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Casey Greene

Bio

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. In addition to developing deep learning methods for extracting context, a core mission of his lab is bringing these capabilities into every molecular biology lab. Before starting the Integrative Genomics Lab in 2012, Casey earned his Ph.D. for his study of gene-gene interactions in the field of computational genetics from Dartmouth College in 2009 and moved to the Lewis-Sigler Institute for Integrative Genomics at Princeton University where he worked as a postdoctoral fellow from 2009-2012. The overarching theme of his work has been the development and evaluation of methods that acknowledge the emergent complexity of biological systems.

Editorial Board Memberships
Current Memberships
Editor Records (manuscripts handled as editor)
Pre Publication Reviews

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Reviews

87

Reviews (last 12 months)

31

Reviews (average per year)

12

Merit

259

Openness

0.6%


Journal Impact factors of journals reviewed for

The distribution of the Journal Impact Factors of journals Casey Greene has reviewed for.

Casey Greene

All fields reviewers

Total reviews over time

A cumulative record of Casey Greene's total number of reviews.

Reviews per month

The total number of reviews performed by Casey Greene each month.

Average review length

The average number of words per review (for which we have content), compared to the average of All fields reviewers and the average of reviewers at affiliated institutions.

Weekly review punchcard

The distribution of days that reviews were performed on, compared to All fields reviewers and reviewers at affiliated institutions.