Far East Journal of Experimental and Theoretical Artificial Intelligence
Volume 1, Issue 1, Pages 23 - 43
(February 2008)
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LEARNING WEIGHTS REPRESENTING ENZYME CONCENTRATION: IDENTIFICATION OF METABOLIC PATHWAYS
Rajat K. De (India), Mouli Das (India) and Subhasis Mukhopadhyay (India)
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Abstract: In the present
article, we introduce a composite methodology for identifying metabolic pathways
from reaction database. The methodology, first of all, generates data on
reaction fluxes in a pathway based on biomass conservation constraint. A new
constraint on steady state condition is defined. Finally, the yield of target
metabolite starting with a given substrate is maximized, incorporating weighting
coefficients reflecting concentration levels of enzymes catalyzing the reactions
in the pathway. The effectiveness of the proposed methodology is demonstrated on
three synthetic systems existing in the literature and four real life pathways
of E. coli K-12 MG1655 and C. elegans. |
Keywords and phrases: internal flux, exchange flux, gradient descent technique, optimization, stoichiometric matrix, flux vector. |
Communicated by Shun-Feng Su |
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