Computational Biology and Biomedical Genomics Training Program

Statement of Purpose

In 2014 we received a five year T32 Training Grant from the NIH to establish a Computational Biology and Biomedical Genomics training program at Georgia Tech. The goal of our program is to provide training for a broad-based set of students with expertise in computational biology and predictive health, which encompasses research from integrative genomics to medical informatics.  We intend to support 4 students per year, mostly students in their second and third years and most for a 2 year term, chosen on the basis of productivity and potential as evidenced by their performance in the first year of the program.  The trainees will be drawn from students in multiple Colleges at Georgia Tech including the Bioinformatics program, Schools of Biology, Biomedical Engineering, Computer Science, Industrial Systems Engineering, and others.  We will establish a common curriculum with two tracks, namely systems biology and personalized medicine, aiming to have between 10 and 20 new students per year engaged in training in these fields of research, including appropriate mentoring and guidance in personal development.

Current Trainees


Melanie Quiver (Bioinformatics - Joe Lachance group)
Interested in genetic bottlenecks throughout evolutionary history and how this might have shaped genomic differences in the risk of alcoholism or other complex disease.

Swetha Garimalla (Biology - Greg Gibson group)
Research Summary: Using multi-omic analysis to characterize the development of long-lived plasma cells in bone marrow in healthy and disease states.

Toyya Pujol-Mitchell (Statistics - Nicoleta Serban group)
Research Summary: Research on how the healthcare and clinical risk condition of mothers during pregnancy impact the health outcomes and the condition of their children

Joshua Lewis (Bioinformatics - Melissa Kemp group)
Reserch Summary: Building computational models of redox biology and disease using multi-omic data.



Peter Audano
Bioinformatics Specialist - University of Washington, Seattle


Robert Chen (CSE- Jimeng Sun group)
Research Summary: Developing machine learning techniques for computational phenotyping and predictive modeling of chronic diseases using electronic medical record data.


Ryan Hoffman (BME - May Wang group)
Research Summary: Investigating new approaches for integrated biomedical informatics across data sources including pathological imaging, bedside monitoring, and electronic health records.


Training Faculty

James Dahlman, Biology, Nanotechnology, genomics, and gene editing,

Greg Gibson, Biology, Quantitative genetics of gene expression and disease,

Michael Goodisman, Biology, Behavioral genetics of social insects, epigenomics,

King Jordan, Biology, Computational genomics, transposable element function,

Kostas Konstantinidis, Biology and Civil and Environmental Engineering, Metagenomics in ecology and disease,

Patrick McGrath, Biology, Fundamental mechanistic studies in C. elegans to identify, predict, and understand how genetic variation impacts the function of the nervous system.

Al Merrill, Biology, Lipidomics, role of sphingolipids in cellular health,

Annalise Paab, Biology, Evolution and quantitative genetics,

Jeffrey Skolnick, Biology, Systems biology, predicting protein-drug interaction,

Todd Streelman, Biology, Evolutionary developmental genomics of dentition, brain,

Fred Vannberg, Biology, GWAS of infectious disease, exosome genome biology,

Joshua Weitz, Biology, Mathematical biology, viral evolution, pattern recognition,

Soojin Yi, Biology, Population genetics and theoretical molecular evolution,

Ed Botchwey, Biomedical Engineering, Tissue engineering, microvasculature, network theory,

Melissa Kemp, Biomedical Engineering, Systems modeling of T cells, single cell profiling,

Manu Platt, Biomedical Engineering, Arterial remodeling in sickle cell, chondrocyte biology,

Eberhard Voit, Biomedical Engineering, Mathematical modeling, systems theory,

May Wang, Biomedical Engineering, Medical image processing, genomic data analysis,

Mark Styczynski, Chemical and Biomolecular Engineering, Metabolomics and systems/network modeling in yeast,

David Bader, Computer Science, High performance computing in biology,

Mark Borodovsky, Computer Science, Bioinformatics, DNA sequence alignment and annotation,

Jimeng Sun, Computer Science, Big data applications for biomedical informatics,

Eva Lee, Industrial and Systems Engineering, Data mining applications in predictive health,

Nicoleta Serban, Industrial and Systems Engineering, Statistical applications in genomics and health systems,

Harold Kim, Physics, Biophysics, transcription factor-DNA interaction,


Executive Committee

Greg Gibson, School of Biology, Training Program Director

King Jordan, School of Biology, Director Bioinformatics Graduate Program

Melissa Kemp, School of Biomedical Engineering

Nicoletta Serbin, School of Industrial and Systems Engineering