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hannahtro/Loopless_Fluxes_with_Mixed_Integer_Optimization

Authors: Hannah Troppens, Mathieu Besançon, St. Elmo Wilken, and Sebastian Pokutta

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Hannah Troppens, Mathieu Besançon, St. Elmo Wilken, Sebastian Pokutta. hannahtro/Loopless_Fluxes_with_Mixed_Integer_Optimization (Software). Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@misc{dagstuhl-artifact-23824,
   title = {{hannahtro/Loopless\underlineFluxes\underlinewith\underlineMixed\underlineInteger\underlineOptimization}}, 
   author = {Troppens, Hannah and Besan\c{c}on, Mathieu and Wilken, St. Elmo and Pokutta, Sebastian},
   note = {Software, swhId: \href{https://archive.softwareheritage.org/swh:1:dir:9c41495c7f2ecd9e7459fa0c51d4be32fa0c033e}{\texttt{swh:1:dir:9c41495c7f2ecd9e7459fa0c51d4be32fa0c033e}} (visited on 2025-07-15)},
   url = {https://github.com/hannahtro/Loopless_Fluxes_with_Mixed_Integer_Optimization},
   doi = {10.4230/artifacts.23824},
}

Document

DOI: 10.4230/LIPIcs.SEA.2025.26

Mixed-Integer Optimization for Loopless Flux Distributions in Metabolic Networks

Authors: Hannah Troppens, Mathieu Besançon, St. Elmo Wilken, and Sebastian Pokutta

Published in: LIPIcs, Volume 338, 23rd International Symposium on Experimental Algorithms (SEA 2025)

Abstract

Constraint-based metabolic models can be used to investigate the intracellular physiology of microorganisms. These models couple genes to reactions, and typically seek to predict metabolite fluxes that optimize some biologically important metric. Classical techniques, like Flux Balance Analysis (FBA), formulate the metabolism of a microbe as an optimization problem where growth rate is maximized. While FBA has found widespread use, it often leads to thermodynamically infeasible solutions that contain internal cycles (loops). To address this shortcoming, Loopless-Flux Balance Analysis (ll-FBA) seeks to predict flux distributions that do not contain these loops. ll-FBA is a disjunctive program, usually reformulated as a mixed-integer program, and is challenging to solve for biological models that often contain thousands of reactions and metabolites. In this paper, we compare various reformulations of ll-FBA and different solution approaches. Overall, the combinatorial Benders' decomposition is the most promising of the tested approaches with which we could solve most instances. However, the model size and numerical instability pose a challenge to the combinatorial Benders' method.

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Hannah Troppens, Mathieu Besançon, St. Elmo Wilken, and Sebastian Pokutta. Mixed-Integer Optimization for Loopless Flux Distributions in Metabolic Networks. In 23rd International Symposium on Experimental Algorithms (SEA 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 338, pp. 26:1-26:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{troppens_et_al:LIPIcs.SEA.2025.26,
  author =	{Troppens, Hannah and Besan\c{c}on, Mathieu and Wilken, St. Elmo and Pokutta, Sebastian},
  title =	{{Mixed-Integer Optimization for Loopless Flux Distributions in Metabolic Networks}},
  booktitle =	{23rd International Symposium on Experimental Algorithms (SEA 2025)},
  pages =	{26:1--26:18},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-375-1},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{338},
  editor =	{Mutzel, Petra and Prezza, Nicola},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SEA.2025.26},
  URN =		{urn:nbn:de:0030-drops-232646},
  doi =		{10.4230/LIPIcs.SEA.2025.26},
  annote =	{Keywords: Systems biology, mixed-integer optimization, disjunctive optimization, flux balance analysis}
}

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Documents authored by Troppens, Hannah

hannahtro/Loopless_Fluxes_with_Mixed_Integer_Optimization

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Mixed-Integer Optimization for Loopless Flux Distributions in Metabolic Networks

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