of Public Health (Shenzhen), Sun Yat-sen University. His main research direction focuses on the development of ultra-high-dimensional statistical methods and deep learning methodologies for 3D genomic data analysis, as well as their applications in medicine. He has published numerous papers in internationally renowned journals and conferences such as Nature Communications, Genome Research, and RECOMB. He also presides over projects funded by the National Natural Science Foundation of China and the Guangdong Provincial Natural Science Foundation.  


Faculty and students are welcome to attend!  

Inviter: Wang Jiangzhou  


School of Mathematical Sciences  

September 29, 2025