Gemma is the work of many people and benefits from numerous open source tools and publicly-available data, as well as generous grant support from many sources.
Zoubarev, A., et al., Gemma: A resource for the re-use, sharing and meta-analysis of expression profiling data. Bioinformatics, 2012. (link)
- Matthew Jacobson
- Justin Leong
- Manuel Belmadani
- Stepan Tesar
The following people have contributed code, algorithms, implementations of algorithms, or other computational work relating to Gemma.
- Elodie Portales-Casamar – Phenocarta
- Jesse Gillis – Coexpression analysis
- Leon French – Ontologies and annotations
- Meeta Mistry – Gene Ontology metrics, differential expression
- Raymond Lim – Differential expression meta-analysis
- Vaneet Lotay – Coexpression algorithm testing
- Xiang Wan – Coexpression analysis
- Brenna Li
- James Liu
- Patrick Savage
- Nathan Holmes
- Jenni Hantula
- Nathan Eveleigh
- John Choi
- Artemis Lai
- Cathy Kwok
- Celia Siu
- Luchia Tseng
- Lydia Xu
- Mark Lee
- Olivia Marais
- Roland Au
- Suzanne Lane
- Tianna Koreman
- Willie Kwok
- Yiqi Chen
- Kevin Griffin
- Stephen Macdonald
- Anton Zoubarev – Lead programmer (2010 – 2014)
- Cameron McDonald – Programmer (2011 – 2014)
- Frances Lui – Programmer (2011 – 2013)
- Nicolas St-Georges – Programmer (2011 – 2014)
- Gavin Ha – Undergraduate research assistant – web services (2008)
- Joseph “JR” Santos – Programmer (2006-2007)
- Kelsey Hamer – Lead programmer (2006-2010)
- Kiran Keshav – Developer (2005) and consultant
- Louise Donnison – Developer (2009-2010)
- Luke Mccarthy – Programmer (2007- Feb 2008)
- Thea Van Rossum – Programmer (2011 – 2012)
- Celia Siu – Systems
- Hugh Brown – Systems
Other contributers to early stages of Gemma include David Quigley, Anshu Sinha and Gozde Cozen. Gemma’s precursor was TMM, which was developed by Homin Lee, Jon Sajdak, Jie Qin and Amy Hsu. Martin Krzywinski has provided helpful advice on visualization.
We are indebted to the many researchers who have made data publicly available. Lists of published papers that relate to the data included in Gemma are available here (full list) and here (search) . If your data is in Gemma, and your paper is not listed, please let us know .
Gemma obtains most data from the Gene Expression Omnibus with an increasing contribution from ArrayExpress. We are grateful for the curation efforts at those sites, and the technical assistance we’ve received.
Tools and resources
Some icons used in Gemma are from famfamfam.
Gemma uses for network visualization. Gemma is developed with the help of the YourKit Java profiler, provided courtesy of YourKit LLC.