Model validation and selection in metabolic flux analysis and flux balance analysis

Kaste, Joshua A. M.; Shachar‐Hill, Yair

doi:10.1002/btpr.3413

Model validation and selection in metabolic flux analysis and flux balance analysis

Journal Article · Fri Nov 24 00:00:00 EST 2023 · Biotechnology Progress

DOI:https://doi.org/10.1002/btpr.3413· OSTI ID:2221867

^[1]; Shachar‐Hill, Yair ^[1]

Michigan State Univ., East Lansing, MI (United States)

13C-Metabolic Flux Analysis (13C-MFA) and Flux Balance Analysis (FBA) are widely used to investigate the operation of biochemical networks in both biological and biotechnological research. Both methods use metabolic reaction network models of metabolism operating at steady state so that reaction rates (fluxes) and the levels of metabolic intermediates are constrained to be invariant. They provide estimated (MFA) or predicted (FBA) values of the fluxes through the network in vivo, which cannot be measured directly. These fluxes can shed light on basic biology and have been successfully used to inform metabolic engineering strategies. Several approaches have been taken to test the reliability of estimates and predictions from constraint-based methods and to compare alternative model architectures. Despite advances in other areas of the statistical evaluation of metabolic models, such as the quantification of flux estimate uncertainty, validation and model selection methods have been underappreciated and underexplored. We review the history and state-of-the-art in constraint-based metabolic model validation and model selection. Applications and limitations of the χ²-test of goodness-of-fit, the most widely used quantitative validation and selection approach in 13C-MFA, are discussed, and complementary and alternative forms of validation and selection are proposed. A combined model validation and selection framework for 13C-MFA incorporating metabolite pool size information that leverages new developments in the field is presented and advocated for. Finally, we discuss how adopting robust validation and selection procedures can enhance confidence in constraint-based modeling as a whole and ultimately facilitate more widespread use of FBA in biotechnology.

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Research Organization:: Michigan State Univ., East Lansing, MI (United States)

Sponsoring Organization:: National Institutes of Health (NIH); National Science Foundation (NSF); USDOE; USDOE Office of Science (SC), Biological and Environmental Research (BER)

Grant/Contract Number:: SC0018269

OSTI ID:: 2221867

Alternate ID(s):: OSTI ID: 2222500
OSTI ID: 2575853

Journal Information:: Biotechnology Progress, Journal Name: Biotechnology Progress Journal Issue: 1 Vol. 40; ISSN 1520-6033; ISSN 8756-7938

Publisher:: Society for Biological EngineeringCopyright Statement

Country of Publication:: United States

Language:: English

References (106)

