Understanding Genetic Disease Similarity Without Compromising Privacy Of Genetic Data
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About The Author

My research lies at the intersection of machine learning, statistics and genetics. Specifically, I am interested in applying Gaussian processes and graphical model techniques for the analysis of large high-dimensional genetic data.

                       

Understanding Genetic Disease Similarity Without Compromising Privacy Of Genetic Data

How strongly do our genes contribute to type 2 diabetes risk? Are heart disorders more heritable among men than women? And is there a shared genetic basis for schizophrenia and depression? The explosive growth of genetic data provides unprecedented opportunities to answer such questions. At the heart of modern genetics lies the observation that most common diseases are polygenic, meaning there is no single mutation acting as a risk factor. Rather, disease risk arises due to the aggregate effect of...

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