© NARAYAN MAHON/WONDERFUL MACHINEBioengineer Jennifer Reed probably wouldn’t have become a rising star in the field of metabolic modeling if it weren’t for Andrew McCulloch, the University of California, San Diego (UCSD), prof who taught her undergraduate statistics course. McCulloch advised the young Reed to pursue a PhD. “You should never talk anyone into doing a PhD,” he says, “but [Reed] clearly had the intellect and everything it would take to become the outstanding scientist she’s turned out to be.”
METHODS: The daughter and granddaughter of engineers, Reed gravitated naturally toward problem solving. “I was always just kind of interested in how things work,” she says. That penchant for tinkering found expression in UCSD’s bioengineering program. After two internships—one at a chemical engineering company and one at the National Institutes of Health in Maryland—she set off for graduate school, prepared to devote her life to research and the “intellectual freedom that comes with it.”
Reed secured a spot in the lab of UCSD systems biologist Bernhard Palsson, who had been similarly impressed with her when she took his undergrad class on modeling metabolism, a class that Reed says “really got me intrigued that you can take something as inherently complex as a cell and predict how that cell will behave using math.” RESULTS: In Palsson’s lab, Reed focused on the computational biology necessary to model the enzymatic pathways involved in E. coli metabolism, but also tested her predictions in the wet lab—a dualism that continues to mark her approach to studying the mechanics of metabolism. She led a successful effort to construct the most complete, genome-scale metabolic model of E. coli (named iJR904 in her honor) of the time, ...
