Big data and big computing power-based machine learning methods have made remarkable progress in image recognition, video analysis and natural language processing with the rapid development of cutting-edge artificial intelligence technologies. These advancements have gradually intersected and integrated with biology, giving rise to a new discipline known as AI biology. AI biology mainly utilizes the principles and techniques of artificial intelligence to study and discover the basic laws of life systems. Its essence lies in simulating and surpassing the associative capabilities of the human nervous system to solve complex biological problems. 

This session aims to explore the latest research progress in the combination of cutting-edge artificial intelligence and life science research. Invited reports will cover the research and development of technical methods, important biological discoveries, and potential clinical applications and practices of AI technology in structural biology, biological big data integration, and biomedical research and development. 

Chair

Chen Luonan

Research fellow, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences (CAS)

Invited speakers & reports

Yang Jianyi

Professor, Shandong University

Report: Learning protein structure

Zhang Qiangfeng

Research fellow, Tsinghua University

Report: AI-driven biological structure analysis 

Liu Qi

Professor, Tongji University

Report: Few-shot learning in omics data mining

Weng Kung, PENG

Songshan Lake Materials Laboratory

Report: NMR-based traits: The next generation of precision medicine

Xu Jianping

Leica Microsystems

Report: Era of autonomous confocal microscopy powered by Leica AIVIA begins

Zhang Shihua

Research fellow, Academy of Mathematics and Systems Science, CAS

Report: Intelligent spatial transcriptomics: Paving the way for deciphering tissue structure 

Zeng Jianyang

Associate professor with tenure, Tsinghua University

Report: Deep learning for advancing drug discovery

Ye Sheng

Research fellow, Beihang University

Report: CUTEDGE: A sequence-independent protein design algorithm based on reciprocal space diffusion model 

Chen Luonan

Research fellow, Shanghai Institutes for Biological Sciences, CAS

Report: Dynamics-based data science and AI in biology and medicine