Thời gian: 14h Thứ 5, ngày 25/05/2023

Địa điểm: Phòng 507 nhà A6

Link online Zoom: 845 8621 8812

Passcode: 123456

Tóm tắt: Next generation sequencing (NGS) and single cell RNA sequencing (scRNA-seq) are the two major sequencing technologies and they have been used dominantly in biological research and medical applications in recent years. NGS technologies have played the key in criminal investigations, paternity tests, and medication tests such as Huntington’s disease, Down syndrome. The single cell RNA sequencing on the other hand provides new opportunities for discovery of previously unknown cell types and facilitating the study of biological processes such as cancer development. Computational methods using machine learning, graph theory and optimization are the fundamental steps in analyzing high-dimensional data produced by these technologies. However, computational models have been challenged by the exponential growth of the data, owing to the growth of large-scale genomic projects such as the Human Cell Atlas. In this talk, we will introduce several computational methods which we have developed for analyzing large-scale NGS data and scRNA-seq data, including genome assembly, clustering, and dimensionality reduction.