David S. Tourigny

David S. Tourigny

Assistant Professor (Birmingham Fellow)
School of Mathematics, University of Birmingham

I am a Birmingham Fellow (Assistant Professor equivalent) within the School of Mathematics, University of Birmingham and Affiliate Faculty at the Irving Institute for Cancer Dynamics, Columbia University. Prior to joining the IICD as a Research Scientist 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.

Research

• Computational biology

My general research focus is geared towards understanding the collective behaviour of cellular populations. I have used both experimental and theoretical approaches to study this in a variety of contexts, ranging from microbial systems to neuronal networks. More recently, I have become interested in the way that stochasticity and heterogeneity at the single-cell level contribute to the development of cancer.

• Mathematics

Some 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.

• 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.

Publications

Here is a short list of selected publications. A full list can be found via Google Scholar

• Cellular landscape of adrenocortical carcinoma at single-nuclei resolution
• Molecular characterization of the tumor microenvironment in renal medullary carcinoma
• Simulating single-cell metabolism using a stochastic flux-balance analysis algorithm
• Cooperative metabolic resource allocation in spatially-structured systems
• Dynamic metabolic resource allocation based on the maximum entropy principle
• Energetic substrate availability regulates synchronous activity in an excitatory neural network
• Elongation Factor G bound to the ribosome in an intermediate state of translocation

I have also contributed three chapters to the text book Economic Principles in Cell Biology.

Software

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.

Teaching

I have been involved in the following teaching activities:

• LM Advanced Mathematical Biology (31128) at University of Birmingham Lecture notes
• Mathematics group study sessions for REUK
• Lectures on Mathematical Foundations of Constraint-Based Modelling
at the M2S 2019 course and workshop organised by Felipe Scott and Raul Conejeros
• Supervisions for Mathematics for Natural Sciences at the University of Cambridge

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