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IJMLC 2012 Vol.2(5): 716-719 ISSN: 2010-3700
DOI: 10.7763/IJMLC.2012.V2.221

Computational Modeling of Metabolic Networks

S. N. Kalyankar, N. V. Kalyankar, and Mohseena Thaseen

Abstract—Metabolism is the set of biochemical reactionsoccurring in living organisms. Metabolites are usually smallmolecules like glucose, amino acids etc. These biochemicalinter-conversions are generally catalyzed by enzymes. Thesequencing of genomes and development of functional genomicsmake it now possible to reconstruct and understand thestructure and function of metabolic networks at large scale.New computational tools and biological concepts are beingdeveloped to understand these metabolic networks moreprecisely. Here attempts were made for reconstruction,visualization, and graph representation of metabolic networksfor structural analysis i.e. connectivity and centrality analyses,modularity and decomposition of the networks to fundamentallevel. Reconstruction, visualization, and graphicalrepresentation of glycolysis for structural analysis anddecomposition of the network to fundamental is done as anexample of basic metabolic network in cells. The methods andconcepts presented deals with static properties and functions ofglycolysis and more complex networks can be representedfollowing similar methods.

Index Terms—Metabolic networks, modeling, visualization.

S. N. Kalyankar is with the Department of Chemistry, Yeshwant College,Nanded 431602(M.S.) India (e-mail: drkalyankarsn@ yahoo.com).
N. V. Kalyankar is with the Department of Physics, Yeshwant College,Nanded 431602(M.S.) India (e-mail: drkalyankarnv@rediffmail.com)
M. Thaseen is with Computer Science and Information TechnologyDepartment, Yeshwant College, Nanded 431602(M.S.) India(e-mail:mohseena@gmail.com)


Cite: S. N. Kalyankar, N. V. Kalyankar, and Mohseena Thaseen, "Computational Modeling of Metabolic Networks," International Journal of Machine Learning and Computing vol. 2, no. 5, pp. 716-719, 2012.

General Information

  • ISSN: 2010-3700 (Online)
  • Abbreviated Title: Int. J. Mach. Learn. Comput.
  • Frequency: Bimonthly
  • DOI: 10.18178/IJMLC
  • Editor-in-Chief: Dr. Lin Huang
  • Executive Editor:  Ms. Cherry L. Chen
  • Abstracing/Indexing: Inspec (IET), Google Scholar, Crossref, ProQuest, Electronic Journals Library.
  • E-mail: ijmlc@ejournal.net

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