1.
2.
3.
4.
5.
6.
7.
8.
Bordbar, A.; Yurkovich, J.T.; Paglia, G.; Rolfsson, O.; Sigurjónsson, Ó.E.; Palsson, B.O. Elucidating dynamic metabolic physiology
through network integration of quantitative time-course metabolomics. Sci. Rep. 2017, 7, 46249. [CrossRef]
Beal, L.D.R.; Hill, D.C.; Martin, R.A.; Hedengren, J.D. GEKKO Optimization Suite. Processes 2018, 6, 106. [CrossRef]
Kamsen, R.; Kalapanulak, S.; Chiewchankaset, P.; Saithong, T. Transcriptome integrated metabolic modeling of carbon assimilation
underlying storage root development in cassava. Sci. Rep. 2021, 11, 8758. [CrossRef]
Di Filippo, M.; Pescini, D.; Galuzzi, B.G.; Bonanomi, M.; Gaglio, D.; Mangano, E.; Consolandi, C.; Alberghina, L.; Vanoni, M.;
Damiani, C. INTEGRATE: Model-based multi-omics data integration to characterize multi-level metabolic regulation. PLoS
Comput. Biol. 2022, 18, e1009337. [CrossRef] [PubMed]
Zhao, J.; Shimizu, K. Metabolic flux analysis of Escherichia coli K12 grown on 13C-labeled acetate and glucose using GC-MS and
powerful flux calculation method. J. Biotechnol. 2003, 101, 101–117. [CrossRef] [PubMed]
Ishii, N.; Nakahigashi, K.; Baba, T.; Robert, M.; Soga, T.; Kanai, A.; Hirasawa, T.; Naba, M.; Hirai, K.; Hoque, A.; et al. Multiple
high-throughput analyses monitor the response of E. coli to perturbations. Science 2007, 316, 593–597. [CrossRef] [PubMed]
Toya, Y.; Ishii, N.; Nakahigashi, K.; Hirasawa, T.; Soga, T.; Tomita, M.; Shimizu, K. 13C-metabolic flux analysis for batch culture of
Escherichia coli and its Pyk and Pgi gene knockout mutants based on mass isotopomer distribution of intracellular metabolites.
Biotechnol. Prog. 2010, 26, 975–992. [CrossRef]
Maeda, K.; Okahashi, N.; Toya, Y.; Matsuda, F.; Shimizu, H. Investigation of useful carbon tracers for 13C-metabolic flux analysis
of Escherichia coli by considering five experimentally determined flux distributions. Metab. Eng. Commun. 2016, 3, 187–195.
[CrossRef]
Bioengineering 2023, 10, 636
9.
10.
11.
12.
13.
14.
15.
16.
17.
18.
19.
20.
21.
22.
23.
24.
25.
26.
27.
28.
29.
30.
11 of 11
Okahashi, N.; Kajihata, S.; Furusawa, C.; Shimizu, H. Reliable Metabolic Flux Estimation in Escherichia coli Central Carbon
Metabolism Using Intracellular Free Amino Acids. Metabolites 2014, 4, 408–420. [CrossRef]
Crown, S.B.; Long, C.P.; Antoniewicz, M.R. Integrated 13C-metabolic flux analysis of 14 parallel labeling experiments in Escherichia
coli. Metab. Eng. 2015, 28, 151–158. [CrossRef]
Van Dien, S.; Iwatani, S.; Usuda, Y.; Matsui, K.; Ueda, T.; Tsuji, Y. Method for Determining Metabolic Flux Affecting Substance
Production. U.S. Patent 7,809,511 B2, 5 October 2010.
Klamt, S.; Schuster, S. Calculating as many fluxes as possible in underdetermined metabolic networks. Mol. Biol. Rep. 2002,
29, 243–248. [CrossRef]
Bogaerts, P.; Vande Wouwer, A. How to Tackle Underdeterminacy in Metabolic Flux Analysis? A Tutorial and Critical Review.
Processes 2021, 9, 1577. [CrossRef]
Fallahi, S.; Skaug, H.J.; Alendal, G. A comparison of Monte Carlo sampling methods for metabolic network models. PLoS ONE
2020, 15, e0235393. [CrossRef] [PubMed]
Kaufman, D.E.; Smith, R.L. Direction choice for accelerated convergence in hit-and-run sampling. Oper. Res. 1998, 46, 84–95.
