Joel H. Graber, Ph.D.

Education
- Ph.D., Cornell University, Experimental Accelerator Physics, 1993
- B.S., Michigan Technological University, Physics, 1987
- B.S., Michigan Technological University, Computer Science, 1987
State-of-the-art biomedical research is increasingly dependent on genome-scale data sets that require computational expertise and robust procedures to facilitate rigorous and reproducible analysis. Moreover, complex projects often require collaboration among research groups with diverse skill sets and expertise, further necessitating detailed and careful procedures for sharing, analysis and integration of related experiments. In the Computational Biology/Bioinformatics Core, we support the broader research community of the MDI Biological Laboratory and its individual research groups by providing expert-level data management, processing and analysis for all generated data.
As director of the core, it is my role to ensure that our computational data analysis resources are up-to-date and sufficiently adaptable to answer the specific questions of interest for each research group. Our work in the core is inherently collaborative, beginning before data is collected with discussions and statistical assessment of projected experiments, continuing through all steps of data analysis, providing explanations of the rationale and consequences of computational options and finally ending with the generation of tables and figures and their interpretation for publication and presentation.
We engineer all computational pipelines to ensure robust and rigorous vetting, storage and analysis of genomic data. Reproducibility is ensured by careful version control of all software and external data resources, combined with complete and detailed logging of all analytic procedures. Rigor is established and enhanced by generating all workflows in a modular manner that facilitates characterization of the consequences of variation in choices of program, data resources or parameters.
Part III: Meet the Computational Biology Core
Breaking Through · November 18, 2020
MDI Biological Laboratory Scientists Decipher Role of a Stress Response Gene
Press Release · September 9, 2020
MDI Biological Laboratory hosts 2020 National Science Foundation Fellows
Bangor Daily News · August 11, 2020
Bioinformatics Part II: What do my genome-scale measurements of gene expression mean?
Breaking Through · July 28, 2020
Part I: Computational Biology is vital to modern research
Breaking Through · July 10, 2020
April 6 Update: Science doesn't stand still
Breaking Through · April 6, 2020
Big Data: Computational Biology Opens a New Window on the World’s Challenges for Colby Scientists
Colby Magazine · October 2, 2017
MDI Biological Laboratory Celebrates Banner Year
Mount Desert Islander · August 2, 2017
Joel Graber, Ph.D., Joins MDI Biological Laboratory As Senior Staff Scientist
Bio IT World · April 28, 2017
Dr. Joel Graber is director of the MDI Biological Laboratory Computational Biology/Bioinformatics Core, which carries out computational analysis and program development in support of MDIBL, INBRE, and visiting scientists. Undergraduate Research Fellows working within the Core perform analysis and interpretation of genome-scale data, with an emphasis “best practices” in big-data analysis. Student work is targeted to discrete projects that can be carried out over the course of a single summer.
Students projects within the Core typically focus on the development of computational analysis or programming tools for genomic analysis related to the core MDIBL interests of stress, aging, and regeneration.
The Core also welcomes collaborative proposals such that a Summer Research Fellow would carry out computational work under the supervision of Core personnel, but focused on specific research questions of interest to other INBRE faculty members.
In addition, Computational Biology/Bioinformatics Core personnel provide training to all summer fellows on site at MDIBL, including both classroom lectures and one-on-one or small group consulting, with a focus on state-of-the-art computational analysis tailored to the needs of individual research projects.