David McMillen

faculty_img Academic Title: Associate Professor

Campus: UTM

CSB Appointment: Cross Appointment

Primary Undergraduate Department:
Chemistry, UTM

Graduate Programs:
Cell & Systems Biology

Titles and Honors:

Academic or Administrative Appointments:

Ph.D. University of Toronto 2000


Mailing Address
Department of Cell & Systems Biology
University of Toronto
3359 Mississauga Road
Mississauga, ON L5L 1C6


Contact Information
Office phone: 905-828-5353 
Office: DV 4056 
Lab: DV 5029/5033 
Lab phone: 905-828-3807 
Email: david.mcmillen@utoronto.ca 
URL: http://www.utm.utoronto.ca/~mcmillen/


Research Areas
Bioinformatics & Computational Biology
Quantitative Biology
Synthetic Biology
Systems Biology



The Synthetic Biology and Cellular Control lab works on two broad topics: synthetic biology (design and construction of novel cellular devices in living cells, to alter and control their behaviour) and systems biology (the dynamics and behaviour of cells and cellular networks). To date, our own wet lab work is exclusively in microorganisms (bacteria and yeast), and we are pursuing mammalian cell work through collaboration. * Synthetic biology. The rapidly growing field of synthetic biology represents an effort to implement engineering at the cellular level. We are developing novel regulatory network architectures and new biological “parts” to accomplish a variety of goals. Often our work takes the form of simple proof-of-concept demonstrations, but we are increasingly interested in the potential of synthetic biology to (eventually!) address real-world issues. We are actively engaging with private and public sector partners to learn about key problems that we can use as inspiration for our research direction. Examples of applied projects include efforts at developing systems to: detect disease microorganisms and respond to counter them; develop robust microorganism-based biosensors for blood assays; and engineer metabolic pathways for better production of useful biological products. * Systems biology. Our experimental work is accompanied and guided by modelling at various levels, from detailed biochemical kinetic models (stochastic or deterministic) to higher-level approaches inspired by control theory. However, no individual student is required to be involved in the math/computational side! Within-lab collaborations can be arranged, where one student works entirely on experiments while teaming with someone with a modelling focus.




Design and characterization of a dual-mode promoter with activation and repression capability for tuning gene expression in yeast.Mazumder M, McMillen DR. Nucleic Acids Res. 2014 Jul;


Tuning response curves for synthetic biology.Ang J, Harris E, Hussey BJ, Kil R, McMillen DR. ACS Synth Biol 2013 Oct;2(10):547-67
Physical constraints on biological integral control design for homeostasis and sensory adaptation.Ang J, McMillen DR. Biophys. J. 2013 Jan;104(2):505-15


An active intracellular device to prevent lethal disease outcomes in virus-infected bacterial cells.Bagh S, Mandal M, Ang J, McMillen DR. Biotechnol. Bioeng. 2011 Mar;108(3):645-54


Minimal genetic device with multiple tunable functions.Bagh S, Mandal M, McMillen DR. Phys Rev E Stat Nonlin Soft Matter Phys 2010 Aug;82(2 Pt 1):021911
Considerations for using integral feedback control to construct a perfectly adapting synthetic gene network.Ang J, Bagh S, Ingalls BP, McMillen DR. J. Theor. Biol. 2010 Oct;266(4):723-38


Increasing the efficiency of bacterial transcription simulations: when to exclude the genome without loss of accuracy.Iafolla MA, Dong GQ, McMillen DR. BMC Bioinformatics 2008;9:373
Plasmid-borne prokaryotic gene expression: sources of variability and quantitative system characterization.Bagh S, Mazumder M, Velauthapillai T, Sardana V, Dong GQ, Movva AB, Lim LH, McMillen DR. Phys Rev E Stat Nonlin Soft Matter Phys 2008 Feb;77(2 Pt 1):021919
Effects of protein maturation on the noise in gene expression.Dong GQ, McMillen DR. Phys Rev E Stat Nonlin Soft Matter Phys 2008 Feb;77(2 Pt 1):021908
Dark proteins: effect of inclusion body formation on quantification of protein expression.Iafolla MA, Mazumder M, Sardana V, Velauthapillai T, Pannu K, McMillen DR. Proteins 2008 Sep;72(4):1233-42


Simplification of stochastic chemical reaction models with fast and slow dynamics.Dong GQ, Jakobowski L, Iafolla MA, McMillen DR. J Biol Phys 2007 Feb;33(1):67-95


Systematic reduction of a stochastic signalling cascade model.Dong CG, Jakobowski L, McMillen DR. J Biol Phys 2006 Oct;32(2):173-6
Extracting biochemical parameters for cellular modeling: A mean-field approach.Iafolla MA, McMillen DR. J Phys Chem B 2006 Nov;110(43):22019-28