Casey Greene, Ph.D.

casey_picture_for_ddd_program

The featured outstanding New PI for September 2018 is Casey Greene, Ph.D.!

Dr. Greene is an Assistant Professor of Systems Pharmacology and Translational Therapeutics in the Perelman School of Medicine at the University of Pennsylvania. He is also the Director of the Childhood Cancer Data Lab for Alex’s Lemonade Stand Foundation.His lab uses computational approaches to develop deep learning methods for large-scale datasets. Dr. Greene’s lab is focused on modeling complex biological systems, which have spanned from zebrafish development to cancer.Dr. Greene is currently funded by grants from National Science Foundation (NSF), the Gordon and Betty Moore Foundation, Alex’s Lemonade Stand Foundation, Pfizer, the Chan-Zuckerberg Initiative, in addition to an R01 from NIH/NIGRI.

Dr. Greene received his B.S. in Chemistry from Berry College. He then received his Ph.D. in Computational Genetics from Dartmouth College. During his Ph.D. studies, Dr. Greene was funded by a highly competitive predoctoral training fellowship from the NIEHS. He was also a finalist for a number of best student paper awards and winner of the Graphics Processing Units (GPUs) for Genetic and Evolutionary Computation Competition in 2009. He then moved to the Lewis-Sigler Institute for Integrative Genomics at Princeton University where he worked as a postdoctoral fellow from 2009-2012. In 2012, Dr. Greene started his independent laboratory at Dartmouth College’s Geisel School of Medicine in the Department of Genetics. In 2014, Dr. Greene was named one of fourteen Moore Investigator in Data-Driven Discovery from the Gordon and Betty Moore Foundation. In 2015, Dr. Greene was recruited to the Perelman School of Medicine at the University of Pennsylvania.

Dr. Greene has many scientific accomplishments. For instance, he, along with Anthony Gitter from the University of Wisconsin, led an open review on deep learning in biology that was authored on GitHub. The full text of the review has been downloaded more than 70,000 times. It was listed in the article, “2017 in news: The science events that shaped the year” from the journal Nature. He states that his accomplishments have been shaped by the “hardworkingpeople that I get to work with and talk to each day about new software, new things we are trying to accomplish, and new discoveries”. Additionally, Dr. Greene’s work has been consistently recognized. He has been invited to give talks around the world and is also an academic editor, associated scientific advisor, or reviewer for many well-known journals. Finally, Dr. Greene is a prolific scientist with nearly 50 peer reviewed research publications in addition to multiple reviews, editorials, and other reports.

Dr. Greene’s lab recently deposited a preprint on bioRxiv where a postdoctoral fellow in his group (Dr. Jaclyn Taroni) demonstrated that performing unsupervised transfer learning enhances the analysis of rare disease datasets. Using both unsupervised machine learning and transfer learning algorithms will be vitally important for analyzing datasets from rare disease where samples are limiting. Using a large, existing dataset to train the model, Dr. Greene’s lab can then use that model to analyze the limited rare-disease data. Using this technique “MultiPLIER”, Drs. Greene and Taroni have begun to better understand the biology of a rare autoimmune disease. You can read the preprint here.

In addition to being an accomplished scientist and passionate mentor, Dr. Greene is dedicated to open science. He provides all of the source code to his lab’s work strives to make research “routinely reproducible”. His lab develops webservers for other scientists to use their algorithms. Dr. Greene believes this will push science forward more efficiently and more rigorously. In fact, he co-founded a research award for this exact purpose: The Research Parasite Award. This award is given annually to scientists that have performed secondary analysis of existing data. To see past winner or apply, please visit the Research Parasite Awardswebsite. He notes: “this is the parasite season, and applications are accepted for this award year until 5PM HST on September 30, 2018. If you share data, don’t miss the Symbiont Awardsfor a chance to win a prize!”

Learn more about Dr. Greene’s research here: http://www.greenelab.com

 

 

 

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