Casey Greene

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Casey is an assistant professor in the Department of Systems Pharmacology and Translational Therapeutics in the Perelman School of Medicine at the University of Pennsylvania. His lab develops deep learning methods that integrate distinct large-scale datasets to extract the rich and intrinsic information embedded in such integrated data. This approach reveals underlying principles of an organism’s genetics, its environment, and its response to that environment. Extracting this key contextual information reveals where the data’s context doesn’t fit existing models and raises the questions that a complete collection of publicly available data indicates researchers should be asking.

bioinformatics genomics big data gene expression neural networks machine learning networks denoising autoencoders computational biology data science data integration open source parasite award research parasite reproducibility adage unsupervised pathway cancer ehr tissue-specific netwas systems biology genetic epidemiology gwas microbiology deep learning rocky2015

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Casey Greene

Presentaciones

Casey Greene's Keynote for Rocky 2015

PSB2016 Computational Microbiology Workshop

Network-based approaches for the analysis of gene-disease associations

2016 Presentation at the University of Hawaii Cancer Center

Using ADAGE for pathway-style analyses

No Boundary Thinking in Bioinformatics Workshop Keynote

Public data as a lab resource.

Gone Fishing (From the PSB No Boundary Thinking Workshop)