Abstract
Pathways and more precisely Elementary Flux Modes (EFM) are artefacts extracted from metabolic networks that are very useful to achieve the comprehension of a very specific metabolic function or dysfunction. Many methods to extract pathways have already been developed and all of them have to deal with common problems like the production of infeasible subnetworks and the production of the same solution repetitively. Although some strategies have been incorporated to those methods in order to mitigate the problems, they get already a high ratio of repetitions and the insistent presence of the same reactions in the solutions. We do a proposal focused on linear programming (LP) methods for pathway extraction. It aims to improve the representation of every reaction in the set of computed pathways by penalizing the most often included reactions during the extraction.
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References
Thiele, I., Palsson, B.Ø.: A protocol for generating a high-quality genome-scale metabolic reconstruction. Nat. Protoc. 5(1), 93–121 (2010)
Schmidt, B.J., Ebrahim, A., Metz, T.O., Adkins, J.N., Palsson, B.Ø., Hyduke, D.R.: GIM3E: condition-specific models of cellular metabolism developed from metabolomics and expression data. Bioinformatics 29(22), 2900–2908 (2013)
Schuster, S., Hilgetag, C.: On elementary flux modes in biochemical reaction systems at steady state. J. Biol. Syst. 2(02), 165–182 (1994)
IBM: IBM ILOG CPLEX Optimizer (2010). http://www-01.ibm.com/software/integration/optimization/cplex-optimizer/
Forrest, J.: CLP-coin-or linear program solver. In: DIMACS Workshop on COIN-OR, 17–20 July (2006)
Burgard, A.P., Nikolaev, E.V., Schilling, C.H., Maranas, C.D.: Flux coupling analysis of genome-scale metabolic network reconstructions. Genome Res. 14(2), 301–312 (2004)
Larhlimi, A., David, L., Selbig, J., Bockmayr, A.: F2C2: a fast tool for the computation of flux coupling in genome-scale metabolic networks. BMC Bioinform. 13(1), 57 (2012)
Becker, S.A., Price, N.D., Palsson, B.Ø.: Metabolite coupling in genome-scale metabolic networks. BMC Bioinform. 7(1), 1 (2006)
De Figueiredo, L.F., Schuster, S., Kaleta, C., Fell, D.A.: Can sugars be produced from fatty acids? A test case for pathway analysis tools. Bioinformatics 24(22), 2615–2621 (2008)
Rezola, A., Pey, J., Tobalina, L., Rubio, Á., Beasley, J.E., Planes, F.J.: Advances in network-based metabolic pathway analysis and gene expression data integration. Brief. Bioinform. 16(2), 265–279 (2015)
Klamt, S., Stelling, J.: Combinatorial complexity of pathway analysis in metabolic networks. Mol. Biol. Rep. 29(1–2), 233–236 (2002)
De Figueiredo, L.F., Podhorski, A., Rubio, A., Kaleta, C., Beasley, J.E., Schuster, S., Planes, F.J.: Computing the shortest elementary flux modes in genome-scale metabolic networks. Bioinformatics 25(23), 3158–3165 (2009)
Pey, J., Planes, F.: Direct calculation of elementary flux modes satisfying several biological constraints in genome-scale metabolic networks. Bioinformatics 30(15), 2197–2203 (2014). (Oxford, England)
Rezola, A., Pey, J., de Figueiredo, L.F., Podhorski, A., Schuster, S., Rubio, A., Planes, F.J.: Selection of human tissue-specific elementary flux modes using gene expression data. Bioinformatics 29(16), 2009–2016 (2013)
Gagneur, J., Klamt, S.: Computation of elementary modes: a unifying framework and the new binary approach. BMC Bioinform. 5(1), 1 (2004)
Planes, F.J., Beasley, J.E.: A critical examination of stoichiometric and path-finding approaches to metabolic pathways. Brief. Bioinform. 9(5), 422–436 (2008)
Jevremovic, D., Boley, D., Sosa, C.P.: Divide-and-conquer approach to the parallel computation of elementary flux modes in metabolic networks. In: 2011 IEEE International Symposium on Parallel and Distributed Processing Workshops and Ph.D. Forum (IPDPSW), pp. 502–511. IEEE (2011)
Hidalgo, J.F., Guil, F., Garcia, J.M.: A new approach to obtain EFMs using graph methods based on the shortest path between end nodes. In: Ortuño, F., Rojas, I. (eds.) IWBBIO 2015. LNCS, vol. 9043, pp. 641–649. Springer, Heidelberg (2015). doi:10.1007/978-3-319-16483-0_62
Wilcoxon, F., Katti, S., Wilcox, R.A.: Critical values and probability levels for the Wilcoxon rank sum test and the Wilcoxon signed rank test. Sel. Tables Math. Stat. 1, 171–259 (1970)
Wilcoxon, F.: Individual comparisons by ranking methods. Biom. Bull. 1(6), 80–83 (1945)
Feist, A.M., Henry, C.S., Reed, J.L., Krummenacker, M., Joyce, A.R., Karp, P.D., Broadbelt, L.J., Hatzimanikatis, V., Palsson, B.Ø.: A genome-scale metabolic reconstruction for escherichia coli k-12 mg1655 that accounts for 1260 orfs and thermodynamic information. Mol. Syst. Biol. 3(1), 121 (2007)
Orth, J.D., Fleming, R.M., Palsson, B.: Reconstruction and use of microbial metabolic networks: the core escherichia coli metabolic model as an educational guide. EcoSal Plus 4(1) (2010)
Acknowledgments
This work was supported in part by the Spanish Ministerio de Economia y Competitividad (MINECO) and European Commission FEDER under grant TIN2015-66972-C5-3-R.
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Hidalgo, J.F., Egea, J.A., Guil, F., García, J.M. (2017). Representativeness of a Set of Metabolic Pathways. In: Rojas, I., Ortuño, F. (eds) Bioinformatics and Biomedical Engineering. IWBBIO 2017. Lecture Notes in Computer Science(), vol 10208. Springer, Cham. https://doi.org/10.1007/978-3-319-56148-6_58
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