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October
2017
11
Jeff Leek, PhD
New York Genome Center
4:00 PM — 5:30 PM

Building a Comprehensive Resource for the Study of Human Gene Expression with Machine Learning and Data Science

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About

Associate Professor of Biostatistics
Johns Hopkins Bloomberg School of Public Health
 
 
“Building a Comprehensive Resource for the Study of Human Gene Expression with Machine Learning and Data Science.”
 
Abstract: Gene expression is an important intermediate phenotype in the study of human biology. It can be cheaply and scalably measured, is an important surrogate for protein expression, and is responsive to both inherited genetic variation and environmental exposures. Dr. Leek will discuss his efforts to build recount2 – a comprehensive database of over 70,000 gene expression samples. He will show how his lab uses cloud computing, statistical modeling, and machine learning to reproducibly unify, clean, and annotate these data. Dr. Leek will then highlight some examples of how both his lab group and others are using the resource to answer fundamental questions about human gene expression.
 
Biography: Jeff Leek, PhD, is an Associate Professor of Biostatistics at the Johns Hopkins Bloomberg School of Public Health and co-editor of the Simply Statistics Blog. He received his PhD in Biostatistics from the University of Washington and is recognized for his contributions to genomic data analysis and statistical methods for personalized medicine. His data analyses have helped us understand the molecular mechanisms behind brain development, stem cell self-renewal, and the immune response to major blunt force trauma. His work has appeared in the top scientific and medical journals Nature, Proceedings of the National Academy of Sciences, Genome Biology, and PLoS Medicine.
 
To read more about Dr. Jeff Leek’s research, please visit: Google Scholar – Jeff Leek, PhD

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