The geometry of the flux cone of a metabolic network

Biophysical Journal

Volumn 89, Issue 6, 2005, Pages 3837-3845

  Wagner, Clemens ^a,b   Urbanczik, Robert ^a  

^a Institute of Pharmacology   (Switzerland)

^b UNIVERSITY OF BERN   (Switzerland)

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; BIOTECHNOLOGY; GENOTYPE; MATHEMATICAL ANALYSIS; METABOLITE; PHENOTYPE; STOICHIOMETRY;

EID: 28444458560     PISSN: 00063495     EISSN: 00063495     Source Type: Journal    
DOI: 10.1529/biophysj.104.055129     Document Type: Article

References (34)

1. Kanehisa, M., and S. Goto. 2000. KEGG: Kyoto encyclopedia of genes and genomes. Nucleic Acids Res. 28:27-30.
2. Karp, P., S. Paley, and P. Romero. 2002. The pathway tools software. Bioinformatics. 18:5225-5232.
3. Clarke, B. 1988. Stoichiometric network analysis. Cell Biophys. 12:237-253.
4. Edwards, J., and B. Palsson. 1998. How will bioinformatics influence metabolic engineering? Biotechnol. Bioeng. 58:162-169.
5. Clarke, B. 1980. Stability of complex reaction networks. In Advances in Chemical Physics. I. Prigogine and S.A. Rice, editors. John Wiley, New York. 1-215.
6. Papin, J., N. Price, S. Wiback, D. Fell, and B. Palsson. 2003. Metabolic pathways in the post-genome era. Trends Biochem. Sci. 28:250-258.
7. Papin, J., N. Price, and B. Palsson. 2002. Extreme pathway length and reaction participation in genome-scale metabolic networks. Genome Res. 12:1889-1900.
8. Klamt, S., and E. Gilles. 2004. Minimal cut sets in biochemical reaction networks. Bioinformatics. 20:226-234.
9. Schuster, R., and S. Schuster. 1993. Refined algorithm and computer program for calculating all non-negative fluxes admissible in steady states of biochemical reaction systems with or without some flux rates fixed. Comput. Appl. Biosci. 9:79-85.
10. Schilling, C., D. Letscher, and B. Palsson. 2000. Theory for the systemic definition of metabolic pathways and their use in interpreting metabolic function from a pathway oriented perspective. J. Theor. Biol. 203:229-248.
11. Stelling, J., S. Klamt, K. Bettenbrock, S. Schuster, and E. Gilles. 2002. Metabolic network structure determines key aspects of functionality and regulation. Nature. 420:190-193.
12. Wiback, S., and B. Palsson. 2002. Extreme pathway analysis of human red blood cell metabolism. Biophys. J. 83:808-818.
13. Vijayasankaran, N., R. Carlson, and F. Srienc. 2005. Metabolic pathway structures for recombinant protein synthesis in Escherichia coll. Appl. Microbiol. Biotechnol. Epub ahead of print.
14. Klamt, S., and J. Stelling. 2003. Two approaches for metabolic pathway analysis? Trends Biotechnol. 21:64-69.
15. Palsson, B., N. Price, and J. Papin. 2003. Development of network-based pathway definitions: the need to analyze real metabolic networks. Trends Biotechnol. 21:195-198.
16. Papin, J., J. Stelling, N. Price, S. Klamt, S. Schuster, and B. Palsson. 2004. Comparison of network-based pathway analysis methods. Trends Biotechnol. 22:400-405.
17. Rockafellar, R. 1972. Convex Analysis. Princeton University Press, Princeton, NJ.
18. Ibarra, R., J. Edwards, and B. Palsson. 2002. Escherichia coli K-12 undergoes adaptive evolution to achieve in silico predicted optimal growth. Nature. 420:186-189.
19. Edwards, J., R. Ramakrishna, and B. Palsson. 2002. Characterizing the metabolic phenotype: a phenotype phase-plane analysis. Biotechnol. Bioeng. 77:27-36.
20. Wagner, C. 2004. Nullspace approach to determine elementary modes of chemical reaction systems. J. Phys. Chem. B. 108:2425-2431.
21. Urbanczik, R., and C. Wagner. 2005. An improved algorithm for stoichiometric network analysis: theory and applications. Bioinformatics. 21:1203-1210.
22. Stucki, J. 2004. Chromokinetics of metabolic pathways. Eur. J. Biochem. 271:2745-2754.
23. Nozicka, R, J. Guddat, H. Hollatz, and B. Bank. 1974. Theory of Linear Parametric Optimization. Akademie-Verlag, Berlin.
24. Heinrich, R., and S. Schuster. 1996. The Regulation of Cellular Systems. Chapman & Hall, New York.
25. Varma, A., B. Boesch, and B. Palsson. 1993. Stoichiometric interpretation of Escherichia coli glucose catabolism under various oxygenation rates. Appl. Environ. Microbiol. 59:2465-2473.
26. Edwards, J., R. Ibarra, and B. Palsson. 2001. In silico predictions of Escherichia coli metabolic capabilities are consistent with experimental data. Nat. Biotechnol. 19:125-130.
27. Famili, I., J. Förster, J. Nielsen, and B. Palsson. 2003. Sacchammyces cerevisiae phenotypes can be predicted by using constraint-based analysis of a genome-scale reconstructed metabolic network. Proc. Natl. Acad. Sci. USA. 100:13134-13139.
28. Schuster, S., and R. Schuster. 1991. Detecting strictly detailed balanced subnetworks in open chemical reaction networks. J. Math. Chem. 6:17-40.
29. Beard, D., S.-D. Liang, and H. Qian. 2002. Energy balance for analysis of complex metabolic networks. Biophys. J. 83:79-86.
30. Price, N., I. Famili, D. Beard, and B. Palsson. 2002. Extreme pathway and Kirchhoff's second law. Biophys. J. 83:2879-2882.
31. Beard, D., E. Babson, E. Curtis, and H. Qian. 2004. Thermodynamic constraints for biochmical networks. J. Theor. Biol. 228:327-333.
32. Price, N., J. Reed, and B. Palsson. 2004. Genome-scale models of microbial cells: evaluating the consequences of constraints. Nat. Rev. Microbiol. 2:886-897.
33. Pfeiffer, T., I. Sanchez-Valdenebro, J. Nuno, F. Montero, and S. Schuster. 1999. METATOOL: for studying metabolic networks. Bioinformatics. 15:251-257.
34. Fischer, G. 1997. Linear Algebra. Vieweg & Sohn, Braunschweig, Germany.