Literature DB >> 25178783

Constraining the flux space using thermodynamics and integration of metabolomics data.

Keng Cher Soh1, Vassily Hatzimanikatis.   

Abstract

Flux balance analysis of stoichiometric metabolic models has become one of the most common methods for estimating intracellular fluxes. However most of these networks are underdetermined and can have multiple alternate optimal flux distributions. Thermodynamic constraints can reduce the solution space significantly and at the same time provide a platform for the integration of metabolomics data. Here we go through the procedure to incorporate thermodynamic constraints and perform thermodynamic analysis of metabolic networks.

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Year:  2014        PMID: 25178783     DOI: 10.1007/978-1-4939-1170-7_3

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  12 in total

1.  The ModelSEED Biochemistry Database for the integration of metabolic annotations and the reconstruction, comparison and analysis of metabolic models for plants, fungi and microbes.

Authors:  Samuel M D Seaver; Filipe Liu; Qizhi Zhang; James Jeffryes; José P Faria; Janaka N Edirisinghe; Michael Mundy; Nicholas Chia; Elad Noor; Moritz E Beber; Aaron A Best; Matthew DeJongh; Jeffrey A Kimbrel; Patrik D'haeseleer; Sean R McCorkle; Jay R Bolton; Erik Pearson; Shane Canon; Elisha M Wood-Charlson; Robert W Cottingham; Adam P Arkin; Christopher S Henry
Journal:  Nucleic Acids Res       Date:  2021-01-08       Impact factor: 16.971

2.  Bioenergetics-based modeling of Plasmodium falciparum metabolism reveals its essential genes, nutritional requirements, and thermodynamic bottlenecks.

Authors:  Anush Chiappino-Pepe; Stepan Tymoshenko; Meriç Ataman; Dominique Soldati-Favre; Vassily Hatzimanikatis
Journal:  PLoS Comput Biol       Date:  2017-03-23       Impact factor: 4.475

3.  pyTFA and matTFA: a Python package and a Matlab toolbox for Thermodynamics-based Flux Analysis.

Authors:  Pierre Salvy; Georgios Fengos; Meric Ataman; Thomas Pathier; Keng C Soh; Vassily Hatzimanikatis
Journal:  Bioinformatics       Date:  2019-01-01       Impact factor: 6.937

4.  Uncertainty reduction in biochemical kinetic models: Enforcing desired model properties.

Authors:  Ljubisa Miskovic; Jonas Béal; Michael Moret; Vassily Hatzimanikatis
Journal:  PLoS Comput Biol       Date:  2019-08-20       Impact factor: 4.475

5.  redGEM: Systematic reduction and analysis of genome-scale metabolic reconstructions for development of consistent core metabolic models.

Authors:  Meric Ataman; Daniel F Hernandez Gardiol; Georgios Fengos; Vassily Hatzimanikatis
Journal:  PLoS Comput Biol       Date:  2017-07-20       Impact factor: 4.475

6.  lumpGEM: Systematic generation of subnetworks and elementally balanced lumped reactions for the biosynthesis of target metabolites.

Authors:  Meric Ataman; Vassily Hatzimanikatis
Journal:  PLoS Comput Biol       Date:  2017-07-20       Impact factor: 4.475

7.  A design-build-test cycle using modeling and experiments reveals interdependencies between upper glycolysis and xylose uptake in recombinant S. cerevisiae and improves predictive capabilities of large-scale kinetic models.

Authors:  Ljubisa Miskovic; Susanne Alff-Tuomala; Keng Cher Soh; Dorothee Barth; Laura Salusjärvi; Juha-Pekka Pitkänen; Laura Ruohonen; Merja Penttilä; Vassily Hatzimanikatis
Journal:  Biotechnol Biofuels       Date:  2017-06-26       Impact factor: 6.040

8.  Synthetic Microbial Ecology: Engineering Habitats for Modular Consortia.

Authors:  Sami Ben Said; Dani Or
Journal:  Front Microbiol       Date:  2017-06-16       Impact factor: 5.640

9.  OptMDFpathway: Identification of metabolic pathways with maximal thermodynamic driving force and its application for analyzing the endogenous CO2 fixation potential of Escherichia coli.

Authors:  Oliver Hädicke; Axel von Kamp; Timur Aydogan; Steffen Klamt
Journal:  PLoS Comput Biol       Date:  2018-09-24       Impact factor: 4.475

10.  Large-scale kinetic metabolic models of Pseudomonas putida KT2440 for consistent design of metabolic engineering strategies.

Authors:  Milenko Tokic; Vassily Hatzimanikatis; Ljubisa Miskovic
Journal:  Biotechnol Biofuels       Date:  2020-02-28       Impact factor: 6.040

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