BIMSA > 生物信息讨论班 Report a paper: Persistent spectral hypergraph based machine learning (PSH-ML) for protein-ligand binding affinity prediction
Report a paper: Persistent spectral hypergraph based machine learning (PSH-ML) for protein-ligand binding affinity prediction
组织者
丘成栋
演讲者
孙楠
时间
2022年10月02日 10:00 至 10:30
地点
Online
线上
Tencent 801 3489 7723 ()
摘要
This paper was published in the journal, Briefings in Bioinformatics (IF 13.994, JCR Q1), and was written by Professor Jie Wu. This paper proposed persistent spectral hypergraph (PSH) based molecular descriptors or fingerprints for the first time. The PSH-based molecular descriptors are used in the characterization of molecular structures and interactions, and further combined with machine learning models, in particular gradient boosting tree (GBT), for protein-ligand binding affinity prediction. They got good results. I will report it in detail.
演讲者介绍
孙楠目前是北京雁栖湖应用数学研究院的博士后。她的研究方向包括生物信息学、机器学习和应用数学，在The Innovation, Computational and Structural Biotechnology Journal, BMC Bioinformatics, Frontiers in Cellular and Infection Microbiology, Journal of Computational Biology, Genes等期刊发表多篇论文，参与多项国家自然科学基金及北京市自然科学基金项目，主持中国博士后科学基金第78批面上资助。