Extra Sums of Squares and Tests for Several Parameters Being Zero Draper, Norman R.; Smith, Harry Applied Regression Analysis https://doi.org/10.1002/9781118625590.ch6	book	April 1998
Pool size measurements improve precision of flux estimates but increase sensitivity to unmodeled reactions outside the core network in isotopically nonstationary metabolic flux analysis (INST‐MFA) Zheng, Amy O.; Sher, Anna; Fridman, Daniel Biotechnology Journal, Vol. 17, Issue 3 https://doi.org/10.1002/biot.202000427	journal	February 2022
Optknock: A bilevel programming framework for identifying gene knockout strategies for microbial strain optimization Burgard, Anthony P.; Pharkya, Priti; Maranas, Costas D. Biotechnology and Bioengineering, Vol. 84, Issue 6 https://doi.org/10.1002/bit.10803	journal	October 2003
Identification of optimal measurement sets for complete flux elucidation in metabolic flux analysis experiments Chang, YoungJung; Suthers, Patrick F.; Maranas, Costas D. Biotechnology and Bioengineering, Vol. 100, Issue 6 https://doi.org/10.1002/bit.21926	journal	January 2008
IsoDesign: A software for optimizing the design of ¹³C‐metabolic flux analysis experiments Millard, Pierre; Sokol, Serguei; Letisse, Fabien Biotechnology and Bioengineering, Vol. 111, Issue 1 https://doi.org/10.1002/bit.24997	journal	September 2013
To be certain about the uncertainty: Bayesian statistics for ¹³ C metabolic flux analysis Theorell, Axel; Leweke, Samuel; Wiechert, Wolfgang Biotechnology and Bioengineering, Vol. 114, Issue 11 https://doi.org/10.1002/bit.26379	journal	August 2017
Effect of light fluctuations on photosynthesis and metabolic flux in Synechocystis sp. PCC 6803 Imada, Tatsumi; Yamamoto, Chiaki; Toyoshima, Masakazu Biotechnology Progress, Vol. 39, Issue 3 https://doi.org/10.1002/btpr.3326	journal	February 2023
Model Assessment and Selection Hastie, Trevor; Tibshirani, Robert; Friedman, Jerome The Elements of Statistical Learning https://doi.org/10.1007/978-0-387-84858-7_7	book	December 2008
Methods and advances in metabolic flux analysis: a mini-review Antoniewicz, Maciek R. Journal of Industrial Microbiology & Biotechnology, Vol. 42, Issue 3 https://doi.org/10.1007/s10295-015-1585-x	journal	January 2015
Engineering metabolism and product formation in Corynebacterium glutamicum by coordinated gene overexpression Koffas, Mattheos A. G.; Jung, Gyoo Yeol; Stephanopoulos, Gregory Metabolic Engineering, Vol. 5, Issue 1 https://doi.org/10.1016/S1096-7176(03)00002-8	journal	January 2003
Conversion of Escherichia coli to Generate All Biomass Carbon from CO2 Gleizer, Shmuel; Ben-Nissan, Roee; Bar-On, Yinon M. Cell, Vol. 179, Issue 6 https://doi.org/10.1016/j.cell.2019.11.009	journal	November 2019
Metabolic flux analysis reaching genome wide coverage: lessons learned and future perspectives Hendry, John I.; Dinh, Hoang V.; Foster, Charles Current Opinion in Chemical Engineering, Vol. 30 https://doi.org/10.1016/j.coche.2020.05.008	journal	December 2020
Strain improvement by metabolic engineering: lysine production as a case study for systems biology Koffas, Mattheos; Stephanopoulos, Gregory Current Opinion in Biotechnology, Vol. 16, Issue 3 https://doi.org/10.1016/j.copbio.2005.04.010	journal	June 2005
Model selection in systems and synthetic biology Kirk, Paul; Thorne, Thomas; Stumpf, Michael PH Current Opinion in Biotechnology, Vol. 24, Issue 4 https://doi.org/10.1016/j.copbio.2013.03.012	journal	August 2013
Isotopically nonstationary metabolic flux analysis (INST-MFA): putting theory into practice Cheah, Yi Ern; Young, Jamey D. Current Opinion in Biotechnology, Vol. 54 https://doi.org/10.1016/j.copbio.2018.02.013	journal	December 2018
Mitigating biomass composition uncertainties in flux balance analysis using ensemble representations Choi, Yoon-Mi; Choi, Dong-Hyuk; Lee, Yi Qing Computational and Structural Biotechnology Journal, Vol. 21 https://doi.org/10.1016/j.csbj.2023.07.025	journal	January 2023
