Jeff Gore is an Associate Professor in the Department of Physics at the Massachusetts Institute of Technology. He leads the Ecological Systems Biology Group, which uses laboratory microcosms to explore the ecological dynamics of interacting populations. Of particular interest are cooperatively growing populations, which can collapse suddenly in deteriorating environments and can also be susceptible to the emergence of “cheater” strategies.
He studied physics, mathematics, and economics at MIT before earning his Ph.D. in Physics at the University of California, Berkeley as a Hertz Fellow studying single-molecule biophysics with Carlos Bustamante. He then returned to MIT as a Pappalardo Fellow, where he used ideas from game theory to explore the evolution of cooperation and cheating with Prof. Alexander van Oudenaarden. Jeff is an NIH New Innovator Awardee, Allen Distinguished Investigator, Sloan Fellow, Pew Scholar in the Biomedical Sciences, and NSF CAREER Awardee. Finally, his efforts in teaching and mentoring have been recognized by the Buechner Teaching Award and the MIT-wide undergraduate research Faculty Mentor of the Year Award.
Research
The Gore biophysics laboratory uses microbial populations to explore how interactions within a population or community can lead to rich emergent phenomena.
Behavior of populations before collapse – Natural populations can collapse suddenly in deteriorating environmental conditions, and recovery after such a collapse can be exceedingly difficult. Theory predicts that in principle changes in the fluctuations of the population size can be used to anticipate an impending "tipping point" leading to population collapse. Our group has used laboratory yeast populations to experimentally measure these theoretically predicted early warning indicators based on critical slowing down (Dai et al, Science (2012)). In addition to changes in the temporal behavior, we have also found that characteristic spatial patterns emerge near a tipping point (Dai et al, Nature (2013)). These early warning indicators can be observed in producer-freeloader communities as well as in different environmental deteriorations (Chen et al, Nature Communications (2014); Dai et al, PNAS (2015)). On an entirely different scale, we have also found that cell memory loses resilience to environmental perturbations approaching such a critical transition (Axelrod et al, eLife (2015)). More recently, we have collaborated with field ecologists to explore these dynamics in intertidal marine communities and in honey bee colonies, suggesting that critical slowing down provides a powerful framework for studying sudden transitions in a wide range of biological systems.
For more information please visit http://www.gorelab.org/