学术讲座

报告时间： 2022年6月1日（星期三）19：30-21：00          

腾讯会议： 345-509-513                    

主讲人姓名： 高欣  沙特阿卜杜拉国王科技大学（KAUST）终身正教授、中国人民大学高瓴人工智能学院访问讲座教授

主讲人简介：沙特阿卜杜拉国王科技大学（KAUST）终身正教授，博士生导师，同时任KAUST计算生物学中心的副主任，智慧医疗中心的副主任，以及KAUST结构和功能生物信息学研究组负责人。他于2004年在清华大学计算机系获得学士学位，2009年在加拿大滑铁卢大学计算机学院获得博士学位。2009年10月至2010年9月，在美国卡耐基梅隆大学计算机学院雷恩计算生物学中心担任雷恩学者。

   高欣教授的研究焦点主要集中在计算机科学与生物学的交叉领域。在计算机科学领域，他领导的研究团队主要致力于开发与深度学习，概率图形模型，内核方法和矩阵分解相关的机器学习理论和方法。在生物信息学领域，他的研究团队主要致力于构建计算模型、研发机器学习技术、设计高效的算法，以解决从生物序列分析到三维结构确定，到功能注释，再到了解和控制复杂生物网络中的分子行为，以及最近的生物医疗和健康领域中的关键开放问题。

报告题目： Towards Accurate Biomedical Genomics Anywhere Anytime

报告摘要：Current genetic diagnosis by next-generation sequencing requires a large investment of resources and offers little point-of-care portability. Furthermore, it is unable to detect many types of genetic variations ¬– including large deletions, duplications, and balanced translocations ¬– that are relevant to human diseases and health.

   Comparing to other sequencing technologies, Nanopore sequencing owns the advantages of point-of-care (i.e., sequencing anywhere anytime), long reads (i.e., assembly-free to detect various genetic variations), and PCR free (i.e., sample preparation is easy). However, its application is severely limited by a number of challenges, including low base-calling accuracy, lack of training data for AI-based methods, and computational burden on reads mapping.

    In this talk, I will first give an overview of the research activities in Structural and Functional Bioinformatics Group. I will then focus on our efforts on developing computational methods to tackle key open problems in Nanopore sequencing. In particular, I will introduce our recent works on developing a collection of computational methods to decode raw electrical current signal sequences into DNA sequences, to simulate raw signals of Nanopore, and to efficiently and accurately align electrical current signal sequences with DNA sequences. I will further introduce their applications in biomedicine and healthcare.