Metabolic flux analysis at ultra short time scale: Isotopically non-stationary 13C labeling experiments Nöh, Katharina; Grönke, Karsten; Luo, Bing Journal of Biotechnology, Vol. 129, Issue 2 https://doi.org/10.1016/j.jbiotec.2006.11.015	journal	April 2007
A scientific workflow framework for 13C metabolic flux analysis Dalman, Tolga; Wiechert, Wolfgang; Nöh, Katharina Journal of Biotechnology, Vol. 232 https://doi.org/10.1016/j.jbiotec.2015.12.032	journal	August 2016
Prospects and problems for standardizing model validation in systems biology Gross, Fridolin; MacLeod, Miles Progress in Biophysics and Molecular Biology, Vol. 129 https://doi.org/10.1016/j.pbiomolbio.2017.01.003	journal	October 2017
The effects of alternate optimal solutions in constraint-based genome-scale metabolic models Mahadevan, R.; Schilling, C. H. Metabolic Engineering, Vol. 5, Issue 4 https://doi.org/10.1016/j.ymben.2003.09.002	journal	October 2003
Integration of gene expression data into genome-scale metabolic models Åkesson, Mats; Förster, Jochen; Nielsen, Jens Metabolic Engineering, Vol. 6, Issue 4 https://doi.org/10.1016/j.ymben.2003.12.002	journal	October 2004
Determination of confidence intervals of metabolic fluxes estimated from stable isotope measurements Antoniewicz, Maciek R.; Kelleher, Joanne K.; Stephanopoulos, Gregory Metabolic Engineering, Vol. 8, Issue 4 https://doi.org/10.1016/j.ymben.2006.01.004	journal	July 2006
Synergy between 13C-metabolic flux analysis and flux balance analysis for understanding metabolic adaption to anaerobiosis in E. coli Chen, Xuewen; Alonso, Ana P.; Allen, Doug K. Metabolic Engineering, Vol. 13, Issue 1 https://doi.org/10.1016/j.ymben.2010.11.004	journal	January 2011
From zero to hero—Design-based systems metabolic engineering of Corynebacterium glutamicum for l-lysine production Becker, Judith; Zelder, Oskar; Häfner, Stefan Metabolic Engineering, Vol. 13, Issue 2 https://doi.org/10.1016/j.ymben.2011.01.003	journal	March 2011
Selection of tracers for 13C-Metabolic Flux Analysis using Elementary Metabolite Units (EMU) basis vector methodology Crown, Scott B.; Antoniewicz, Maciek R. Metabolic Engineering, Vol. 14, Issue 2 https://doi.org/10.1016/j.ymben.2011.12.005	journal	March 2012
COMPLETE-MFA: Complementary parallel labeling experiments technique for metabolic flux analysis Leighty, Robert W.; Antoniewicz, Maciek R. Metabolic Engineering, Vol. 20 https://doi.org/10.1016/j.ymben.2013.08.006	journal	November 2013
Parallel labeling experiments validate Clostridium acetobutylicum metabolic network model for 13C metabolic flux analysis Au, Jennifer; Choi, Jungik; Jones, Shawn W. Metabolic Engineering, Vol. 26 https://doi.org/10.1016/j.ymben.2014.08.002	journal	November 2014
Integrated 13 C-metabolic flux analysis of 14 parallel labeling experiments in Escherichia coli Crown, Scott B.; Long, Christopher P.; Antoniewicz, Maciek R. Metabolic Engineering, Vol. 28 https://doi.org/10.1016/j.ymben.2015.01.001	journal	March 2015
13C metabolic flux analysis of the extremely thermophilic, fast growing, xylose-utilizing Geobacillus strain LC300 Cordova, Lauren T.; Antoniewicz, Maciek R. Metabolic Engineering, Vol. 33 https://doi.org/10.1016/j.ymben.2015.06.004	journal	January 2016
13C-metabolic flux analysis of co-cultures: A novel approach Gebreselassie, Nikodimos A.; Antoniewicz, Maciek R. Metabolic Engineering, Vol. 31 https://doi.org/10.1016/j.ymben.2015.07.005	journal	September 2015
13C metabolic flux analysis at a genome-scale Gopalakrishnan, Saratram; Maranas, Costas D. Metabolic Engineering, Vol. 32 https://doi.org/10.1016/j.ymben.2015.08.006	journal	November 2015
