McMillen, David R.
Contact Information
3359 Mississauga Road North
Mississauga, Ontario
L5L 1C6
Research
We apply a combination of experimental and theoretical techniques to study the internal dynamics of cells, with specific reference to processes such as gene expression and regulation. Working in simple organisms as such a bacteria allows us to address simplified systems by constructing our own novel genetic regulatory networks, inserting them into living cells, and comparing their behaviour to that of theoretical/computational models of biochemical reaction kinetics. We also have a program in synthetic biology, where we are interested in using these simplified genetic networks as controllers designed to alter the internal dynamics of cells in predictable ways, with the long-term goal being the ability to carry out medical interventions from inside the cell.
Publications
Jordan Ang, Brian Ingalls, and David R. McMillen (2011). Probing the input-output behavior of biological systems: system identification methods from control theory. Methods in Enzymology 487 (Computer Methods, Part C): 279-317.
Sangram Bagh, Mahuya Mandal, and David R. McMillen (2011). An active intracellular device to prevent lethal viral effects in bacteria. Biotechnology and Bioengineering 108(3): 645-654.
Jordan Ang, Sangram Bagh, Brian P. Ingalls, and David R. McMillen (2010). Considerations for using integral feedback control to construct a perfectly adapting synthetic gene network. Journal of Theoretical Biology 266(4): 723-738. (published online at here).
Sangram Bagh, Mahuya Mandal, and David R. McMillen (2010). Minimal genetic device with multiple tunable functions. Physical Review E 82(2): 021911. (published online here).
Sangram Bagh and David R. McMillen (2009). A synthetic genetic circuit whose signal-response curve is temperature-tunable from band-detection to sigmoidal behaviour. Natural Computing (published online (.pdf) here).
Marco Iafolla, Mostafizur Mazumder, Vandit Sardana, Tharsan Velauthapillai, Karanbir Pannu, and David R. McMillen (2008). Dark proteins: inclusion body quantification. Proteins: structure, function, and bioinformatics 72: 1233-1242.
Sangram Bagh, Mostafizur Mazumder, Tharsan Velauthapillai, Vandit Sardana, Guang Qiang Dong, Ashok B. Movva, Len H. Lim, and David R. McMillen (2008). Plasmid-borne prokaryotic gene expression: sources of variability and quantitative system characterization. Physical Review E 77: 021919.
Guang Qiang Dong and David R. McMillen (2008). Effects of protein maturation on the noise in gene expression. Physical Review E 77: 021908
Marco Iafolla, Guang Qiang Dong, and David R. McMillen (2008). Increasing the accuracy of bacterial transcription simulations: when to exclude the genome without loss of accuracy. BMC Bioinformatics 9: 373.
Guang Qiang Dong, Luke Jakobowski, Marco Iafolla, and David R. McMillen (2007). Simplification of stochastic chemical reaction models with fast and slow dynamics. Journal of Biological Physics 32: 67-95.
Marco A. J. Iafolla and David R. McMillen (2006). Extracting biochemical parameters for cellular modeling: A ‘mean-field’ approach. Journal of Physical Chemistry-B 110: 22019-22028.
Guang Qiang Dong, Luke Jakobowski, and David R. McMillen (2006). Systematic reduction of a stochastic signalling cascade model. Journal of Biological Physics 32: 173-176.
Nicholas Guido, Xiao Wang, David Adalsteinsson, David R. McMillen, Jeff Hasty, Charles Cantor, Timothy Elston, and James Collins (2006). A bottom-up approach to gene regulation. Nature 439: 856-860.
David Adalsteinsson, David R. McMillen, and Timothy C Elston (2004).Biochemical Network Stochastic Simulator (BioNetS): Software for Stochastic Modeling of Biochemical Networks. BioMed Central (BMC) Bioinformatics 5:24.