Literature DB >> 29337084

A graph-based approach to analyze flux-balanced pathways in metabolic networks.

Mona Arabzadeh1, Morteza Saheb Zamani2, Mehdi Sedighi3, Sayed-Amir Marashi4.   

Abstract

An elementary flux mode (EFM) is a pathway with minimum set of reactions that are functional in steady-state constrained space. Due to the high computational complexity of calculating EFMs, different approaches have been proposed to find these flux-balanced pathways. In this paper, an approach to find a subset of EFMs is proposed based on a graph data model. The given metabolic network is mapped to the graph model and decisions for reaction inclusion can be made based on metabolites and their associated reactions. This notion makes the approach more convenient to categorize the output pathways. Implications of the proposed method on metabolic networks are discussed.
Copyright © 2017 Elsevier B.V. All rights reserved.

Keywords:  Elementary flux mode (EFM); Graph data model; Metabolic network

Mesh:

Year:  2018        PMID: 29337084     DOI: 10.1016/j.biosystems.2017.12.001

Source DB:  PubMed          Journal:  Biosystems        ISSN: 0303-2647            Impact factor:   1.973


  4 in total

1.  Finding MEMo: minimum sets of elementary flux modes.

Authors:  Annika Röhl; Alexander Bockmayr
Journal:  J Math Biol       Date:  2019-08-06       Impact factor: 2.259

2.  Boosting the extraction of elementary flux modes in genome-scale metabolic networks using the linear programming approach.

Authors:  Francisco Guil; José F Hidalgo; José M García
Journal:  Bioinformatics       Date:  2020-08-15       Impact factor: 6.937

Review 3.  Review of Machine Learning Methods for the Prediction and Reconstruction of Metabolic Pathways.

Authors:  Hayat Ali Shah; Juan Liu; Zhihui Yang; Jing Feng
Journal:  Front Mol Biosci       Date:  2021-06-17

4.  Improving the EFMs quality by augmenting their representativeness in LP methods.

Authors:  José F Hidalgo; Jose A Egea; Francisco Guil; José M García
Journal:  BMC Syst Biol       Date:  2018-11-20
  4 in total

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