Evidence for transketolase-like TKTL1 flux in CHO cells based on parallel labeling experiments and 13 C-metabolic flux analysis Ahn, Woo Suk; Crown, Scott B.; Antoniewicz, Maciek R. Metabolic Engineering, Vol. 37 https://doi.org/10.1016/j.ymben.2016.05.005	journal	September 2016
Optimal tracers for parallel labeling experiments and 13C metabolic flux analysis: A new precision and synergy scoring system Crown, Scott B.; Long, Christopher P.; Antoniewicz, Maciek R. Metabolic Engineering, Vol. 38 https://doi.org/10.1016/j.ymben.2016.06.001	journal	November 2016
13C metabolic flux analysis of three divergent extremely thermophilic bacteria: Geobacillus sp. LC300, Thermus thermophilus HB8, and Rhodothermus marinus DSM 4252 Cordova, Lauren T.; Cipolla, Robert M.; Swarup, Adti Metabolic Engineering, Vol. 44 https://doi.org/10.1016/j.ymben.2017.10.007	journal	November 2017
Elucidation of photoautotrophic carbon flux topology in Synechocystis PCC 6803 using genome-scale carbon mapping models Gopalakrishnan, Saratram; Pakrasi, Himadri B.; Maranas, Costas D. Metabolic Engineering, Vol. 47 https://doi.org/10.1016/j.ymben.2018.03.008	journal	May 2018
Metabolism in dense microbial colonies: 13C metabolic flux analysis of E. coli grown on agar identifies two distinct cell populations with acetate cross-feeding Wolfsberg, Eric; Long, Christopher P.; Antoniewicz, Maciek R. Metabolic Engineering, Vol. 49 https://doi.org/10.1016/j.ymben.2018.08.013	journal	September 2018
Predicting the metabolic capabilities of Synechococcus elongatus PCC 7942 adapted to different light regimes Broddrick, Jared T.; Welkie, David G.; Jallet, Denis Metabolic Engineering, Vol. 52 https://doi.org/10.1016/j.ymben.2018.11.001	journal	March 2019
Metabolic flux responses to deletion of 20 core enzymes reveal flexibility and limits of E. coli metabolism Long, Christopher P.; Antoniewicz, Maciek R. Metabolic Engineering, Vol. 55 https://doi.org/10.1016/j.ymben.2019.08.003	journal	September 2019
Quantifying the propagation of parametric uncertainty on flux balance analysis Dinh, Hoang V.; Sarkar, Debolina; Maranas, Costas D. Metabolic Engineering, Vol. 69 https://doi.org/10.1016/j.ymben.2021.10.012	journal	January 2022
13C-metabolic flux analysis of Clostridium ljungdahlii illuminates its core metabolism under mixotrophic culture conditions Dahle, Michael L.; Papoutsakis, Eleftherios T.; Antoniewicz, Maciek R. Metabolic Engineering, Vol. 72 https://doi.org/10.1016/j.ymben.2022.03.011	journal	July 2022
A High-Quality Genome-Scale Model for Rhodococcus opacus Metabolism Roell, Garrett W.; Schenk, Christina; Anthony, Winston E. ACS Synthetic Biology, Vol. 12, Issue 6 https://doi.org/10.1021/acssynbio.2c00618	journal	May 2023
Systematic evaluation of objective functions for predicting intracellular fluxes in Escherichia coli Schuetz, Robert; Kuepfer, Lars; Sauer, Uwe Molecular Systems Biology, Vol. 3, Issue 1 https://doi.org/10.1038/msb4100162	journal	January 2007
What is flux balance analysis? Orth, Jeffrey D.; Thiele, Ines; Palsson, Bernhard Ø Nature Biotechnology, Vol. 28, Issue 3 https://doi.org/10.1038/nbt.1614	journal	March 2010
A protocol for generating a high-quality genome-scale metabolic reconstruction Thiele, Ines; Palsson, Bernhard Ø Nature Protocols, Vol. 5, Issue 1 https://doi.org/10.1038/nprot.2009.203	journal	January 2010
Utilizing tandem mass spectrometry for metabolic flux analysis Wang, Yujue; Hui, Sheng; Wondisford, Fredric E. Laboratory Investigation, Vol. 101, Issue 4 https://doi.org/10.1038/s41374-020-00488-z	journal	April 2021
A genome-scale metabolic model of Saccharomyces cerevisiae that integrates expression constraints and reaction thermodynamics Oftadeh, Omid; Salvy, Pierre; Masid, Maria Nature Communications, Vol. 12, Issue 1 https://doi.org/10.1038/s41467-021-25158-6	journal	August 2021
