Professor, Department of Molecular Biology, School of Biological Sciences
Computational genomics and the dynamics of gene regulatory networks which control cell function.
Jeff Hasty engineers synthetic gene networks in order to gain insight into the general modules of gene regulation. These modules include subnetworks that act as switches or oscillators, as well as networks that communicate across a population of cells. The work provides a framework for predicting and evaluating basic gene regulatory motifs that govern protein production at the genomic level. Hasty develops and uses mathematical models to analyze gene networks and employs experimental techniques to construct the networks according to the model blueprint. For example, he has developed a model of a positive feedback loop, in which a gene produces a protein which in turn causes that gene to become more active. He has confirmed this model in experimental studies with E-coli. Hasty believes there are many such modular mechanisms that taken together, control the function of cells. Understanding genetic networks is a first step towards logically controlling and monitoring the function of cells. Hasty's long-term goal is to build synthetic genetic switches or oscillators which could be inserted into a patient's cells to tightly regulate the expression of a desired protein, or even to cause an undesirable cell to self-destruct. Hasty has been an invited speaker on gene regulatory networks at more than 20 professional meetings, and his work has been covered in the popular press including CNN and Business Week.
Prior to joining UCSD in 2002, Jeff Hasty was an Assistant Research Professor in the Biomedical Engineering Department at Boston University. He received a Ph.D. in physics from GeorgiaTech in 1997, and went on to serve as a lecturer at Georgia Tech and post-doctoral fellow at the Supercomputing Research Institute at Florida State University before joining Boston University. A promising biophysicist/mathematical biologist, Hasty's research on gene networks is supported by DARPA, NSF, and the Fetzer Institute.