1. Croes, D., Couche, F., Wodak, S.J., et al.: Metabolic PathFinding: Inferring relevant pathways in biochemical networks. Nucleic Acids Res. 2005(33), W326–W330

   Google Scholar 

2. Dijkstra, E.W.: A note on two problems in connexion with Graphs. Numerische Mathematik 1, 269–271 (1959)

   Article MATH MathSciNet  Google Scholar 

3. Roman, M.T., Flemming, B.O.: Palsson. Reconstruction and use of microbial metabolic networks: The core Escherichia coli metabolic model as an educational guide. In: Escherichia coli and Salmonella: Cellular and Molecular Biology, Chapter 10.2.1, Washington, DC (2010)

   Google Scholar 

4. Elementary Flux Mode Tool,http://www.csb.ethz.ch/tools/efmtool

5. De Figueiredo, L.F., et al.: Can sugars be produced from fatty acids? A test case for pathway analysis tools. Bioinformatics 24, 2615–2621 (2008)

   Article  Google Scholar 

6. De Figueiredo, L.F., et al.: Computing the shortest elementary flux modes in genome-scale metabolic networks. Bioinformatics 25, 3158–3165 (2009)

   Article  Google Scholar 

7. Hunt, K.A., et al.: Complete enumeration of elementary flux modes through scalable, demand-based subnetwork definition. Bioinformatics (2014) (in press)

   Google Scholar 

8. Jevremovic, D., Boley, D., Sosa, C.P.: Divide-and-Conquer Approach to the Parallel Computation of Elementary Flux Modes in Metabolic Networks. In: IEEE International Symposium on IPDPS 2011, pp. 50–511 (2011)

   Google Scholar 

9. Klamt, S., Stelling, J.: Combinatorial complexity of pathway analysis in metabolic networks. Mol. Biol. Rep. 29(1-2), 233–236 (2002)

   Article  Google Scholar 

10. Planes, F.J., Beasly, J.E.: A critical examination of stoichiometric and path-finding approaches to metabolic pathways. Briefings in Bioinformatics 9, 422–436 (2008)

    Article  Google Scholar 

11. Pey, J., Prada, J., Beasley, J.E., Planes, F.: Path finding methods accounting for stoichiometry in metabolic networks. Genome Biol. 12(5), 49 (2011)

    Article  Google Scholar 

12. Pey, J., Planes, F.J.: Direct calculation of Elementary Flux Modes satisfying several biological constraints in genome-scale metabolic networks. Bioinformatics (2014) (in press)

    Google Scholar 

13. Rezola, A., et al.: Selection of human tissue-specific elementary flux modes using gene expression data. Bioinformatics 29, 2009–2016 (2013)

    Article  Google Scholar 

14. Rezola, A., et al.: Advances in network-based metabolic pathway analysis and gene expression data integration. Bioinform in press, Brief (2014)

    Google Scholar 

15. Schmidt, B.J., et al.: GIM3E: condition-specific models of cellular metabolism developed from metabolomics and expression data. Bioinformatics 29, 2900–2908 (2013)

    Article  Google Scholar 

16. Schuster, S., Hilgetag, C.: On elementary flux modes in biochemical reaction systems at steady state. J. Biol. Syst. 2, 165–182 (1994)

    Article  Google Scholar 

17. von Kamp, A., Schuster, S.: Metatool 5.0: Fast and flexible elementary modes analysis. Bioinformatics 22(15), 1930–1931 (2006)

    Article  Google Scholar 

18. Seo, H., Lee, D.-Y., Park, S., Fan, L.T., Shafie, S., Bertk, B., Friedler, F.: Graph-theoretical identification of pathways for biochemical reaction. Biotechnology Letters 23, 1551–1557 (2001)

    Article  Google Scholar 

19. Thiele, I., Palsson, B.: A protocol for generating a high-quality genome-scale metabolic reconstruction. Nat. Protoc. 5, 93–121 (2010)

    Article  Google Scholar 

20. Terzer, M., Stelling, J.: Large-scale computation of elementary flux modes with bit pattern trees. Bioinformatics 24, 2229–2235 (2008)

    Article  Google Scholar 

21. Urbanczik, R., Wagner, C.: An improved algorithm for stoichiometric network analysis: theory and applications. Bioinformatics 21, 1203–1210 (2005)

    Article  Google Scholar 

Download references