报告专家：崔学峰教授（山东大学）

报告题目：Protein structure prediction with Alphafold2

报告地点：9-433

报告时间：2021年11月8日14:30-16:00

报告简介：In December 2020, a team of AI scientists from Google DeepMind indisputably won the 14th Critical Assessment of Structural Prediction (CASP14) competition, a biennial blind test where computational biologists try to predict the structure of several proteins whose structure has been determined experimentally but not publicly released. Their results were so astounding, and the problem so central to biology, that it took the entire world by surprise and left an entire discipline, computational biology, wondering what had just happened.

Nature has now released that AlphaFold 2 paper, after eight long months of waiting. We have 70+ pages of long-awaited answers, and several thousand lines of code that will, no doubt, become a fundamental part of computational biology. At the same time, however, we have many new questions. What is the secret sauce before the news splash, and why is it so effective? Is it a piece of code that the average user can actually run? What are AlphaFold 2’s shortcomings? And, most important of all, what will it mean for computational biology? And for all of us?

专家个人简介：

崔学峰，山东大学计算机科学与技术学院教授、博士生导师。崔教授在加拿大滑铁卢大学戴维分校的计算机科学学院获得学士、硕士和博士学位，曾在沙特阿拉伯阿卜杜拉国王理工大学（Kaista）担任博士后研究员，清华大学终身副教授等，2019年获得ACM SIGBIO新星奖。