High Level Research
Del Vecchio’s group focuses on model-based analysis, design, and control of biomolecular circuits in living cells. The objective of the research is to make genetic circuits more modular, robust to context, and hence make design more scalable. At the same time, we are investigating circuit design approaches that will enable accurate and precise in vivo control of gene expression. One of our target applications is the design of synthetic genetic circuits that accurately control cell fate-determining transcription factor levels, for reprogramming cell fate. Our approach is grounded on rigorous mathematical analysis of physics-based models of biological network dynamics, on the development of new control-theoretic tools for design, and on theory-educated experiments in living cells, from bacterial to mammalian.
Research
Modular design of biological networks
Our current ability of designing synthetic genetic circuits bottom up, that is, our ability to create larger systems from the composition of simpler functional units...
Stochastic behavior
The behavior of biomolecular systems in living cells is noisy due to the intrinsic stochasticity of biochemical reactions. Stochasticity leads to subtle tradeoffs in the design of synthetic circuits...
Genetic feedback controllers to reprogram cell fate
(Post-doc position available for experimental work) The fate of a cell is encoded by a specific signature of transcription factor (TF) levels. Gene regulatory networks (GRNs), in turn, dictate TF levels...
Intelligent Transportation
(Archived- no longer active) We have been working since 2006 on (cooperative) active safety systems to prevent collisions with focus on traffic intersections...
Latest Publications:
The Effect of Loads in Molecular Communications
C. McBride, R. Shah, and D. Del Vecchio
Prc. of the IEEE
Accepted
April 2019
Time-scale separation based design of biomolecular feedback controllers
T. Grunberg and D. Del Vecchio
Submitted
2019
Robustness of reprogramming strategies to small perturbations
R. Shah and D. Del Vecchio
Submitted
2019