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Blending algorithms and Bayesian machine learning in computational biology.

The Efficient Learning and Graph Algorithm Techniques for Omics (EL GATO) Lab at UConn was founded in 2018 and includes researchers with a wide range of interests and specialties. Our research aims to develop probabilistic machine learning models, combinatorial algorithms, and scalable inference methods to better understand high-dimensional data, particularly genomics and genetics data applied to complex disease.

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Some recent news

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{% capture text %} We focus on Bayesian machine learning and combinatorial methods development across a wide range of areas.

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