IGERT Student Profile: W. Garrett Jenkinson
Garrett Jenkinson. Credit: Mary Spiro/JHU
Trying to fit complex experimental data gathered by scientists and engineers into predictable mathematical models has proved challenging, if not impossible, for computer engineers and mathematicians. Yet this daunting task has provided an exciting research puzzle for W. Garrett Jenkinson, a doctoral student in Electrical and Computer Engineering. Jenkinson is an IGERT* fellow with the Johns Hopkins Institute for NanoBioTechnology as well as a National Defense Science and Engineering Graduate Fellow with the U.S. Department of Defense.
Jenkinson explains that, in mathematics, linearity is an important concept because the output “y“ changes proportionally to the input “x.“
“Systems with many linear components are simple to analyze because their effects combine in a predictable fashion,“ he says.
But when the components are nonlinear—which describes most situations in nature—their combined effects become much less clear and much more difficult to analyze.
“It is very difficult to model things in a nonlinear system that is dynamic in time,“ Jenkinson says. In trying to find a specific model for these nonlinear dynamics, he explains, mathematicians tend to want to ignore certain variables. “But to be accurate, you can’t always assume things that are not true in real life,“ he adds.
Nonlinear system models could be used to calculate the pathways brain cells use to communicate, or the speed with which a disease spreads through a population, or even to predict the weather. “Physicists, cell biologists, and epidemiologists all are attempting to model nonlinear systems,“ Jenkinson says. In reading the current literature on nonlinear system modeling from across these disciplines, Jenkinson says, “it has been difficult to extract the fundamental mathematical principles of these networks.“
Working in the lab of John Goutsias, professor of Electrical and Computer Engineering and affiliated faculty member of INBT, Jenkinson focuses his study on nonlinear systems for modeling chemical reaction pathways in cells. By modeling how molecules interact given different concentrations of stimuli over time, he hopes to then compare how a defective cell—like a cancer cell—might behave differently. This knowledge could provide information for drug targets and relates to the research of Jenkinson’s co-advisor, Konstantinos Konstantopoulos, professor and chair of Chemical and Biomolecular Engineering and INBT affiliated faculty member.
Although his math skills are impressive, Jenkinson says he’s got a lot to learn about the biological sciences. “It has been helpful to be in the INBT journal clubs and to talk about biology and chemistry. It is nice to see it all integrated,“ he says.
Before coming to Hopkins, Jenkinson earned both a Bachelor’s and Master’s in Electrical and Computer Engineering from Carnegie Mellon University, where he developed an interest in applying mathematics to biological problems. In addition to his doctoral work at Hopkins, he will earn an additional Master’s in Applied Mathematics and Statistics. Ultimately, he plans to conduct research and says he would enjoy teaching.
A native of Stuart, Fla., Jenkinson plays hockey, rugby and lacrosse and is an avid surfer.
*IGERT stands for Integrative Graduate Education and Research Traineeship and is funded by the National Science Foundation.
To learn more about the Goutsias Lab, go to http://cis.jhu.edu/~goutsias/
To learn more about the Konstantopoulos Lab, go to http://www.jhu.edu/chembe/kostas/
For details on the NanoBio IGERT, visit http://inbt.jhu.edu/igert.php
Story by Mary Spiro
