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Applying Automatically Derived Gene-Groups to Automatically Predict and Refine Metabolic Pathways
July/August 2003 (vol. 15 no. 4)
pp. 883-894

Abstract—This paper describes an automated technique to predict integrated pathways and refine existing metabolic pathways using the information of automatically derived, functionally similar gene-groups and orthologs (functionally equivalent genes) derived by the comparison of complete microbial genomes archived in GenBank. The described method integrates automatically derived orthologous and homologous gene-groups (http://www.mcs.kent.edu/~arvind/orthos.html) with the biochemical pathway template available at the KEGG database (http://www.genome.ad.jp), the enzyme information derived from the SwissProt enzyme database (http://expasys.hcuge.ch/), and the Ligand database (http://www.genome.ad.jp). The technique refines existing pathways (based upon the network of reactions of enzymes) by associating corresponding nonenzymatic and regulatory proteins to enzymes and operons and by identifying substituting homologs. The technique is suitable for building and refining integrated pathways using evolutionary diverse organisms. A methodology and the corresponding algorithm are presented. The technique is illustrated by comparing the genomes of E. coli and B. subtilis with M. tuberculosis. The findings about integrated pathways are briefly discussed.

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Index Terms:
Automation, bacteria, drug-discovery, enzymes, gene-groups, homologs, metabolic pathway, microbes, operons, orthologs, pathogenicity, pathway.
Citation:
Arvind K. Bansal, Christopher J. Woolverton, "Applying Automatically Derived Gene-Groups to Automatically Predict and Refine Metabolic Pathways," IEEE Transactions on Knowledge and Data Engineering, vol. 15, no. 4, pp. 883-894, July-Aug. 2003, doi:10.1109/TKDE.2003.1209006
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