MEMOTE for standardized genome-scale metabolic model testing Lieven, Christian; Beber, Moritz E.; Olivier, Brett G. Nature Biotechnology, Vol. 38, Issue 3 https://doi.org/10.1038/s41587-020-0446-y	journal	March 2020
Creation and analysis of biochemical constraint-based models using the COBRA Toolbox v.3.0 Heirendt, Laurent; Arreckx, Sylvain; Pfau, Thomas Nature Protocols, Vol. 14, Issue 3 https://doi.org/10.1038/s41596-018-0098-2	journal	February 2019
High-resolution 13C metabolic flux analysis Long, Christopher P.; Antoniewicz, Maciek R. Nature Protocols, Vol. 14, Issue 10 https://doi.org/10.1038/s41596-019-0204-0	journal	August 2019
Flux balance analysis with or without molecular crowding fails to predict two thirds of experimentally observed epistasis in yeast Alzoubi, Deya; Desouki, Abdelmoneim Amer; Lercher, Martin J. Scientific Reports, Vol. 9, Issue 1 https://doi.org/10.1038/s41598-019-47935-6	journal	August 2019
Introducing an Optimization- and explicit Runge-Kutta- based Approach to Perform Dynamic Flux Balance Analysis Schroeder, Wheaton L.; Saha, Rajib Scientific Reports, Vol. 10, Issue 1 https://doi.org/10.1038/s41598-020-65457-4	journal	June 2020
Flux balance analysis predicts essential genes in clear cell renal cell carcinoma metabolism Gatto, Francesco; Miess, Heike; Schulze, Almut Scientific Reports, Vol. 5, Issue 1 https://doi.org/10.1038/srep10738	journal	June 2015
Regulatory on/off minimization of metabolic flux changes after genetic perturbations Shlomi, T.; Berkman, O.; Ruppin, E. Proceedings of the National Academy of Sciences, Vol. 102, Issue 21 https://doi.org/10.1073/pnas.0406346102	journal	May 2005
Global reconstruction of the human metabolic network based on genomic and bibliomic data Duarte, N. C.; Becker, S. A.; Jamshidi, N. Proceedings of the National Academy of Sciences, Vol. 104, Issue 6 https://doi.org/10.1073/pnas.0610772104	journal	January 2007
Isotopically nonstationary ¹³ C flux analysis of changes in Arabidopsis thaliana leaf metabolism due to high light acclimation Ma, Fangfang; Jazmin, Lara J.; Young, Jamey D. Proceedings of the National Academy of Sciences, Vol. 111, Issue 47 https://doi.org/10.1073/pnas.1319485111	journal	November 2014
Reimport of carbon from cytosolic and vacuolar sugar pools into the Calvin–Benson cycle explains photosynthesis labeling anomalies Xu, Yuan; Wieloch, Thomas; Kaste, Joshua A. M. Proceedings of the National Academy of Sciences, Vol. 119, Issue 11 https://doi.org/10.1073/pnas.2121531119	journal	March 2022
Analysis of optimality in natural and perturbed metabolic networks Segre, D.; Vitkup, D.; Church, G. M. Proceedings of the National Academy of Sciences, Vol. 99, Issue 23 https://doi.org/10.1073/pnas.232349399	journal	November 2002
Use of Randomized Sampling for Analysis of Metabolic Networks Schellenberger, Jan; Palsson, Bernhard Ø. Journal of Biological Chemistry, Vol. 284, Issue 9 https://doi.org/10.1074/jbc.R800048200	journal	October 2008
Flux balance analysis in the era of metabolomics Lee, J. M. Briefings in Bioinformatics, Vol. 7, Issue 2 https://doi.org/10.1093/bib/bbl007	journal	March 2006
DEMETER: efficient simultaneous curation of genome-scale reconstructions guided by experimental data and refined gene annotations Heinken, Almut; Magnúsdóttir, Stefanía; Fleming, Ronan M. T. Bioinformatics, Vol. 37, Issue 21 https://doi.org/10.1093/bioinformatics/btab622	journal	September 2021
Accurate flux predictions using tissue-specific gene expression in plant metabolic modeling Kaste, Joshua A. M.; Shachar-Hill, Yair Bioinformatics, Vol. 39, Issue 5 https://doi.org/10.1093/bioinformatics/btad186	journal	April 2023
Predicting metabolic engineering knockout strategies for chemical production: accounting for competing pathways Tepper, N.; Shlomi, T. Bioinformatics, Vol. 26, Issue 4 https://doi.org/10.1093/bioinformatics/btp704	journal	December 2009