[CrossRef]
Haraldsdottir, H.S.; Cousins, B.; Thiele, I.; Fleming, R.M.T.; Vempala, S. CHRR: Coordinate hit-and-run with rounding for uniform
sampling of constraint-based models. Bioinformatics 2017, 33, 1741–1743. [CrossRef] [PubMed]
Megchelenbrink, W.; Huynen, M.; Marchiori, E. optGpSampler: An improved tool for uniformly sampling the solution-space of
genome-scale metabolic networks. PLoS ONE 2014, 9, e86587. [CrossRef]
Orth, J.D.; Thiele, I.; Palsson, B.Ø. What is flux balance analysis? Nat. Biotechnol. 2010, 28, 245–248. [CrossRef]
Burgard, A.P.; Vaidyaraman, S.; Maranas, C.D. Minimal reaction sets for Escherichia coli metabolism under different growth
requirements and uptake environments. Biotechnol. Prog. 2001, 17, 791–797. [CrossRef]
Herrmann, H.A.; Dyson, B.C.; Vass, L.; Johnson, G.N.; Schwartz, J.M. Flux sampling is a powerful tool to study metabolism under
changing environmental conditions. npj Syst. Biol. Appl. 2019, 5, 32. [CrossRef]
Scott, W.T.; Smid, E.J.; Block, D.E.; Notebaart, R.A. Metabolic flux sampling predicts strain-dependent differences related to aroma
production among commercial wine yeasts. Microb. Cell Fact. 2021, 20, 204. [CrossRef]
Orth, J.D.; Conrad, T.M.; Na, J.; Lerman, J.A.; Nam, H.; Feist, A.M.; Palsson, B.Ø. A comprehensive genome-scale reconstruction
of Escherichia coli metabolism—2011. Mol. Syst. Biol. 2011, 7, 535. [CrossRef]
Ebrahim, A.; Lerman, J.A.; Palsson, B.Ø.; Hyduke, D.R. COBRApy: COnstraints-Based Reconstruction and Analysis for Python.
BMC Syst. Biol. 2013, 7, 74. [CrossRef]
Mugavin, M.E. Multidimensional scaling: A brief overview. Nurs. Res. 2008, 57, 64–68. [CrossRef] [PubMed]
Beyß, M.; Azzouzi, S.; Weitzel, M.; Wiechert, W.; Nöh, K. The Design of FluxML: A Universal Modeling Language for 13C
Metabolic Flux Analysis. Front. Microbiol. 2019, 10, 1022. [CrossRef] [PubMed]
Chalkis, A.; Fisikopoulos, V. Volesti: Volume Approximation and Sampling for Convex Polytopes in R. arXiv 2020,
arXiv:2007.01578. [CrossRef]
Chevallier, A.; Cazals, F.; Fearnhead, P. Efficient Computation of the Volume of a Polytope in High-Dimensions Using Piecewise
Deterministic Markov Processes. In Proceedings of the 25th International Conference on Artificial Intelligence and Statistics, Virtual, 28–30 March 2022; Volume 151, pp. 10146–10160. Available online: https://proceedings.mlr.press/v151/chevallier22a.html
(accessed on 12 April 2023).
Hubbard, J.A.; Lewandowska, K.B.; Hughes, M.N.; Poole, R.K. Effects of iron-limitation of Escherichia coli on growth, the
respiratory chains and gallium uptake. Arch. Microbiol. 1986, 146, 80–86. [CrossRef]
Pourciau, C.; Pannuri, A.; Potts, A.; Yakhnin, H.; Babitzke, P.; Romeo, T. Regulation of Iron Storage by CsrA Supports Ex-ponential
Growth of Escherichia coli. mBio 2019, 10, e01034-19. [CrossRef] [PubMed]
Gerken, H.; Vuong, P.; Soparkar, K.; Misra, R. Roles of the EnvZ/OmpR Two-Component System and Porins in Iron Acquisition
in Escherichia coli. mBio 2020, 11, e01192-20. [CrossRef] [PubMed]
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