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Items: 1 to 20 of 84

1.

Flux duality in nonlinear GMA systems: implications for metabolic engineering.

Marin-Sanguino A, Mendoza ER, Voit EO.

J Biotechnol. 2010 Sep 1;149(3):166-72. doi: 10.1016/j.jbiotec.2009.12.009. Epub 2009 Dec 14.

PMID:
20015458
2.

Optimization of biotechnological systems through geometric programming.

Marin-Sanguino A, Voit EO, Gonzalez-Alcon C, Torres NV.

Theor Biol Med Model. 2007 Sep 26;4:38.

3.

A hybrid model of anaerobic E. coli GJT001: combination of elementary flux modes and cybernetic variables.

Kim JI, Varner JD, Ramkrishna D.

Biotechnol Prog. 2008 Sep-Oct;24(5):993-1006. doi: 10.1002/btpr.73.

PMID:
19194908
4.

Strategies for representing metabolic pathways within biochemical systems theory: reversible pathways.

Sorribas A, Savageau MA.

Math Biosci. 1989 Jun;94(2):239-69. Review.

PMID:
2520170
5.

Flux networks in metabolic graphs.

Warren PB, Queiros SM, Jones JL.

Phys Biol. 2009 Sep 22;6(4):046006. doi: 10.1088/1478-3975/6/4/046006.

PMID:
19773605
6.

Combining pathway analysis with flux balance analysis for the comprehensive study of metabolic systems.

Schilling CH, Edwards JS, Letscher D, Palsson BØ.

Biotechnol Bioeng. 2000-2001;71(4):286-306.

PMID:
11291038
7.

Toward predicting metabolic fluxes in metabolically engineered strains.

Liao JC, Oh MK.

Metab Eng. 1999 Jul;1(3):214-23.

PMID:
10937936
8.

Optimization of biochemical systems by linear programming and general mass action model representations.

Marín-Sanguino A, Torres NV.

Math Biosci. 2003 Aug;184(2):187-200.

PMID:
12832147
9.

Approximation of delays in biochemical systems.

Mocek WT, Rudnicki R, Voit EO.

Math Biosci. 2005 Dec;198(2):190-216. Epub 2005 Sep 19.

PMID:
16181644
10.
11.

Optimization in integrated biochemical systems.

Voit EO.

Biotechnol Bioeng. 1992 Aug;40(5):572-82.

PMID:
18601153
12.

[Dynamic paradigm in psychopathology: "chaos theory", from physics to psychiatry].

Pezard L, Nandrino JL.

Encephale. 2001 May-Jun;27(3):260-8. French.

PMID:
11488256
13.

Optimization and evolution in metabolic pathways: global optimization techniques in Generalized Mass Action models.

Sorribas A, Pozo C, Vilaprinyo E, Guillén-Gosálbez G, Jiménez L, Alves R.

J Biotechnol. 2010 Sep 1;149(3):141-53. doi: 10.1016/j.jbiotec.2010.01.026. Epub 2010 Feb 10.

PMID:
20152867
14.

Advantages and disadvantages of aggregating fluxes into synthetic and degradative fluxes when modelling metabolic pathways.

De Atauri P, Curto R, Puigjaner J, Cornish-Bowden A, Cascante M.

Eur J Biochem. 1999 Oct;265(2):671-9.

15.

Metabolic design: how to engineer a living cell to desired metabolite concentrations and fluxes.

Kholodenko BN, Cascante M, Hoek JB, Westerhoff HV, Schwaber J.

Biotechnol Bioeng. 1998 Jul 20;59(2):239-47.

PMID:
10099334
16.

Incorporating metabolic flux ratios into constraint-based flux analysis by using artificial metabolites and converging ratio determinants.

Choi HS, Kim TY, Lee DY, Lee SY.

J Biotechnol. 2007 May 10;129(4):696-705. Epub 2007 Mar 4.

PMID:
17408794
17.

Controllability of non-linear biochemical systems.

Ervadi-Radhakrishnan A, Voit EO.

Math Biosci. 2005 Jul;196(1):99-123.

PMID:
15982674
18.

Predicting biological system objectives de novo from internal state measurements.

Gianchandani EP, Oberhardt MA, Burgard AP, Maranas CD, Papin JA.

BMC Bioinformatics. 2008 Jan 24;9:43. doi: 10.1186/1471-2105-9-43.

19.

Metabolic pathway analysis: basic concepts and scientific applications in the post-genomic era.

Schilling CH, Schuster S, Palsson BO, Heinrich R.

Biotechnol Prog. 1999 May-Jun;15(3):296-303. Review.

PMID:
10356246
20.

Metabolic flux distribution analysis by 13C-tracer experiments using the Markov chain-Monte Carlo method.

Yang J, Wongsa S, Kadirkamanathan V, Billings SA, Wright PC.

Biochem Soc Trans. 2005 Dec;33(Pt 6):1421-2.

PMID:
16246135
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