Balázsi Research Lab
Gábor Balázsi, PhD
- Henry Laufer Professor, The Louis and Beatrice Laufer Center for Physical and Quantitative Biology
- Professor, Department of Biomedical Engineering
Office: (631) 632-5414
Email: gabor.balazsi@stonybrook.edu
Stony Brook University115C Laufer Center
Stony Brook, NY 11794-5252
Research Program
Departments
- The Louis and Beatrice Laufer Center for Physical and Quantitative Biology
- Department of Biomedical Engineering
Research Interest
The goal of my laboratory is to combine synthetic and evolutionary biology to develop a predictive, quantitative understanding of cancer-related processes such as metastasis-relevant cellular decision-making and the survival and evolution of cell populations during drug treatment. We have been pursuing two main research directions:
- Computational modeling and co-analyzing natural gene and protein networks with genome-scale data
- Designing, building and experimentally characterizing synthetic gene circuits in adapting and evolving mammalian (including human cancer) cell lines.
Our current goal is to merge these two efforts and use synthetic gene circuits as perturbation tools to understand how gene regulatory networks adapt and evolve as they control cancer cell populations.
In the past, we mapped gene regulatory network responses to environmental changes; we showed how nongenetic cellular diversity can aid cell survival and mediate drug resistance; we built various synthetic gene circuits to control nongenetic cellular variability; we built “dimmer” or “linearizer” gene circuits for precise gene expression tuning; we developed computational models of natural and synthetic gene regulatory networks affecting drug resistance and metastasis; and we have confirmed computational predictions of evolutionary dynamics by experimental evolution of cells carrying synthetic gene circuits, bridging the fields of synthetic and evolutionary biology. Now we are interfacing natural gene networks with synthetic gene circuits to study how short-term and evolutionary dynamics of cancer cell populations affects cellular phenotypes relevant to metastasis and drug resistance, with suggestions for potential new therapeutic approaches against cancer drug resistance.
Education
- PhD, Physics, University of Missouri at Saint Louis & Missouri S&T at Rolla, USA
- MS, Physics, University of Missouri at Saint Louis, USA
- MS, Magnetism, Babeş-Bolyai University of Cluj, Romania
- BS, Physics, Babeş-Bolyai University of Cluj, Romania