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Damages in Metabolic Pathways: Computational Approaches | OMICS International | Abstract
ISSN: 0974-7230

Journal of Computer Science & Systems Biology
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Research Article

Damages in Metabolic Pathways: Computational Approaches

Nruthya Lakshminarasimhan and Somnath Tagore*

Department of Biotechnology & Bioinformatics, Dr D Y Patil University, Plot 50, Sec 15, CBD Belapur, Navi Mumbai 400614, India

*Corresponding Author:
Dr. Somnath Tagore
Department of Biotechnology & Bioinformatics
Dr D Y Patil University
Plot 50, Sec 15, CBD Belapur
Navi Mumbai 400614, India
E-mail : [email protected]

Received date: May 15, 2009; Accepted date: June 23, 2009; Published date: June 24, 2009

Citation: Lakshminarasimhan N, Tagore S (2009) Damages in Metabolic Pathways: Computational Approaches. J Comput Sci Syst Biol 2:208-215. doi:10.4172/jcsb.1000033

Copyright: © 2009 Lakshminarasimhan N, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.


Damage analysis in metabolic pathways is one of the most highlighted fields in systems biology area. Metabolic errors are studied with respect to inherited enzyme deficiencies. The damages usually occur due to changes in a particular enzymatic reaction or deletion of a step. Some enzyme disorders can also cause the particular reaction not to occur causing accumulation or reduced presence of a metabolite. This leads to dysfunction and disease state. Furthermore, the deletion of a path may change the end product of a reaction and can give rise to disorders. Thus, if the pathway leading to these changes can be determined, it would be easier to determine the disorders. Various statistical methods have been employed to determine the damages in the metabolic pathway. One such method is graph analysis technique. Here a graph is represented in the form of nodes and edges and the various properties may be determined. The wet lab results may be interpreted using statistics. Other studies of metabolomics can be performed using flux based analysis, fourier -transformation, Lp and power laws.


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