学术报告
题 目: The rise of deep learning in drug discovery
广州再生医学与健康广东省实验室(生物岛实验室)
地 点: 北京大学老化学楼东配楼101报告厅
主持人: 裴剑锋 研究员
摘 要:
Over the past decade, deep learning has achieved remarkable success in various artificial intelligence research areas. Evolved from the previous research on artificial neural networks, this technology has shown superior performance to other machine learning algorithms in areas such as image and voice recognition, natural language processing, among others. The first wave of applications of deep learning in pharmaceutical research has emerged in recent years, and its utility has gone beyond bioactivity predictions and has shown promise in addressing diverse problems in drug discovery. In this talk, we are going to discuss examples covering bioactivity prediction, de novomolecular design, synthesis prediction and virtual screening etc.
报告人简介:
陈红明 1998年于中国科学院化工冶金研究所(现过程工程研究所)获得计算化学博士学位。1998-2000年期间,在德国拜耳公司Wuppertal药物研发中心从事博士后研究工作。他在2001年加入阿斯利康制药公司瑞典哥德堡的研发中心,从事计算化学和新药开发工作长达18年,曾在先导化合物发现部门担任主任研究员(Principal Scientist)职位。他于2019年加盟广州再生医学与健康广东省实验室(现更名生物岛实验室),担任研究员(Principal Investigator)并组建人工智能与药物设计研发团队。他的主要研究兴趣在计算化学,化学信息学,人工智能/机器学习等方面,已发表学术论文和专利70余篇。目前担任Molecular Informatics 杂志学术咨询委员会委员和Artificial Intelligence in the Life Sciences杂志编委委员。