Some considerations about debugging a genome - scale metabolic models ba sed on computational algorithms

Article Sidebar

PDF (Español (España))
Published: Dec 22, 2014
Keywords:
Systems Biology, reconstruction of metabolic models.

Main Article Content

Hendy Maier Pérez Barrera
Universidad de Ciencias Pedagógicas “Rafael María de Mendive”
Yaniel Jesús Barceló Fernández
Universidad de Ciencias Pedagógicas “Rafael María de Mendive”
Yarlenis Pacheco Suarez
Universidad “Hermanos Saíz Montes de Oca”, de Pinar del Río

Abstract

The development of molecular biology has allowed rapid progress in understanding the functions and principles of operation of cells and unicellular organisms at the molecular level. One of the new areas of research that emerges from this picture is Systems Biology, having as one of its reconstruction of genome - scale metabolic models cornerstones. Currently, this reconstruction is a complex issue, because basically it is not automated. Consequently, this paper attempts to make some considerations about debugging a genomic scale metabolic models based on computational algorithms, an intention that has a high methodological value, how to make possible a major social problem.

Downloads

Download data is not yet available.

Article Details

How to Cite
Pérez Barrera, H. M., Barceló Fernández, Y. J., & Pacheco Suarez, Y. (2014). Some considerations about debugging a genome - scale metabolic models ba sed on computational algorithms. Mendive. Journal on Education, 13(1), 84–92. Retrieved from https://mendive.upr.edu.cu/index.php/MendiveUPR/article/view/683
Issue
Vol. 13 No. 1 (2014): Oct. -december
Section
ARTICLES

References

. Benson, D. Lipman, D & Ostell, J. 1993. GenBank. Nucleic Acid Research. 21. 2963-2965.

. Chen, L. and Vitkup, D. (2006). Predicting genes for orphan metabolic activitiesusing phylogenetic profiles. Genome Biol 2006, 7:R17.

. Edwards J.S., Ibarra R.U., Palsson B.Ø. (2001) Insilico predictions of Escherichia coli metabolic capabilities are consistent with experimental data. Nat Biotechnol 19, 125–130.

. Fang, K., Zhao, H., Sun, Ch., Lam, C. M., Chang, S., Zhang, K., Panda, G., Godinho, M., Martins dos Santos, V. and Wang, J. (2011). Exploring the metabolic network of the epidemic pathogen Burkholderia cenocepacia J2315 via genome-scale reconstruction. Systems biology 1752-0509/5/83.

. Feist A.M., Herrgard M.J., Thiele I. et al. (2009) Reconstruction of biochemical networks in microorganisms. Nat Rev Microbiol7, 129–143. 8

. Förster J., Famili I., Fu P. et al. (2003) Genome-scale reconstruction of the Saccharomyces cerevisiae metabolic network. Genome Res13, 244–253.

. Green, M.L. and Karp, P.D. (2004). A Bayesian method for identifying missing enzymes in predicted metabolic pathway databases. BMC Bioinformatics2004, 5:76.

. Kumar, V.S, Dasika, M.S and Maranas, C.D. (2007).Optimization based automated curation of metabolic reconstructions. BMC Bioinformatics 2007, 8:212 doi:10.1186/1471-2105-8-212.

. Kharchenko, P., Vitkup, D. and Church, G.M. (2004). Filling gaps in a metabolicnetwork using expression information. Bioinformatics 2004, 20Suppl 1:I178-I185.

. Kharchenko, P., Chen, L., Freund, Y., Vitkup, D. and Church, G.M. 2006. Identifyingmetabolic enzymes with multiple types of association evidence. BMC Bioinformatics 2006, 7:177.

. Latendresse, M., Krummenacker, M., Trupp, M., and Karp, P.D. (2012). Construction and completion of flux balance models from pathway databases. Bioinformatics Vol. 28 no. 3 2012, pages 388– 396.

. doi:10.1093/bioinformatics/btr681).

. Notebaart R.A., van Enckevort F.H., Francke C. et al. (2006) Accelerating the reconstruction of genome-scale metabolic networks. BMC Bioinformatics. doi:10.1186/1471-2105-7-296.

. Osterman, A. and Overbeek, R. (2003). Missing genes in metabolic pathways:a comparative genomics approach. Curr Opin Chem Biol 2003,7:238-251.

. Papin J.A., Price N.D., Wiback S.J. et al. (2003) Metabolic pathways in the post-genome era. Trends BiochemSci 28, 250–258.

. Reed JL, Vo TD, Schilling CH, Palsson B. (2003): An expanded genome-scale model of Escherichia coli K-12 (iJR904 GSM/GPR). Genome biology 2003, 4(9):R54.51–R54.12.

. Snoep J.L., Bruggeman F., Olivier B.G. et al. (2006) Towards building the silicon cell: A modular approach. BioSystems 83, 207–216.

. Schilling C.H., Letscher D., Palsson B.Ø. (2000) Theory for the systemic definition of metabolic pathways and their use in interpreting metabolic function from a pathway-oriented perspective. J TheorBiol203, 229–248.

. Thiele I., Palsson B.Ø. (2010) A protocol for generating a high-quality genome-scale reconstruction. Nat Protoc5, 93–121.

. Triana J., Montagud A., Siurana M., Gamermann D., Torres J., Tena J., Fernández de Córdoba P., Urchueguía J. F. Reconstruction procedure to generate and evaluate genome-scale metabolic network models, use of Synechococcus elongatus PCC7942 as a case study. Summited at Metabolic Network Reconstruction for the series Methods in Molecular Biology, Springer.

. Voet D. and Voet J.G. (2004) Biochemistry. John Wiley & Sons. Hoboken.

. Saha R, Suthers PF, Maranas CD: Zea mays iRS1563: a comprehensive genome-scale metabolic reconstruction of maize metabolism. PLoS ONE 2011, 6:e21784.

. Ranganathan S, Suthers PF, Maranas CD: OptForce: an optimization procedure for identifying all genetic manipulations leading to targeted overproductions. PLoS Comput Biol 2010, 6:e1000744

. Kumar A, Suthers PF, Maranas CD: MetRxn: a knowledgebase of metabolites and reactions spanning metabolic models and databases. BMC Bioinform 2012, 13:6.

Most read articles by the same author(s)