Abstract
Modeling and analyzing the architecture of metabolic networks using various computational strategies can be successfully used for studying their internal metabolic dynamics as well as predicting missing links in diseased networks. In the present work, we have implemented our algorithm based on structural grammars, for automated metabolic pathway reconstruction and modeling in metabolic pathways responsible for coding genes responsible for the cause of Type 1 Diabetes mellitus (T1D) in Homo sapiens. We have especially implemented our algorithm for studying the metabolic pairs responsible for the functioning of GAD1 and GAD2 genes. We have also used the algorithm for automated reconstruction of glutamate metabolism, β-alanine metabolism, taurine & hypotaurine metabolism and butanoate metabolism pathway datasets. We have also used the algorithm for missing and multiple link prediction as well as nodal point analysis for all the four metabolic pathways with 90.4-100% accuracy.
Highlights
Introduction and BackgroundMetabolic pathway modeling is one of the most essential areas in the post-genomic era
We implemented our algorithm to four metabolic pathways, namely, glutamate metabolism, β-alanine metabolism, taurine & hypotaurine metabolism and butanoate metabolism, responsible for the functioning of GAD1 and GAD2 genes involved in Type 1 Diabetes mellitus (T1D)
We were interested in analyzing the reactions catalyzed by the enzymes which can be further analyzed for studying the expression analysis of GAD1 and GAD2
Summary
Introduction and BackgroundMetabolic pathway modeling is one of the most essential areas in the post-genomic era. Computational models based on biological constraints can be built which are further used to relate the developed models with their biological behaviors [1]. These theoretical models can be further trained in order to analyze and simulate these complex networks of different organisms and tissues. Computational models can be used for simulating the function of metabolic pathways, thereby improving the understanding of the structure of cellular processes. Automated reconstruction is a process of building the complete metabolic network given some input metabolites and their constraints is a flourishing and fast developing domain [2]
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