Oyelade, O. J. and Isewon, Itunuoluwa and Aromolaran, Olufemi and Achas, Moses (2017) Extreme Pathway Analysis of Mycobacterium Tuberculosis. In: International Conference on Computational Science and Computational Intelligence.
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Abstract
Tuberculosis is a multisystem disorder characterized by the formation of swelling that is filled with blood which is caused from breakage in the wall of a blood vessel. This breakage can occur in different organs of the body and is caused by a bacterium known as Mycobacterium Tuberculosis (mtb) which can be represented as a metabolic network with genes, proteins and enzymes that are interconnected. This interconnection defines the uniqueness of any bacteria. The analysis of a metabolic network system is achievable through different computational techniques depending on what information is available. The flux balance analysis is mostly used for analyzing this type of network because of the little amount of information required. The application of flux balance analysis to mtb involves the conversion of the metabolic network into a stoichiometric matrix where the rows represents the metabolites and the columns represent the reactions. In this study, the stoichiometric matrix is an 828 by 1027 matrix. The analysis generated a linear problem having more unknowns than the number of equations. This type of problem is normally solved using an extreme pathways algorithm to extract independent paths and simplex method for optimization of biomass. Here, the extreme pathways analysis was used in the categorization of the metabolite of mtb while biomass was employed as the objective function using default constraints. The output represents three categories of metabolite: 31 metabolites that form part of the biomass component that are inactive, 14 metabolites that remain active and 32 metabolites that are activated after the optimization process.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Uncontrolled Keywords: | Mycobacterium Tuberculosis; Metabolic network system; Flux balance; Extreme pathways algorithm; Stoichiometric matrix; Biomass |
| Subjects: | Q Science > Q Science (General) Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
| Divisions: | Faculty of Engineering, Science and Mathematics > School of Electronics and Computer Science |
| Depositing User: | Mrs Hannah Akinwumi |
| Date Deposited: | 21 Jun 2021 16:49 |
| Last Modified: | 21 Jun 2021 16:49 |
| URI: | http://eprints.covenantuniversity.edu.ng/id/eprint/14814 |
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