메뉴 건너뛰기




Volumn 14, Issue 5, 2003, Pages 491-496

Advances in flux balance analysis

Author keywords

[No Author keywords available]

Indexed keywords

BIOMASS PRODUCTION; ESCHERICHIA COLI; HELICOBACTER PYLORI; MATHEMATICAL ANALYSIS; MATHEMATICAL MODEL; METHODOLOGY; METHYLOBACTERIUM EXTORQUENS; MICROBIAL BIOMASS; MICROBIAL METABOLISM; NONHUMAN; PHYSICAL CHEMISTRY; PRIORITY JOURNAL; REVIEW; SIMULATION; STEADY STATE; STOICHIOMETRY; THEORY; THERMODYNAMICS;

EID: 0142122303     PISSN: 09581669     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.copbio.2003.08.001     Document Type: Review
Times cited : (635)

References (42)
  • 1
    • 0142025925 scopus 로고    scopus 로고
    • edn September 1, 1998. Edited by: The Institute for Genomic Research
    • TIGR: Microbial database. edn September 1, 1998. Edited by: The Institute for Genomic Research; 1998.
    • (1998) TIGR: Microbial Database
  • 4
    • 0034625143 scopus 로고    scopus 로고
    • The Escherichia coli MG1655 in silico metabolic genotype: Its definition, characteristics, and capabilities
    • Edwards J.S., Palsson B.O. The Escherichia coli MG1655 in silico metabolic genotype: its definition, characteristics, and capabilities. Proc. Natl. Acad Sci. USA. 97:2000;5528-5533.
    • (2000) Proc. Natl. Acad Sci. USA , vol.97 , pp. 5528-5533
    • Edwards, J.S.1    Palsson, B.O.2
  • 5
    • 0033580813 scopus 로고    scopus 로고
    • Systems properties of the Haemophilus influenzae Rd metabolic genotype
    • Edwards J.S., Palsson B.O. Systems properties of the Haemophilus influenzae Rd metabolic genotype. J. Biol. Chem. 274:1999;17410-17416.
    • (1999) J. Biol. Chem. , vol.274 , pp. 17410-17416
    • Edwards, J.S.1    Palsson, B.O.2
  • 6
    • 0037313750 scopus 로고    scopus 로고
    • Genome-scale reconstruction of the Saccharomyces cerevisiae metabolic network
    • The largest FBA model to date, consisting of 1175 metabolic reactions and 584 metabolites
    • Forster J., Famili I., Fu P., Palsson B.O., Nielsen J. Genome-scale reconstruction of the Saccharomyces cerevisiae metabolic network. Genome Res. 13:2003;244-253 The largest FBA model to date, consisting of 1175 metabolic reactions and 584 metabolites.
    • (2003) Genome Res. , vol.13 , pp. 244-253
    • Forster, J.1    Famili, I.2    Fu, P.3    Palsson, B.O.4    Nielsen, J.5
  • 8
    • 0027909387 scopus 로고
    • Biochemical production capabilities of Escherichia coli
    • Varma A., Boesch B.W., Palsson B.O. Biochemical production capabilities of Escherichia coli. Biotechnol. Bioeng. 42:1993;59-73.
    • (1993) Biotechnol. Bioeng. , vol.42 , pp. 59-73
    • Varma, A.1    Boesch, B.W.2    Palsson, B.O.3
  • 9
    • 0027716622 scopus 로고
    • Metabolic capabilities of Escherichia coli: I. Synthesis of biosynthetic precursors and cofactors
    • Varma A., Palsson B.O. Metabolic capabilities of Escherichia coli: I. Synthesis of biosynthetic precursors and cofactors. J. Theor. Biol. 165:1993;477-502.
    • (1993) J. Theor. Biol. , vol.165 , pp. 477-502
    • Varma, A.1    Palsson, B.O.2
  • 10
    • 0027723421 scopus 로고
    • Metabolic capabilities of Escherichia coli: II. Optimal growth patterns
    • Varma A., Palsson B.O. Metabolic capabilities of Escherichia coli: II. Optimal growth patterns. J. Theor. Biol. 165:1993;503-522.
