ArticleBMC bioinformatics2020
Speeding up the core algorithm for the dual calculation of minimal cut sets in large metabolic networks.
Article in BMC bioinformatics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed, 19 citations in OpenAlex.
- Minimal cut sets in metabolic networks: from conceptual foundations to applications in metabolic engineering and biomedicine.Briefings in bioinformatics · 2025Review
- Convex Representation of Metabolic Networks with Michaelis-Menten Kinetics.Bulletin of mathematical biology · 2024Article
- FastKnock: an efficient next-generation approach to identify all knockout strategies for strain optimization.Microbial cell factories · 2024Article
- Rapid-SL identifies synthetic lethal sets with an arbitrary cardinality.Scientific reports · 2022Article
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Authors and funding
3 authors at 2 institutions in 2 countries.
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Abstract
backgroundThe concept of minimal cut sets (MCS) has become an important mathematical framework for analyzing and (re)designing metabolic networks. However, the calculation of MCS in genome-scale metabolic models is a complex computational problem. The development of duality-based algorithms in the last years allowed the enumeration of thousands of MCS in genome-scale networks by solving mixed-integer linear problems (MILP). A recent advancement in this field was the introduction of the MCS
resultsIn this work, we introduce several new variants and modifications of duality-based MCS algorithms and benchmark their effects on the overall performance. As one major result, we generalize the original MCS
conclusionsOur results further enhance the algorithmic toolbox for MCS calculations and are of general importance for theoretical developments as well as for practical applications of the MCS framework.
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