报告人：宋江宁教授

报告题目：Artificial intelligence to explore the multi-modality biomedical data and accelerate knowledge discovery

摘要：The rapid accumulation of molecular data motivates development of innovative approaches to computationally characterize sequences, structures and functions of biological and chemical molecules in an efficient, accessible and accurate manner. We address this vital need by developing a holistic platform that generates features from sequence and structural data for a diverse collection of molecule types. Our freely available and easy-to-use AI platforms can generate, analyse and visualize more than 180 representations for biological sequences, structures and ligands. With the assistance of the AI tools, users can encode their molecular data into representations that facilitate construction of predictive models and analytical studies. In the talk, I will illustrate how such AI tools can be used to accelerate and streamline research in bioinformatics, computational biology, and cheminformatics areas.

报告时间：2022年10月28日下午14：00-16：00

报告形式：腾讯会议，会议号：310-589-501

获取会议密码请发邮件至：jhua@stu.hit.edu.cn

报告人简介：Prof. Song is a Group Leader in the Cancer and Infection and Immunity Programs in the Biomedicine Discovery Institute (BDI), and Department of Biochemistry and Molecular Biology, Faculty of Medicine, Nursing and Health Sciences, Monash University, Melbourne, Australia. Trained as a bioinformatician and data-savvy scientist, he has a very strong specialty in Artificial Intelligence, Bioinformatics, Comparative Genomics, Cancer Genomics, Computational Biomedicine, Data Mining, Machine Learning, Proteomics, and Biomedical Big Data, which are highly sought-after expertise and skill sets in the data-driven biomedical sciences. He is also a member of the Monash Data Futures Institute, the ARC Centre of Excellence in Advanced Molecular Imaging and Center to Impact Antimicrobial Resistance.