13CFLUX2—high-performance software suite for 13C-metabolic flux analysis Weitzel, Michael; Nöh, Katharina; Dalman, Tolga Bioinformatics, Vol. 29, Issue 1 https://doi.org/10.1093/bioinformatics/bts646	journal	October 2012
INCA: a computational platform for isotopically non-stationary metabolic flux analysis Young, J. D. Bioinformatics, Vol. 30, Issue 9 https://doi.org/10.1093/bioinformatics/btu015	journal	January 2014
CHRR: coordinate hit-and-run with rounding for uniform sampling of constraint-based models Haraldsdóttir, Hulda S.; Cousins, Ben; Thiele, Ines Bioinformatics, Vol. 33, Issue 11 https://doi.org/10.1093/bioinformatics/btx052	journal	January 2017
Integrating proteomic or transcriptomic data into metabolic models using linear bound flux balance analysis Tian, Mingyuan; Reed, Jennifer L. Bioinformatics, Vol. 34, Issue 22 https://doi.org/10.1093/bioinformatics/bty445	journal	June 2018
The metabolic origins of non-photorespiratory CO2 release during photosynthesis: a metabolic flux analysis Xu, Yuan; Fu, Xinyu; Sharkey, Thomas D. Plant Physiology, Vol. 186, Issue 1 https://doi.org/10.1093/plphys/kiab076	journal	February 2021
Genome-Scale Fluxome of Synechococcus elongatus UTEX 2973 Using Transient ¹³ C-Labeling Data Hendry, John I.; Gopalakrishnan, Saratram; Ungerer, Justin Plant Physiology, Vol. 179, Issue 2 https://doi.org/10.1104/pp.18.01357	journal	December 2018
The principle of flux minimization and its application to estimate stationary fluxes in metabolic networks: Flux minimization Holzhütter, Hermann-Georg European Journal of Biochemistry, Vol. 271, Issue 14 https://doi.org/10.1111/j.1432-1033.2004.04213.x	journal	June 2004
It Is All about Metabolic Fluxes Nielsen, J. Journal of Bacteriology, Vol. 185, Issue 24 https://doi.org/10.1128/JB.185.24.7031-7035.2003	journal	December 2003
Stoichiometric flux balance models quantitatively predict growth and metabolic by-product secretion in wild-type Escherichia coli W3110. Varma, A.; Palsson, B. O. Applied and Environmental Microbiology, Vol. 60, Issue 10 https://doi.org/10.1128/aem.60.10.3724-3731.1994	journal	January 1994
Reconstruction and Use of Microbial Metabolic Networks: the Core Escherichia coli Metabolic Model as an Educational Guide Orth, Jeffrey D.; Palsson, Bernhard Ø.; Fleming, R. M. T. EcoSal Plus, Vol. 4, Issue 1 https://doi.org/10.1128/ecosalplus.10.2.1	journal	September 2010
Predicting biological system objectives de novo from internal state measurements Gianchandani, Erwin P.; Oberhardt, Matthew A.; Burgard, Anthony P. BMC Bioinformatics, Vol. 9, Issue 1 https://doi.org/10.1186/1471-2105-9-43	journal	January 2008
Development and experimental verification of a genome-scale metabolic model for Corynebacterium glutamicum Shinfuku, Yohei; Sorpitiporn, Natee; Sono, Masahiro Microbial Cell Factories, Vol. 8, Issue 1 https://doi.org/10.1186/1475-2859-8-43	journal	January 2009
A detailed genome-wide reconstruction of mouse metabolism based on human Recon 1 Sigurdsson, Martin I.; Jamshidi, Neema; Steingrimsson, Eirikur BMC Systems Biology, Vol. 4, Issue 1 https://doi.org/10.1186/1752-0509-4-140	journal	January 2010
Rational design of 13C-labeling experiments for metabolic flux analysis in mammalian cells Crown, Scott B.; Ahn, Woo; Antoniewicz, Maciek R. BMC Systems Biology, Vol. 6, Issue 1 https://doi.org/10.1186/1752-0509-6-43	journal	January 2012
COBRApy: COnstraints-Based Reconstruction and Analysis for Python Ebrahim, Ali; Lerman, Joshua A.; Palsson, Bernhard O. BMC Systems Biology, Vol. 7, Issue 1 https://doi.org/10.1186/1752-0509-7-74	journal	January 2013
Comparisons of Shewanella strains based on genome annotations, modeling, and experiments Ong, Wai; Vu, Trang T.; Lovendahl, Klaus N. BMC Systems Biology, Vol. 8, Issue 1 https://doi.org/10.1186/1752-0509-8-31	journal	January 2014