    • (1993) J. Theor. Biol. , vol.165 , pp. 503-522
    • Varma, A.1    Palsson, B.O.2
  • 11
    • 0028146781 scopus 로고
    • Stoichiometric flux balance models quantitatively predict growth and metabolic by-product secretion in wild-type Escherichia coli W3110
    • Varma A., Palsson B.O. Stoichiometric flux balance models quantitatively predict growth and metabolic by-product secretion in wild-type Escherichia coli W3110. Appl. Environ. Microbiol. 60:1994;3724-3731.
    • (1994) Appl. Environ. Microbiol. , vol.60 , pp. 3724-3731
    • Varma, A.1    Palsson, B.O.2
  • 12
    • 0027223982 scopus 로고
    • Stoichiometric interpretation of Escherichia coli glucose catabolism under various oxygenation rates
    • Varma A., Boesch B.W., Palsson B.O. Stoichiometric interpretation of Escherichia coli glucose catabolism under various oxygenation rates. Appl. Environ. Microbiol. 59:1993;2465-2473.
    • (1993) Appl. Environ. Microbiol. , vol.59 , pp. 2465-2473
    • Varma, A.1    Boesch, B.W.2    Palsson, B.O.3
  • 13
    • 0037069467 scopus 로고    scopus 로고
    • Analysis of optimality in natural and perturbed metabolic networks
    • Defined minimization of metabolic adjustment to more accurately predict knockouts that would be lethal to cellular systems
    • Segre D., Vitkup D., Church G.M. Analysis of optimality in natural and perturbed metabolic networks. Proc. Natl. Acad Sci. USA. 99:2002;15112-15117 Defined minimization of metabolic adjustment to more accurately predict knockouts that would be lethal to cellular systems.
    • (2002) Proc. Natl. Acad Sci. USA , vol.99 , pp. 15112-15117
    • Segre, D.1    Vitkup, D.2    Church, G.M.3
  • 14
    • 0034447725 scopus 로고    scopus 로고
    • Combining pathway analysis with flux balance analysis for the comprehensive study of metabolic systems
    • Schilling C.H., Edwards J.S., Letscher D., Palsson B.O. Combining pathway analysis with flux balance analysis for the comprehensive study of metabolic systems. Biotechnol. Bioeng. 71:2000;286-306.
    • (2000) Biotechnol. Bioeng. , vol.71 , pp. 286-306
    • Schilling, C.H.1    Edwards, J.S.2    Letscher, D.3    Palsson, B.O.4
  • 16
    • 0033136116 scopus 로고    scopus 로고
    • Toward metabolic phenomics: Analysis of genomic data using flux balances
    • Schilling C.H., Edwards J.S., Palsson B.O. Toward metabolic phenomics: analysis of genomic data using flux balances. Biotechnol. Prog. 15:1999;288-295.
    • (1999) Biotechnol. Prog. , vol.15 , pp. 288-295
    • Schilling, C.H.1    Edwards, J.S.2    Palsson, B.O.3
  • 18
    • 0035125986 scopus 로고    scopus 로고
    • In silico predictions of Escherichia coli metabolic capabilities are consistent with experimental data
    • Edwards J.S., Ibarra R.U., Palsson B.O. In silico predictions of Escherichia coli metabolic capabilities are consistent with experimental data. Nat. Biotechnol. 19:2001;125-130.
    • (2001) Nat. Biotechnol. , vol.19 , pp. 125-130
    • Edwards, J.S.1    Ibarra, R.U.2    Palsson, B.O.3
  • 19
    • 0037079023 scopus 로고    scopus 로고
    • Escherichia coli K-12 undergoes adaptive evolution to achieve in silico predicted optimal growth
    • This work demonstrated that, while the path of evolution cannot be predicted, the final endpoint of evolution for E. coli can be predicted using FBA
    • Ibarra R.U., Edwards J.S., Palsson B.O. Escherichia coli K-12 undergoes adaptive evolution to achieve in silico predicted optimal growth. Nature. 420:2002;186-189 This work demonstrated that, while the path of evolution cannot be predicted, the final endpoint of evolution for E. coli can be predicted using FBA.
