Professor David McMillen

David R. McMillen

Associate Professor


Campus

UTM

CSB Appointment

Full

Research Areas

Bioinformatics / Computational Biology, Biotechnology, Quantitative Biology /Modelling, Systems Biology

Education

Ph.D. University of Toronto 2000

Primary Undergraduate Department

Chemistry, UTM

Graduate Programs

Cell & Systems Biology

Research Description

Systems and synthetic biology. Design, construction, and analysis of synthetic networks (feedback controllers, logical operators, etc.) in microorganisms and (through collaboration) mammalian cells, to alter cellular behaviour from within.


Contact Information

Office Phone: 905-828-5353
Office: DV4056
Lab: DV5029/DV5033
Lab Phone: 905-828-3807
Email

Mailing Address

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

Visit lab’s website


Publications

2014

Design and characterization of a dual-mode promoter with activation and repression capability for tuning gene expression in yeast

Mazumder M, McMillen DR
2014, Nucleic acids research, 25056312

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2013

Tuning response curves for synthetic biology

Ang J, Harris E, Hussey BJ, Kil R, McMillen DR
2013, ACS synthetic biology, 2, 547-67, 23905721

Physical constraints on biological integral control design for homeostasis and sensory adaptation

Ang J, McMillen DR
2013, Biophysical journal, 104, 505-15, 23442873

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2010

An active intracellular device to prevent lethal disease outcomes in virus-infected bacterial cells

Bagh S, Mandal M, Ang J, McMillen DR
2011, Biotechnology and bioengineering, 108, 645-54, 20967799

Minimal genetic device with multiple tunable functions

Bagh S, Mandal M, McMillen DR
2010, Physical review. E, Statistical, nonlinear, and soft matter physics, 82, 021911, 20866841

Considerations for using integral feedback control to construct a perfectly adapting synthetic gene network

Ang J, Bagh S, Ingalls BP, McMillen DR
2010, Journal of theoretical biology, 266, 723-38, 20688080

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2008

Increasing the efficiency of bacterial transcription simulations: when to exclude the genome without loss of accuracy

Iafolla MA, Dong GQ, McMillen DR
2008, BMC bioinformatics, 9, 373, 18789148

Dark proteins: effect of inclusion body formation on quantification of protein expression

Iafolla MA, Mazumder M, Sardana V, Velauthapillai T, Pannu K, McMillen DR
2008, Proteins, 72, 1233-42, 18350571

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
2008, Physical review. E, Statistical, nonlinear, and soft matter physics, 77, 021919, 18352063

Effects of protein maturation on the noise in gene expression

Dong GQ, McMillen DR
2008, Physical review. E, Statistical, nonlinear, and soft matter physics, 77, 021908, 18352052

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2007

Simplification of stochastic chemical reaction models with fast and slow dynamics

Dong GQ, Jakobowski L, Iafolla MA, McMillen DR
2007, Journal of biological physics, 33, 67-95, 19669554

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2006

Extracting biochemical parameters for cellular modeling: A mean-field approach

Iafolla MA, McMillen DR
2006, The journal of physical chemistry. B, 110, 22019-28, 17064172

Systematic reduction of a stochastic signalling cascade model

Dong CG, Jakobowski L, McMillen DR
2006, Journal of biological physics, 32, 173-6, 19669460

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