David S. Tourigny

Research Scientist at Irving Institute for Cancer Dynamics
Columbia University, New York

I am a Research Scientist at the Irving Institute for Cancer Dynamics, Columbia University working with Simon Tavare and Ed Reznik. Prior to joining the IICD in September 2020, I held a Research Fellowship from the Simons Foundation and LSRF hosted by the Columbia University Irving Medical Centre. Before that, I was a Research Fellow in the Department of Applied Mathematics and Theoretical Physics, University of Cambridge where I also completed my PhD under the supervision of Venki Ramakrishnan and Garib Murshudov at the MRC Laboratory of Molecular Biology as a member of Trinity College.


  • Computational biology

  • My current research focus is on understanding the dynamic regulation of metabolism in space and time. I have used both experimental and theoretical approaches to study metabolism in a variety of contexts, ranging from microbial systems to neuronal networks. More recently, I have become interested in the way that stochasticity at the single-cell level and metabolic population heterogeneity contribute to phenomena such as microbial 'bet-hedging' or development of human diseases like cancer (see Publications and this video presentation for details on a current project). Having previously worked on the ribosome during my PhD, I have a longer-term ambition to explore the integration of metabolism with protein synthesis as one of the most energy-demanding processes inside the cell.

  • Mathematics

  • Most of my work involves mathematical and computational modelling based on Applied Dynamical Systems Theory and Constrained Optimisation. In the past, I also have worked on these topics in their own right with relatively less application. Specifically, this involved some geometric properties of certain dynamical systems (see Publications).

  • Scientific software

  • I am continually developing software tools for my own research purposes as well as the wider scientific community. See Software for more information.


I develop and maintain the Python/C++ package dfba (see also paper here) for dynamic flux-balance analysis (DFBA) simulations. This is joint work with Moritz E. Beber and Jorge Carrasco Muriel that forms part of the openCOBRA code base for constraint-based reconstruction and analysis of metabolic models.

Other software and scripts for data processing can be accessed via GitLab.

During my PhD I worked on a maximum likelihood-based algorithm for clustering and inferring diffraction data from macromolecular crystals (today, this would probably be called machine learning). Details can be found in the second section of my thesis.


I have been involved in a small amount of teaching:

  • Lecture on Mathematical Foundations of Constraint-Based Modelling at the M2S 2019 course and workshop organised by Felipe Scott and Raul Conejeros. Slides from the lecture are available here
  • Supervisions for the course Mathematics for Natural Sciences at the University of Cambridge