    • (2002) Nature , vol.420 , pp. 186-189
    • Ibarra, R.U.1    Edwards, J.S.2    Palsson, B.O.3
  • 20
    • 0034661295 scopus 로고    scopus 로고
    • Recursive MILP model for finding all alternate optima in LP models for metabolic networks
    • Lee S., Phalakornkule C., Domach M.M., Grossmann I.E. Recursive MILP model for finding all alternate optima in LP models for metabolic networks. Comp. Chem. Eng. 24:2000;711-716.
    • (2000) Comp. Chem. Eng. , vol.24 , pp. 711-716
    • Lee, S.1    Phalakornkule, C.2    Domach, M.M.3    Grossmann, I.E.4
  • 21
    • 0034805665 scopus 로고    scopus 로고
    • A MILP-based flux alternative generation and NMR experimental design strategy for metabolic engineering
    • Phalakornkule C., Lee S., Zhu T., Koepsel R., Ataai M.M., Grossmann I.E., Domach M.M. A MILP-based flux alternative generation and NMR experimental design strategy for metabolic engineering. Metab. Eng. 3:2001;124-137.
    • (2001) Metab. Eng. , vol.3 , pp. 124-137
    • Phalakornkule, C.1    Lee, S.2    Zhu, T.3    Koepsel, R.4    Ataai, M.M.5    Grossmann, I.E.6    Domach, M.M.7
  • 22
    • 0036350955 scopus 로고    scopus 로고
    • The genome-scale metabolic extreme pathway structure in Haemophilus influenzae shows significant network redundancy
    • Papin J.A., Price N.D., Edwards J.S., Palsson B.O. The genome-scale metabolic extreme pathway structure in Haemophilus influenzae shows significant network redundancy. J. Theor. Biol. 215:2002;67-82.
    • (2002) J. Theor. Biol. , vol.215 , pp. 67-82
    • Papin, J.A.1    Price, N.D.2    Edwards, J.S.3    Palsson, B.O.4
  • 23
    • 0035824029 scopus 로고    scopus 로고
    • Regulation of gene expression in flux balance models of metabolism
    • Covert M.W., Schilling C.H., Palsson B. Regulation of gene expression in flux balance models of metabolism. J. Theor. Biol. 213:2001;73-88.
    • (2001) J. Theor. Biol. , vol.213 , pp. 73-88
    • Covert, M.W.1    Schilling, C.H.2    Palsson, B.3
  • 24
    • 0037424661 scopus 로고    scopus 로고
    • Constraints-based models: Regulation of gene expression reduces the steady-state solution space
    • Covert M.W., Palsson B.O. Constraints-based models: regulation of gene expression reduces the steady-state solution space. J. Theor. Biol. 221:2003;309-325.
    • (2003) J. Theor. Biol. , vol.221 , pp. 309-325
    • Covert, M.W.1    Palsson, B.O.2
  • 25
    • 0036708443 scopus 로고    scopus 로고
    • Dynamic flux balance analysis of diauxic growth in Escherichia coli
    • Combined, these two manuscripts provide approaches for capturing the dynamic shifts that occur in gene regulation over time. Although substantially different, the two approaches compliment each other.
    • Mahadevan R., Edwards J.S., Doyle F.J. Dynamic flux balance analysis of diauxic growth in Escherichia coli. Biophys. J. 83:2002;1331-1340 Combined, these two manuscripts provide approaches for capturing the dynamic shifts that occur in gene regulation over time. Although substantially different, the two approaches compliment each other.
    • (2002) Biophys. J. , vol.83 , pp. 1331-1340
    • Mahadevan, R.1    Edwards, J.S.2    Doyle, F.J.3
  • 26
    • 0036286631 scopus 로고    scopus 로고
    • Energy balance for analysis of complex metabolic networks
    • Concentration-dependent chemical potentials are used to specify additional nonlinear constraints on the FBA optimization problem. The approach also allows for determination of intracellular concentrations; however, there is no guarantee that the solution is the global optimum.
