“‘Big Data’ Challenges in the Life Sciences” versus” ‘Big’ Data Challenges in the Life Sciences”
发布时间 :2019-05-05  阅读次数 :3839

报告题目:“‘Big Data’ Challenges in the Life Sciences” versus” ‘Big’ Data Challenges in the Life Sciences”

主讲人: Simon Rayner   

Professor of Computational Biology, Dept of Medical Genetics, Oslo University Hospital/University of Oslo

Principal Investigator, Hybrid Technology Hub/Organoid on Chip Centre of Excellence, Department of Molecular Biology, University of Oslo, Oslo, Norway 

报告时间:2019-05-13   13:00-15:00

报告地点:生命科学技术学院  3-105

联系人:Ilya Vinnikov(ilya.vinnikov@gmail.com



Simon Rayner has worked in both academia and industry. He has a PhD in Computational Physics from the University of East Anglia in the UK. He is currently a Professor of Computational Biology in the Department of Medical Genetics at Oslo University Hospital and a Principal Investigator at the Hybrid Technology Hub Organoid on Chip Centre of Excellence at the Institute of Molecular Biology at the University of Oslo. His primary research interests involve investigating genetic disposition to infectious disease and using synthetic organoid platforms to study infectious disease pathways. He also works on the epidemiology of epidemics and epizootics in SE Asia. He was previously a Principal Investigator at Wuhan Institute of Virology and an Associate Professor at the Departments of Biochemistry and Internal Medicine at UT Southwestern Medical Centre in Dallas, Texas, USA where is worked on the Human Genome Project. He was Assistant Editor in Chief for Virologica Sinica from 2009 to 2015 and the co-founder of a successful biotech company in the US.



The phrase “’Big Data’ Challenges in the Life Sciences” is commonly associated with challenges in large-scale projects such as public healthcare in the context of personalized medicine. On the other hand, “ ‘Big’ Challenges in Data in the Life Sciences” is associated with the general challenges dealing with all data in the life sciences and is something everyone faces in one way or another. This encompasses factors such as data collection, data curation, data standardization, data storage and data visualization. In this presentation I will talk about the latter (“ ‘Big’ Challenges in Data in the Life Sciences”) and discuss these challenges in the context of previous infectious disease research in virology in Wuhan and Beijing and on current research focusing on microRNA characterization and applying deep learning to microRNA targeting in the context of genetic disposition to infectious disease.