WANT A PROFILE LIKE THIS?
Create my FREE Plan Or learn about other options
Casey Greene
PeerJ Author
445 Points

Contributions by role

Author 135
Preprint Author 175
Editor 135

Contributions by subject area

Bioinformatics
Computational Biology
Genomics
Legal Issues
Science and Medical Education
Statistics
Computational Science
Data Mining and Machine Learning
Agricultural Science
Mathematical Biology
Microbiology

Casey S Greene

PeerJ Author

Summary

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.

Bioinformatics Computational Biology

Editing Journals

Past or current institution affiliations

University of Pennsylvania

Work details

Assistant Professor

University of Pennsylvania, Perelman School of Medicine
August 2015
Systems Pharmacology and Translational Therapeutics

Assistant Professor

Geisel School of Medicine at Dartmouth
August 2012 - July 2015
Genetics

Websites

  • Greene Lab
  • Google Scholar
  • PubMed Search

PeerJ Contributions

  • Articles 1
  • Preprints 3
  • Edited 1
  • Feedback 1
January 21, 2016
Cross-platform normalization of microarray and RNA-seq data for machine learning applications
Jeffrey A. Thompson, Jie Tan, Casey S. Greene
https://doi.org/10.7717/peerj.1621 PubMed 26844019
September 20, 2018 - Version: 1
Discovering pathway and cell-type signatures in transcriptomic compendia with machine learning
Gregory P Way, Casey S Greene
https://doi.org/10.7287/peerj.preprints.27229v1
February 2, 2018 - Version: 3
Sci-Hub provides access to nearly all scholarly literature
Daniel S Himmelstein, Ariel R Romero, Jacob G Levernier, Thomas A Munro, Stephen R McLaughlin, Bastian Greshake Tzovaras, Casey S Greene
https://doi.org/10.7287/peerj.preprints.3100v3
October 30, 2015 - Version: 1
Cross-platform normalization of microarray and RNA-seq data for machine learning applications
Jeffrey A Thompson, Jie Tan, Casey S Greene
https://doi.org/10.7287/peerj.preprints.1460v1

Academic Editor on

January 24, 2019
Prioritizing bona fide bacterial small RNAs with machine learning classifiers
Erik J.J. Eppenhof, Lourdes Peña-Castillo
https://doi.org/10.7717/peerj.6304 PubMed 30697489

Provided feedback on

24 Jul 2019

Discovering pathway and cell-type signatures in transcriptomic compendia with machine learning

This manuscript has now been published: https://www.annualreviews.org/doi/abs/10.1146/annurev-biodatasci-072018-021348