    • Beard D.A., Liang S.C., Qian H. Energy balance for analysis of complex metabolic networks. Biophys. J. 83:2002;79-86 Concentration-dependent chemical potentials are used to specify additional nonlinear constraints on the FBA optimization problem. The approach also allows for determination of intracellular concentrations; however, there is no guarantee that the solution is the global optimum.
    • (2002) Biophys. J. , vol.83 , pp. 79-86
    • Beard, D.A.1    Liang, S.C.2    Qian, H.3
  • 27
    • 0035812464 scopus 로고    scopus 로고
    • Probing the performance limits of the Escherichia coli metabolic network subject to gene additions or deletions
    • Burgard A.P., Maranas C.D. Probing the performance limits of the Escherichia coli metabolic network subject to gene additions or deletions. Biotechnol. Bioeng. 74:2001;364-375.
    • (2001) Biotechnol. Bioeng. , vol.74 , pp. 364-375
    • Burgard, A.P.1    Maranas, C.D.2
  • 28
    • 0037021804 scopus 로고    scopus 로고
    • Characterizing the metabolic phenotype: A phenotype phase plane analysis
    • Edwards J.S., Ramakrishna R., Palsson B.O. Characterizing the metabolic phenotype: a phenotype phase plane analysis. Biotechnol. Bioeng. 77:2002;27-36.
    • (2002) Biotechnol. Bioeng. , vol.77 , pp. 27-36
    • Edwards, J.S.1    Ramakrishna, R.2    Palsson, B.O.3
  • 29
    • 0037023907 scopus 로고    scopus 로고
    • Stoichiometric model for evaluating the metabolic capabilities of the facultative methylotroph Methylobacterium extorquens AM1, with application to reconstruction of C-3 and C-4 metabolism
    • Computational prediction and experimental validation of network redundancy.
    • Van Dien S.J., Lidstrom M.E. Stoichiometric model for evaluating the metabolic capabilities of the facultative methylotroph Methylobacterium extorquens AM1, with application to reconstruction of C-3 and C-4 metabolism. Biotechnol. Bioeng. 78:2002;296-312 Computational prediction and experimental validation of network redundancy.
    • (2002) Biotechnol. Bioeng. , vol.78 , pp. 296-312
    • Van Dien, S.J.1    Lidstrom, M.E.2
  • 30
    • 0037008673 scopus 로고    scopus 로고
    • Transcriptional regulation in constraints-based metabolic models of Escherichia coli
    • Covert M.W., Palsson B.O. Transcriptional regulation in constraints-based metabolic models of Escherichia coli. J. Biol. Chem. 277:2002;28058-28064.
    • (2002) J. Biol. Chem. , vol.277 , pp. 28058-28064
    • Covert, M.W.1    Palsson, B.O.2
  • 31
    • 0034519221 scopus 로고    scopus 로고
    • Robustness analysis of the Escherichia coli metabolic network
    • Edwards J.S., Palsson B.O. Robustness analysis of the Escherichia coli metabolic network. Biotechnol. Prog. 16:2000;927-939.
    • (2000) Biotechnol. Prog. , vol.16 , pp. 927-939
    • Edwards, J.S.1    Palsson, B.O.2
  • 32
    • 0038293216 scopus 로고    scopus 로고
    • Optimization-based framework for inferring and testing hypothesized metabolic objective functions
    • Optimization is used to determine if a given objective function is consistent with experimentally observed fluxes in E. coli.
    • Burgard A.P., Maranas C.D. Optimization-based framework for inferring and testing hypothesized metabolic objective functions. Biotechnol. Bioeng. 82:2003;670-677 Optimization is used to determine if a given objective function is consistent with experimentally observed fluxes in E. coli.
    • (2003) Biotechnol. Bioeng. , vol.82 , pp. 670-677
    • Burgard, A.P.1    Maranas, C.D.2
  • 33
    • 0036040830 scopus 로고    scopus 로고
    • Calculating as many fluxes as possible in underdetermined metabolic networks
    • Although it is not possible to uniquely determine all of the fluxes in an underdetermined system, some of the fluxes can be uniquely specified.
    • Klamt S., Schuster S. Calculating as many fluxes as possible in underdetermined metabolic networks. Mol. Biol. Rep. 29:2002;243-248 Although it is not possible to uniquely determine all of the fluxes in an underdetermined system, some of the fluxes can be uniquely specified.