Non-stationary 13C metabolic flux analysis of Chinese hamster ovary cells in batch culture using extracellular labeling highlights metabolic reversibility and compartmentation Nicolae, Averina; Wahrheit, Judith; Bahnemann, Janina BMC Systems Biology, Vol. 8, Issue 1 https://doi.org/10.1186/1752-0509-8-50	journal	January 2014
Addressing uncertainty in genome-scale metabolic model reconstruction and analysis Bernstein, David B.; Sulheim, Snorre; Almaas, Eivind Genome Biology, Vol. 22, Issue 1 https://doi.org/10.1186/s13059-021-02289-z	journal	February 2021
Estimating the Dimension of a Model Schwarz, Gideon The Annals of Statistics, Vol. 6, Issue 2 https://doi.org/10.1214/aos/1176344136	journal	March 1978
Systems Biology: The Big Picture Spivey, Angela Environmental Health Perspectives, Vol. 112, Issue 16 https://doi.org/10.1289/ehp.112-a938	journal	November 2004
Systems biology elucidates the distinctive metabolic niche filled by the human gut microbe Eggerthella lenta Noecker, Cecilia; Sanchez, Juan; Bisanz, Jordan E. PLOS Biology, Vol. 21, Issue 5 https://doi.org/10.1371/journal.pbio.3002125	journal	May 2023
A pathogen-specific isotope tracing approach reveals metabolic activities and fluxes of intracellular Salmonella Mitosch, Karin; Beyß, Martin; Phapale, Prasad PLOS Biology, Vol. 21, Issue 8 https://doi.org/10.1371/journal.pbio.3002198	journal	August 2023
Context-Specific Metabolic Networks Are Consistent with Experiments Becker, Scott A.; Palsson, Bernhard O. PLoS Computational Biology, Vol. 4, Issue 5 https://doi.org/10.1371/journal.pcbi.1000082	journal	May 2008
Constraint-Based Model of Shewanella oneidensis MR-1 Metabolism: A Tool for Data Analysis and Hypothesis Generation Pinchuk, Grigoriy E.; Hill, Eric A.; Geydebrekht, Oleg V. PLoS Computational Biology, Vol. 6, Issue 6 https://doi.org/10.1371/journal.pcbi.1000822	journal	June 2010
Sampling the Solution Space in Genome-Scale Metabolic Networks Reveals Transcriptional Regulation in Key Enzymes Bordel, Sergio; Agren, Rasmus; Nielsen, Jens PLoS Computational Biology, Vol. 6, Issue 7 https://doi.org/10.1371/journal.pcbi.1000859	journal	July 2010
Systematic Evaluation of Methods for Integration of Transcriptomic Data into Constraint-Based Models of Metabolism Machado, Daniel; Herrgård, Markus PLoS Computational Biology, Vol. 10, Issue 4 https://doi.org/10.1371/journal.pcbi.1003580	journal	April 2014
Enhanced flux prediction by integrating relative expression and relative metabolite abundance into thermodynamically consistent metabolic models Pandey, Vikash; Hadadi, Noushin; Hatzimanikatis, Vassily PLOS Computational Biology, Vol. 15, Issue 5 https://doi.org/10.1371/journal.pcbi.1007036	journal	May 2019
ΔFBA—Predicting metabolic flux alterations using genome-scale metabolic models and differential transcriptomic data Ravi, Sudharshan; Gunawan, Rudiyanto; Stelling, Joerg PLOS Computational Biology, Vol. 17, Issue 11, p. e1009589 https://doi.org/10.1371/journal.pcbi.1009589	journal	November 2021
Validation-based model selection for 13C metabolic flux analysis with uncertain measurement errors Sundqvist, Nicolas; Grankvist, Nina; Watrous, Jeramie PLOS Computational Biology, Vol. 18, Issue 4 https://doi.org/10.1371/journal.pcbi.1009999	journal	April 2022
The genome-scale metabolic model for the purple non-sulfur bacterium Rhodopseudomonas palustris Bis A53 accurately predicts phenotypes under chemoheterotrophic, chemoautotrophic, photoheterotrophic, and photoautotrophic growth conditions Tec-Campos, Diego; Posadas, Camila; Tibocha-Bonilla, Juan D. PLOS Computational Biology, Vol. 19, Issue 8 https://doi.org/10.1371/journal.pcbi.1011371	journal	August 2023
A Topological Map of the Compartmentalized Arabidopsis thaliana Leaf Metabolome Krueger, Stephan; Giavalisco, Patrick; Krall, Leonard PLoS ONE, Vol. 6, Issue 3 https://doi.org/10.1371/journal.pone.0017806	journal	March 2011
