Response to comment on 'Can sugars be produced from fatty acids? A test case for pathway analysis tools'

Bioinformatics

Volumn 25, Issue 24, 2009, Pages 3330-3331

  de Figueiredo, Luis F ^a   Schuster, Stefan ^a   Kaleta, Christoph ^a   Fell, David A ^b  

^a FRIEDRICH SCHILLER UNIVERSITY JENA   (Germany)

^b OXFORD BROOKES UNIVERSITY   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

CARBOHYDRATE; FATTY ACID;

BIOLOGY; BIOSYNTHESIS; GLUCONEOGENESIS; GLYCOLYSIS; METABOLISM; METHODOLOGY; NOTE;

CARBOHYDRATES; COMPUTATIONAL BIOLOGY; FATTY ACIDS; GLUCONEOGENESIS; GLYCOLYSIS; METABOLIC NETWORKS AND PATHWAYS;

EID: 75849128878     PISSN: 13674803     EISSN: 14602059     Source Type: Journal    
DOI: 10.1093/bioinformatics/btp591     Document Type: Letter

References (32)

1. Acuña, V. et al. (2009) Modes and cuts in metabolic networks: complexity and algorithms. Biosystems, 95, 51-60.
2. Blum, T. and Kohlbacher, O. (2008) Using atom mapping rules for an improved detection of relevant routes in weighted metabolic networks. J. Comput. Biol., 15, 565-576.
3. Caspi, R. et al. (2008) The MetaCyc Database of metabolic pathways and enzymes and the BioCyc collection of Pathway/Genome Databases. Nucleic Acids Res., 36, D623-D631.
4. Croes, D. et al. (2006) Inferring meaningful pathways in weighted metabolic networks. J. Mol. Biol., 356, 222-236.
5. de Figueiredo, L.F. et al. (2009a) Can sugars be produced from fatty acids? A test case for pathway analysis tools. Bioinformatics, 25, 152-158.
6. de Figueiredo, L.F. et al. (2009b) Computing the shortest elementary flux modes in genome-scale metabolic networks. Bioinformatics, [Epub ahead of print, doi:10.1093/bioinformatics/btp564, September 30].
7. Faust, K. et al. (2009) In response to "can sugars be produced from fatty acids? a test case for pathway analysis tools". Bioinformatics, [Epub ahead of print, doi: 10.1093/bioinformatics/btp557, September 23].
8. Fischer, E. and Sauer, U. (2003)A novel metabolic cycle catalyzes glucose oxidation and anaplerosis in hungry Escherichia coli. J. Biol. Chem., 278, 46446-46451.
9. Kaleta, C. et al. (2006) Analyzing molecular reaction networks: from pathways to chemical organizations. Mol. Biotechnol., 34, 117-123.
10. Kaleta, C. et al. (2009) Can the whole be less than the sum of its parts? Pathway analysis in genome-scale metabolic networks using elementary flux patterns. Genome Res., 19, 1872-1883.
11. Kanehisa, M. et al. (2008) KEGG for linking genomes to life and the environment. Nucleic Acids Res., 36, D480-D484.
12. Klamt, S. et al. (2007) Structural and functional analysis of cellular networks with CellNetAnalyzer. BMC Syst. Biol., 1, 2.
13. Likić, V.A. (2006) Databases of metabolic pathways. Biochem. Mol. Biol. Educ., 34, 408-412.
14. Nelson, D.L. and Cox, M.M. (2000) Lehninger Principles of Biochemistry. 3rd edn. W.H. Freeman, New York.
15. Papin, J.A. et al. (2003) Metabolic pathways in the post-genome era. Trends Biochem. Sci., 28, 250-258.
16. Papin, J. et al. (2004) Comparison of network-based pathway analysis methods. Trends Biotechnol., 22, 400-405.
17. Poolman, M.G. et al. (2006) Challenges to be faced in the reconstruction of metabolic networks from public databases. IEE Proc. Sys1t3. Biol., 153, 379-384.
18. 13C-based flux analysis. Mol. Syst. Biol., 2, 62.
19. Schilling, C.H. and Palsson, B.Ø. (1998) The underlying pathway structure of biochemical reaction networks. Proc. Natl Acad. Sci. USA, 95, 4193-4198.
20. Schuster, S. and Kenanov, D. (2005) Adenine and adenosine salvage pathways in erythrocytes and the role of S-adenosylhomocysteine hydrolase.Atheoretical study using elementary flux modes. FEBS J., 272, 5278-5290.
21. Schuster, S. et al. (1999) Detection of elementary flux modes in biochemical networks: a promising tool for pathway analysis and metabolic engineering. Trends Biotechnol., 17, 53-60.
22. Schuster, S.et al. (2000) Ageneral definition of metabolic pathways useful for systematic organization and analysis of complex metabolic networks. Nat. Biotechnol., 18, 326-332.
23. Schwarz, R. et al. (2005) YANA - a software tool for analyzing flux modes, gene-expression and enzyme activities. BMC Bioinformatics, 6, 135.
24. Stryer, L. (1995) Biochemistry. 4th edn. W.H. Freeman and Company, New York.
25. Terzer, M. and Stelling, J. (2008) Large scale computation of elementary flux modes with bit pattern trees. Bioinformatics, 24, 2229-2235.
26. Teusink, B. et al. (2000) Can yeast glycolysis be understood in terms of in vitro kinetics of the constituent enzymes? Testing biochemistry. Eur. J. Biochem., 267, 5313-5329.
27. Trinh, C.T. et al. (2009) Elementary mode analysis: a useful metabolic pathway analysis tool for characterizing cellular metabolism. Appl. Microbiol. Biotechnol., 81, 813-826.
28. Urbanczik, R. and Wagner, C. (2005)An improved algorithm for stoichiometric network analysis: theory and applications. Bioinformatics, 21, 1203-1210.
29. Voet, D. and Voet, J. (2004) Biochemistry. 3rd edn. Wiley, Hoboken, USA.
30. von Kamp, A. and Schuster, S. (2006) Metatool 5.0: fast and flexible elementary modes analysis. Bioinformatics, 22, 1930-1931.
31. Wagner, C. and Urbanczik, R. (2005) The geometry of the flux cone of a metabolic network. Biophys. J., 89, 3837-3845.
32. Weinman, E.O. et al. (1957) Conversion of fatty acids to carbohydrate: application of isotopes to this problem and role of the Krebs cycle as a synthetic pathway. Physiol. Rev., 37, 252-272.