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Edna K. Papazian Professor of Medicine and Human Genetics, co-Chief of Section of Computational Biomedicine and Biomedical Data Science, Senior Fellow of the Institute for Genomics and Systems Biology
The Computational Social Science Workshop at the University of Chicago cordially invites you to attend this week's talk:
Summary: I will attempt to cover several interrelated topics, spending more time on parts that resonate with the audience. I will introduce our recent study analyzing phenotypic data harvested from over 175 million unique patients. We use them to 1) estimate the heritability and familial environmental patterns of diseases, and 2) infer the genetic and environmental correlations between disease pairs from a set of complex diseases. I am particularly interested in inferring objective classifications of diseases (based on a formal optimization criterion), separately from environmental and genetic factors. I will then show how the same data can be used for spatial analysis of disease prevalence (with several examples, including “many Americas” analysis in medications use). Finally, I will give an example of practical application of computational analysis (asthma and sepsis story).
A light lunch will be provided by Good Earth Catering Company.
Andrey Rzhetsky is an Edna K. Papazian Professor of Medicine and Human Genetics, at the University of Chicago, and a co-Chief of Section of Computational Biomedicine and Biomedical Data Science. He is also a Pritzker Scholar, and a Senior Fellow the Institute for Genomics and Systems Biology at the University of Chicago. His research is focused on computational dissection of etiology of complex human diseases.
Some suggested background:
- Attached in Repository: Patchwork of contrasting medication cultures across the USA
- Attached in Repository: Classification of common human diseases derived from shared genetic and environmental determinants
- Attached in Repository: Preexisting Type 2 Immune Activation Protects against the Development of Sepsis
The 2018-2019 Computational Social Science Workshop meets Thursdays from 11 a.m. to 12:20 p.m. in Kent 120. All interested faculty and graduate students are welcome.
Students in the Masters of Computational Social Science program are expected to attend and join the discussion by posting a comment on the issues page of the workshop's public repository on GitHub. Further instructions are documented in the Computational Social Science Workshop's README on Github.