Niall Mangan Data-driven mathematical modeling for understanding complex systems

Research Interests

For many biological systems we can write down a comprehensive set of equations that captures all possible mechanisms of interest – diffusion, active transport, chemical reactions of varying forms, "stickiness," etc. However, only a few of these mechanisms are expected to be important at a given time. I develop methods to discover reduced models in a data-driven way by combining statistical and machine-learning approaches with mechanistic modeling. I have a few ongoing projects in this area:
  • Modeling the natural and bioengineered spatial organization of enzymes in cells to enhance throughput of biochemical pathways, especially for the production of biofuels, alternatives to plastic, and other high-value products
  • Discovering the "minimal" biochemical network to describe an organism's metabolism across varying external and developmental conditions
  • Inferring the structure and dynamics of biological networks using methods that bridge the gap between -omic level studies and models for small metabolic or regulatory networks

Selected Publications

Model selection for hybrid dynamical systems via sparse regression. Mangan NM, Askham T, Brunton SL, Kutz JN, and Proctor JL. Proc. of the Royal Society A. 2019 March 1;475(2223):20180534.

Spatially organizing biochemistry: choosing a strategy to translate synthetic biology to the factory. Jakobson CM, Tullman-Ercek D, and Mangan NM. Scientific Reports. 2018 May 29;8:8196.

A systems-level model reveals that 1,2-Propanediol utilization microcompartments enhance pathway flux through intermediate sequestration. Jakobson CM, Tullman-Ercek D, Slininger MF, and Mangan NM. PLoS Computational Biology. 2017 May 5;13(5):e1005525.

pH determines the energetic efficiency of the cyanobacterial COconcentrating mechanism. Mangan NM, Flamholz A, Hood RD, Milo R, and Savage DF. PNAS. 2016 September 6;113(36):E5354-E5362.

Inferring Biological Networks by Sparse Identification of Nonlinear Dynamics. Mangan NM, Brunton SL, Proctor JL, and Kutz JN. IEEE Transactions on Molecular, Biological and Multi-Scale Communications. 2016 June;2(1):52-63.

View all publications by Niall M. Mangan listed in Google Scholar.