【报告摘要】This report focuses on mutational signatures, which are distinct combinations of mutation types generated by various mutational processes. Cancer is often driven by somatic mutations, and understanding these mutations is crucial for unravelling the mechanisms of cancer development. In this report, I will introduce the concept of DNA mutations, explain how mutation catalogues are constructed, describe methods for extracting mutational signatures, and explore the mechanisms underlying these signatures. Additionally, I will introduce the applications and recent advances in mutational signature research. By examining mutational signatures, this report aims to shed light on how genomic mutation data from cancer patients can be used to quantify DNA mutational processes and patterns, offering deeper insights into the biological processes driving cancer. This understanding paves the way for advancements in cancer diagnosis, prognosis, and personalised treatment strategies.

【报告人简介】Dr. Rong Zhu, Professor in Beijing Institute of Technology, graduated from the Academy of Mathematics and Systems Science at the Chinese Academy of Sciences and later conducted research at Newcastle University and the University of Cambridge in the UK. Her research interests include model averaging, model selection, high-dimensional statistics, and genomic data modeling. She has published several academic papers in top international journals such as the Journal of the American Statistical Association and Journal of Business & Economic Statistics.