|
Vol: 57(71) No: 4 / December 2012 Web Based Software for Stoichiometric Models Comparison Martins Mednis Biosystems Group, Latvia University of Agrculture, Faculty of Information Technology, Liela iela 2, LV-3001, Jelgava, Latvia, e-mail: martins.mednis@llu.lv Zintis Rove Biosystems Group, Latvia University of Agrculture, Faculty of Information Technology, Liela iela 2, LV-3001, Jelgava, Latvia Keywords: comparison, analysis, inconsistencies, stoichiometric, genome-scale, reconstruction Abstract The molecular processes in cells form a huge network, which makes detailed mathematical modeling and simulation extremely difficult [1]. Genome-scale reconstructions of metabolic networks and so stoichiometric models may contain hundreds of metabolites and sometimes over a thousand reactions. The functions of such networks are hard for the human mind to comprehend [2]. Process of iterative model building promises to accelerate biological discovery, product development, and process design [2], [3]. Consequently, the need for analysis, comparison and merge of biomodels is growing. The demand for a method to relate different models has been pointed out [4], [5]. In this paper we present an on-line software tool - ModeRator - for comparison of COBRA compatible stoichiometric models. The purpose of the software is to analyze complex models, detect the inconsistencies and to compare the models. While COBRA is a Matlab toolbox, ModeRator works with COBRA models even without having Matlab and COBRA toolbox installed on a computer. The software tool can be used on-line at http://biosystems.lv/moderator/ or hosted on a local computer. The source code on sourceforge.net and the video tutorial on YouTube is available. User manual and installation instructions are also available. ModeRator has been tested on several representative genome-scale stoichiometric models. The results show that ModeRator is able to correctly analyze and compare the models. References M. Schulz, J. Uhlendorf, E. Klipp, and W. Liebermeister, “SBMLmerge, a system for combining biochemical network models.,” Genome informatics International Conference on Genome Informatics, vol. 17, no. 1, pp. 62–71, 2006. [2] B. Ø. Palsson, Systems Biology: Properties of reconstructed networks. Cambridge University Press, 2006. [3] T. Ideker, V. Thorsson, J. A. Ranish, R. Christmas, J. Buhler, J. K. Eng, R. Bumgarner, D. R. Goodlett, R. Aebersold, and L. Hood, “Integrated genomic and proteomic analyses of a systematically perturbed metabolic network.,” Science, vol. 292, no. 5518, pp. 929–34, 2001. [4] S. Gay, S. Soliman, and F. Fages, “A graphical method for reducing and relating models in systems biology,” Bioinformatics, vol. 26, no. 18, pp. i575–i581, 2010. [5] O. Radulescu, A. N. Gorban, A. Zinovyev, and A. Lilienbaum, “Robust simplifications of multiscale biochemical networks,” BMC systems biology, vol. 2, no. 1, p. 86, 2008. [6] J. L. Snoep and B. G. Olivier, “JWS online cellular systems modelling and microbiology.,” Microbiology, vol. 149, no. Pt 11, pp. 3045–3047, 2003. [7] C. Van Gend, R. Conradie, F. B. Du Preez, and J. L. Snoep, “Data and model integration using JWS Online.,” In Silico Biology, vol. 7, no. 2 Suppl, pp. S27–S35, 2007. [8] N. Le Novère, B. Bornstein, A. Broicher, M. Courtot, M. Donizelli, H. Dharuri, L. Li, H. Sauro, M. Schilstra, B. Shapiro, J. L. Snoep, and M. Hucka, “BioModels Database: a free, centralized database of curated, published, quantitative kinetic models of biochemical and cellular systems,” Nucleic Acids Research, vol. 34, no. Database issue, pp. D689–D691, 2006. [9] M. Mednis, Z. Rove, and V. Galvanauskas, “ModeRator - a software tool for comparison of stoichiometric models,” in 7th IEEE International Symposium on Applied Computational Intelligence and Informatics, 2012, pp. 97–100. [10] W. Balzano and M. R. Del Sorbo, “Genomic comparison using data mining techniques based on a possibilistic fuzzy sets model.,” Bio Systems, vol. 88, no. 3, pp. 343–349, 2007. [11] J. Schellenberger, R. Que, R. M. T. Fleming, I. Thiele, J. D. Orth, A. M. Feist, D. C. Zielinski, A. Bordbar, N. E. Lewis, S. Rahmanian, J. Kang, D. R. Hyduke, and B. Ø. Palsson, “COBRA Toolbox 2 . 0,” Nature Protocols, vol. 6, no. 9, pp. 1290–1307, 2011. [12] A. Kostromins and E. Stalidzans, “Paint4Net: COBRA Toolbox extension for visualization of stoichiometric models of metabolism,” Biosystems, 2012. [13] D. Xavier, S. Vázquez, C. Higuera, F. Morán, and F. Montero, “Tools-4-Metatool (T4M): Online suite of web-tools to process stoichiometric network analysis data from METATOOL,” Biosystems, pp. 1–4, 2011. [14] J. Boele, B. G. Olivier, and B. Teusink, “FAME, the Flux Analysis and Modeling Environment.,” BMC systems biology, vol. 6, no. 1, p. 8, 2012. [15] B. G. Olivier, J. M. Rohwer, and J.-H. S. Hofmeyr, “Modelling cellular systems with PySCeS.,” Bioinformatics, vol. 21, no. 4, pp. 560–561, 2005. [16] M. A. Oberhardt, J. Puchałka, V. A. P. Martins Dos Santos, and J. A. Papin, “Reconciliation of Genome-Scale Metabolic Reconstructions for Comparative Systems Analysis,” PLoS Computational Biology, vol. 7, no. 3, p. 18, 2011. [17] S. a Becker, A. M. Feist, M. L. Mo, G. Hannum, B. Ø. Palsson, and M. J. Herrgard, “Quantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox.,” Nature protocols, vol. 2, no. 3, pp. 727–38, Jan. 2007. [18] J. Schellenberger, J. O. Park, T. M. Conrad, and B. Ø. Palsson, “BiGG: a Biochemical Genetic and Genomic knowledgebase of large scale metabolic reconstructions,” BMC Bioinformatics, vol. 11, no. 1, p. 213, 2010. [19] Z. Rove, M. Mednis, and I. Odzina, “Biochemical networks comparison algorithm,” in Applied Information and Communication Technologies, 2012, pp. 306–311. [20] K. Y. Lee, J. M. Park, T. Y. Kim, H. Yun, and S. Y. Lee, “The genome-scale metabolic network analysis of Zymomonas mobilis ZM4 explains physiological features and suggests ethanol and succinic acid production strategies,” Microbial Cell Factories, vol. 9, no. 1, p. 94, 2010. [21] H. Widiastuti, J. Y. Kim, S. Selvarasu, I. A. Karimi, H. Kim, J.-S. Seo, and D.-Y. Lee, “Genome-scale modeling and in silico analysis of ethanologenic bacteria Zymomonas mobilis.,” Biotechnology and Bioengineering, vol. 108, no. 3, pp. 655–665, 2011. |