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Inferring biochemical routes from biochemical networks

Ghosh, Soma and Vishveshwara, Saraswathi and Chandra, Nagasuma (2013) Inferring biochemical routes from biochemical networks. In: 4th Annual ORNL Biomedical Sciences and Engineering Conference on Collaborative Biomedical Innovations, MAY 21-23, 2013, Biomed Sci & Engn Ctr, Oak Ridge Natl Lab, Oak Ridge, TN.

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Official URL: http://dx.doi.org/ 10.1109/BSEC.2013.6618500

Abstract

Metabolism is a defining feature of life, and its study is important to understand how a cell works, alterations that lead to disease and for applications in drug discovery. From a systems perspective, metabolism can be represented as a network that captures all the metabolites as nodes and the inter-conversions among pairs of them as edges. Such an abstraction enables the networks to be studied by applying graph theory, particularly, to infer the flow of chemical information in the networks by identifying relevant metabolic pathways. In this study, different weighting schemes are used to illustrate that appropriately weighted networks can capture the quantitative cellular dynamics quite accurately. Thus, the networks now combine the elegance and simplicity of representation of the system and ease of analysing metabolic graphs. Metabolic routes or paths determined by this therefore are likely to be more biologically meaningful. The usefulness of the approach is demonstrated with two examples, first for understanding bacterial stress response and second for studying metabolic alterations that occurs in cancer cells.

Item Type: Conference Proceedings
Additional Information: Copy right for this article belongs to the IEEE, 345 E 47TH ST, NEW YORK, NY 10017 USA
Department/Centre: Division of Biological Sciences > Molecular Biophysics Unit
Depositing User: Id for Latest eprints
Date Deposited: 10 Oct 2014 09:15
Last Modified: 10 Oct 2014 09:15
URI: http://eprints.iisc.ac.in/id/eprint/49999

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