    • (2002) Mol. Biol. Rep. , vol.29 , pp. 243-248
    • Klamt, S.1    Schuster, S.2
  • 34
    • 0037197159 scopus 로고    scopus 로고
    • Calculability analysis in underdetermined metabolic networks illustrated by a model of the central metabolism in purple nonsulfur bacteria
    • Klamt S., Schuster S., Gilles E.D. Calculability analysis in underdetermined metabolic networks illustrated by a model of the central metabolism in purple nonsulfur bacteria. Biotechnol. Bioeng. 77:2002;734-751.
    • (2002) Biotechnol. Bioeng. , vol.77 , pp. 734-751
    • Klamt, S.1    Schuster, S.2    Gilles, E.D.3
  • 36
    • 0021383728 scopus 로고
    • Equations and calculations for fermentations of butyric acid bacteria
    • Papoutsakis E.T. Equations and calculations for fermentations of butyric acid bacteria. Biotechnol. Bioeng. 26:1984;174-187.
    • (1984) Biotechnol. Bioeng. , vol.26 , pp. 174-187
    • Papoutsakis, E.T.1
  • 37
    • 0022493181 scopus 로고
    • Fat synthesis in adipose tissue. An examination of stoichiometric constraints
    • Fell D.A., Small J.A. Fat synthesis in adipose tissue. An examination of stoichiometric constraints. J. Biochem. 238:1986;781-786.
    • (1986) J. Biochem. , vol.238 , pp. 781-786
    • Fell, D.A.1    Small, J.A.2
  • 38
    • 0025405421 scopus 로고
    • Simple constrained optimization view of acetate overflow in E. coli
    • Majewski R.A., Domach M.M. Simple constrained optimization view of acetate overflow in E. coli. Biotechnol. Bioeng. 35:1990;731-738.
    • (1990) Biotechnol. Bioeng. , vol.35 , pp. 731-738
    • Majewski, R.A.1    Domach, M.M.2
  • 39
    • 0026594358 scopus 로고
    • Optimal selection of metabolic fluxes for in vivo measurement. I. Development of mathematical methods
    • Savinell J.M., Palsson B.O. Optimal selection of metabolic fluxes for in vivo measurement. I. Development of mathematical methods. J. Theor. Biol. 155:1992;201-214.
    • (1992) J. Theor. Biol. , vol.155 , pp. 201-214
    • Savinell, J.M.1    Palsson, B.O.2
  • 40
    • 0026566666 scopus 로고
    • Optimal selection of metabolic fluxes for in vivo measurement. II. Application to Escherichia coli and hybridoma cell metabolism
    • Savinell J.M., Palsson B.O. Optimal selection of metabolic fluxes for in vivo measurement. II. Application to Escherichia coli and hybridoma cell metabolism. J. Theor. Biol. 155:1992;215-242.
    • (1992) J. Theor. Biol. , vol.155 , pp. 215-242
    • Savinell, J.M.1    Palsson, B.O.2
  • 41
    • 0343035686 scopus 로고    scopus 로고
    • Stoichiometric model of Escherichia coli metabolism: Incorporation of growth-rate dependent biomass composition and mechanistic energy requirements
    • Pramanik J., Keasling J.D. Stoichiometric model of Escherichia coli metabolism: incorporation of growth-rate dependent biomass composition and mechanistic energy requirements. Biotechnol. Bioeng. 56:1997;398-421.
    • (1997) Biotechnol. Bioeng. , vol.56 , pp. 398-421
    • Pramanik, J.1    Keasling, J.D.2
  • 42
    • 0032552815 scopus 로고    scopus 로고
    • Effect of Escherichia coli biomass composition on central metabolic fluxes predicted by a stoichiometric model
    • Pramanik J., Keasling J.D. Effect of Escherichia coli biomass composition on central metabolic fluxes predicted by a stoichiometric model. Biotechnol. Bioeng. 60:1998;230-238.
    • (1998) Biotechnol. Bioeng. , vol.60 , pp. 230-238
    • Pramanik, J.1    Keasling, J.D.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.