报告题目:多组学数据分析中的机器学习方法
主 讲 人:黄 昆
单 位:印第安纳大学
时 间:8月26日8:30
ZOOM ID:210 089 8623
密 码:123456
摘 要:
With the advancement in high throughput technologies, various types of "omics" data have been generated for human disease studies. In particular, large amounts of "multi-omics" data have been generated for important diseases such as cancer and Alzheimer's disease. However, computationally it is challenging to integrate the multiple types of omics data given the high dimensionality, heterogeneous data type, high dynamical range, and multiple tasks associated with the integration. In this talk, I will introduce our work over the past decade on applying different machine learning approaches for integrative analysis of multi-omics data. These methods were driven by translational applications such as cancers and Alzheimer's diseases. These methods have led to new biological hypotheses related to these diseases.
简 介:
黄昆, 1996年毕业于清华大学获生物学理学与电子计算机工学双学士学位,后于美国伊利诺伊大学香槟校区(UIUC)获得生理学、电子工程和数学等三个硕士学位,2004年获得电子与计算机工程学博士学位。2010年获俄亥俄州立大学终身教职。2017年加入印第安纳大学医学院参与领导精准健康计划,担任数据科学与信息学主任,同时任基因组数据科学讲席教授,医学院主管数据科学副院长,印第安纳大学Simon综合癌症中心副主任。2018年当选美国医学与生物工程学院(AIMBE)会士。主要研究方向包括生物信息学,医学图像分析,医疗大数据,机器学习及其在癌症研究及神经科学等方面的应用,发表研究论文200余篇。