optGpSampler: An Improved Tool for Uniformly Sampling the Solution-Space of Genome-Scale Metabolic Networks Megchelenbrink, Wout; Huynen, Martijn; Marchiori, Elena PLoS ONE, Vol. 9, Issue 2 https://doi.org/10.1371/journal.pone.0086587	journal	February 2014
Metabolic flux analysis of heterotrophic growth in Chlamydomonas reinhardtii Boyle, Nanette R.; Sengupta, Neelanjan; Morgan, John A. PLOS ONE, Vol. 12, Issue 5 https://doi.org/10.1371/journal.pone.0177292	journal	May 2017
The choice of the objective function in flux balance analysis is crucial for predicting replicative lifespans in yeast Schnitzer, Barbara; Österberg, Linnea; Cvijovic, Marija PLOS ONE, Vol. 17, Issue 10 https://doi.org/10.1371/journal.pone.0276112	journal	October 2022
Vibrio natriegens genome‐scale modeling reveals insights into halophilic adaptations and resource allocation Coppens, Lucas; Tschirhart, Tanya; Leary, Dagmar H. Molecular Systems Biology, Vol. 19, Issue 4 https://doi.org/10.15252/msb.202110523	journal	February 2023
Robustifying Experimental Tracer Design for13C-Metabolic Flux Analysis Beyß, Martin; Parra-Peña, Victor D.; Ramirez-Malule, Howard Frontiers in Bioengineering and Biotechnology, Vol. 9 https://doi.org/10.3389/fbioe.2021.685323	journal	June 2021
RobOKoD: microbial strain design for (over)production of target compounds Stanford, Natalie J.; Millard, Pierre; Swainston, Neil Frontiers in Cell and Developmental Biology, Vol. 3 https://doi.org/10.3389/fcell.2015.00017	journal	March 2015
Tandem Mass Spectrometry for 13C Metabolic Flux Analysis: Methods and Algorithms Based on EMU Framework Choi, Jungik; Antoniewicz, Maciek R. Frontiers in Microbiology, Vol. 10 https://doi.org/10.3389/fmicb.2019.00031	journal	January 2019
High-Quality Genome-Scale Reconstruction of Corynebacterium glutamicum ATCC 13032 Feierabend, Martina; Renz, Alina; Zelle, Elisabeth Frontiers in Microbiology, Vol. 12 https://doi.org/10.3389/fmicb.2021.750206	journal	November 2021
Highlighting the potential of Synechococcus elongatus PCC 7942 as platform to produce α-linolenic acid through an updated genome-scale metabolic modeling Santos-Merino, María; Gargantilla-Becerra, Álvaro; de la Cruz, Fernando Frontiers in Microbiology, Vol. 14 https://doi.org/10.3389/fmicb.2023.1126030	journal	March 2023
Flux Balance Analysis of Plant Metabolism: The Effect of Biomass Composition and Model Structure on Model Predictions Yuan, Huili; Cheung, C. Y. Maurice; Hilbers, Peter A. J. Frontiers in Plant Science, Vol. 7 https://doi.org/10.3389/fpls.2016.00537	journal	April 2016
Probing Light-Dependent Regulation of the Calvin Cycle Using a Multi-Omics Approach Yu King Hing, Nathaphon; Aryal, Uma K.; Morgan, John A. Frontiers in Plant Science, Vol. 12 https://doi.org/10.3389/fpls.2021.733122	journal	October 2021
Isotopically non-stationary metabolic flux analysis of heterotrophic Arabidopsis thaliana cell cultures Smith, Edward N.; Ratcliffe, R. George; Kruger, Nicholas J. Frontiers in Plant Science, Vol. 13 https://doi.org/10.3389/fpls.2022.1049559	journal	January 2023
New Insights on Metabolic Features of Bacillus subtilis Based on Multistrain Genome-Scale Metabolic Modeling Blázquez, Blas; San León, David; Rojas, Antonia International Journal of Molecular Sciences, Vol. 24, Issue 8 https://doi.org/10.3390/ijms24087091	journal	April 2023

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Integrative teaching of metabolic modeling and flux analysis with interactive python modules

Journal Article · Tue Aug 15 20:00:00 EDT 2023 · Biochemistry and Molecular Biology · OSTI ID:1995902

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Model validation and selection in metabolic flux analysis and flux balance analysis

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