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Updated: Dec 24, 2025

High-Throughput Metabolic Profiling for Model Refinements of Microalgae
Published on: December 4, 2021
SWIFTCORE: a tool for the context-specific reconstruction of genome-scale metabolic networks
Mojtaba Tefagh1, Stephen P Boyd2
1Information Systems Laboratory, Department of Electrical Engineering, Stanford University, Stanford, US. mtefagh@stanford.edu.
Background:
High-throughput omics technologies have enabled the comprehensive reconstructions of genome-scale metabolic networks for many organisms. However, only a subset of reactions is active in each cell which differs from tissue to tissue or from patient to patient. Reconstructing a subnetwork of the generic metabolic network from a provided set of context-specific active reactions is a demanding computational task.
Results:
We propose SWIFTCC and SWIFTCORE as effective methods for flux consistency checking and the context-specific reconstruction of genome-scale metabolic networks which consistently outperform the previous approaches.
Conclusions:
We have derived an approximate greedy algorithm which efficiently scales to increasingly large metabolic networks. SWIFTCORE is freely available for non-commercial use in the GitHub repository at https://mtefagh.github.io/swiftcore/.
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