Jeremy Goecks

Jeremy Goecks

Assistant Professor of Computational Biology
Faculty: Full-Time
Address: Innovation Hall

Areas of Expertise

Platforms for High-throughput Genomic Analysis, Cancer Genomics, Scientific and Information Visualization, Interactive High Performance Computing.

  • 2013-Present: Assistant Professor, Computational Biology Institute, George Washington University
  • 2009-2013: Postdoctoral Researcher, Departments of Biology and Math & Computer Science, Emory University

Current Research

Please see Dr. Goecks' lab Website ( for a complete description of his research.

My research agenda centers on two complementary areas: computational platforms for high-throughput genomic analysis and cancer genomics.

With the widespread adoption of high-throughput DNA sequencing technologies in biomedical research, there is an increasing need for computational platforms that simplify and provide broad access to multi-step, compute-intensive analyses of genomic data. To address this need, the Galaxy project ( has developed a Web-based platform for accessible, reproducible, and collaborative analysis of high-throughput genomics data, aptly named Galaxy ( I am a lead member of the Galaxy project, with a focus on Galaxy’s collaboration, visualization, and visual analysis features. A primary goal of this work is enabling visualization of very large genomic datasets on the Web. We are also developing visual analysis applications that combine visualization with analysis and workflows so that visual inspection can be used to guide and workflow usage.

I also lead the development of Galaxy-based workflows (pipelines) for personalized cancer treatment. Because cancer is a disease of the genome, genomic analyses have proven useful for understanding the disease state and suggest potential treatments. Galaxy pipelines for tumor analysis combine multiple genomic features (e.g. mutations, structural variations and rearrangements, gene expression levels) into a comprehensive genomic profile of a tumor. Next, the pipelines integrate publicly available data with private patient data to find promising drugs and similar laboratory models that can used for high-throughput screening. By virtue of integrating these pipelines into Galaxy, they provide standardized, reproducible, and understandable pipelines for clinical cancer genomic analyses.


Ph.D. Georgia Institute of Technology, 2009 (Computer Science)
B.S. University of Wisconsin, 2001 (Computer Science)


For a complete publication list, please visit Dr. Goecks' Google Scholar page.
Journal Articles

Harris, N. L., Cock, P. J., Chapman, B. A., Goecks, J., Hotz, H. R., & Lapp, H. (2015). The Bioinformatics Open Source Conference (BOSC) 2013. Bioinformatics, 31(2), 299-300.

Budd, A., Corpas, M., Brazas, M.D., Fuller, J.C., Goecks, J., Mulder, N.J., Michaut, M., Ouellette, B.F., Pawlik, A. and Blomberg, N., 2015. A quick guide for building a successful bioinformatics community. PLoS Comput Biol, 11(2), p.e1003972.

Goecks, J., El‐Rayes, B. F., Maithel, S. K., Khoury, H. J., Taylor, J., & Rossi, M. R. (2015). Open pipelines for integrated tumor genome profiles reveal differences between pancreatic cancer tumors and cell lines. Cancer medicine, 4(3), 392-403.

Phillips, C. J., Phillips, C. D., Goecks, J., Lessa, E. P., Sotero-Caio, C. G., Tandler, B., ... & Baker, R. J. (2014). Dietary and flight energetic adaptations in a salivary gland transcriptome of an insectivorous bat. PloS one, 9(1), e83512.

C. J. Phillips, C. D. Phillips, J. Goecks, E. P. Lessa, C. Sotero-Caio, B. Tandler, A. Nekrutenko, M. R. Gannon, R. K. Chesser, and R. J. Baker. Dietary and Flight Energetic Adaptations in a Salivary Gland Transcriptome of an Insectivorous Bat. PLoS ONE, in press.
P. Li, J. Goecks, and T. Lee (2012) Turning pipe dreams into reality. Genome Biology, 13:318.

J. Goecks, C. Eberhard, T. Too, The Galaxy Team, A. Nekrutenko, and J. Taylor (2013) Web-based visual analysis for high-throughput genomics. BMC Genomics, 14, 1.

N.T. Mortimer, J. Goecks, J.A. Mobley, G.J. Bowersock, J. Taylor, and T. Schlenke (2013) Parasitoid wasp venom SERCA regulates Drosophila calcium levels and inhibits cellular immunity. Proceedings of the National Academy of Sciences, 110, 23.

J. Goecks*, N.T. Mortimer*, J.A. Mobley, G.J. Bowersock, J. Taylor, and T. Schlenke (2013) Integrative Approach Reveals Composition of Endoparasitoid Wasp Venoms. PLoS ONE, 8(5): e64125. *Equal Contributions. 

J. Goecks, N. Coraor, The Galaxy Team, A. Nekrutenko, and J. Taylor (2012) NGS analyses by visualization with Trackster. Nature Biotechnology, 30, 11.

J. Goecks, A. Nekrutenko, J. Taylor and The Galaxy Team. (2010) Galaxy: a comprehensive approach for supporting accessible, reproducible, and transparent computational research in the life sciences. Genome Biology 11, R86. 

Peer-reviewed Conference Papers with Proceedings
J. Goecks, K. Li, D. Clements, The Galaxy Team, and J. Taylor (2011) The Galaxy Track Browser: Transforming the Genome Browser from Visualization Tool to Analysis Tool. 2011 IEEE Symposium on Biological Data Visualization. 
J. Goecks, W.K. Edwards, and E.D. Mynatt (2009) Challenges in Supporting End-User Privacy and Security Management with Social Navigation. 2009 ACM Symposium on Usable Privacy and Security.

J. Goecks, A. Voida, S. Voida, E.D. Mynatt (2008) Charitable Technologies: Collaborative Computing in Nonprofit Fundraising. Proceedings of the 2008 ACM Conference on Computer-Supported Cooperative Work (CSCW), p. 689-698.

J. Goecks and E.D. Mynatt (2005). Supporting Privacy Management via Community Experience and Expertise. Proceedings of 2005 Conference on Communities and Technologies, p. 397-418.

J. Goecks and E.D. Mynatt (2004). Leveraging Social Networks for Information Sharing. Proceedings of 2004 ACM Conference on Computer-Supported Cooperative Work (CSCW), p. 328-331.

J. Tullio, J. Goecks, E.D. Mynatt, and D. Nguyen (2002). Augmenting Shared Personal Calendars. Proceedings of 2002 ACM Conference on User Interface Software and Technology (UIST), p. 11-20.

J. Goecks and D. Cosley (2002). NuggetMine: Intelligent Groupware for Opportunistically Sharing Information Nuggets. Proceedings of 2002 ACM Conference on Intelligent User Interfaces (IUI), p. 87-94.

J. Goecks and J. Shavlik (2000). Learning about Users by Unobtrusively Observing Their Normal Behavior: Surrogate Measures for User Interest. Proceedings of 2000 ACM Conference on Intelligent User Interfaces, p. 129-132.


Presidential Fellowship, Georgia Institute of Technology, 2001-2006