应计算学部机器学习研究中心邀请，沙特阿卜杜拉国王科技大学 高欣 教授将于2021年8月10日通过线上会议的形式作报告，介绍机器学习方法辅助的基因诊断技术，欢迎大家参加。

报告时间：2021年8月10日（星期二）9:30-10:30

特邀讲者：高欣 教授

报告地点：腾讯会议ID：585 320 599

主持人：武小荷 博士

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 (http://sfb.kaust.edu.sa). 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.