报告题目： Data Science in Imaging Genomics

报 告 人： Li Shen（沈理）

报告时间：4月19日（周二）16:00

报告地点：将军路校区计算机楼507

报告简介：

Imaging genomics is an emerging data science field, where integrative analysis of imaging and omics data is performed to provide new insights into the phenotypic characteristics and genetic mechanisms of normal or disordered physiology, and to impact the development of new diagnostic, therapeutic and preventive approaches. However, due to the unprecedented scale and complexity of these data sets, this field is facing major computational and bioinformatics challenges. In this talk, using the Alzheimer’s Disease Neuroimaging Initiative (ADNI) project as an example, we will discuss fundamental concepts, state-of-the-art statistical and machine learning methods, and innovative applications in this young and rapidly evolving field. We show that the broad availability and wide scope of imaging genomics data, coupled with computational and data science advances, have the potential to significantly contribute to multiple US and worldwide health priority areas including the big data to knowledge initiative, the brain initiative, Alzheimer’s disease, and precision medicine.

 报告人简介：

Dr. Li Shen holds a B.S. degree from Xi’an Jiao Tong University, an M.S. degree from Shanghai Jiao Tong University, and a Ph.D. degree from Dartmouth College, all in Computer Science. He is an Associate Professor of Radiology and Imaging Sciences at Indiana University School of Medicine (IUSM), and Associate Director of the Center for Computational Biology and Bioinformatics (CCBB) at IUSM. He is the Executive Director of the MICCAI Society Board of Directors. He is also affiliated with the IU Center for Neuroimaging, the IU Network Science Institute, the Stark Neurosciences Research Institute at IUSM, Departments of CIS, ECE and Biostatistics at IUPUI, and the School of Informatics and Computing at IUPUI. His research interests include medical image computing, bioinformatics, data mining, and network science. The central theme of his lab is focused on developing computational and informatics methods for integrative analysis of multimodal imaging data, high throughput “omics” data, cognitive and other biomarker data, and rich biological knowledge such as pathways and networks, with applications to various complex disorders. The goal is twofold: (1) advance computer science and bioinformatics by producing novel algorithms for analyzing large scale heterogeneous data sets; and (2) improve mechanistic understanding of disease processes and treatment responses for early diagnosis and therapeutics. His research is primarily funded by NIH (NLM, NIA, NIBIB, NIAAA, NCATS), NSF, DOD and NCAA. Further information about Dr. Shen’s research is available at http://www.iu.edu/~shenlab/.

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