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Multi-genome Core Pathway Identification through Gene Clustering

Abstract : In the wake of gene-oriented data analysis in large-scale bioinformatics studies, focus in research is currently shifting towards the analysis of the functional association of genes, namely the metabolic pathways in which genes participate. The goal of this paper is to attempt to identify the core genes in a specific pathway, based on a user-defined selection of genomes. To this end, a novel methodology has been developed that uses data from the KEGG database, and through the application of the MCL clustering algorithm, identifies clusters that correspond to different “layers” of genes, either on a phylogenetic or a functional level. The algorithm’s complexity, evaluated experimentally, is presented and the results on a characteristic case study are discussed.
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Dimitrios Vitsios, Fotis Psomopoulos, Pericles Mitkas, Christos Ouzounis. Multi-genome Core Pathway Identification through Gene Clustering. 8th International Conference on Artificial Intelligence Applications and Innovations (AIAI), Sep 2012, Halkidiki, Greece. pp.545-555, ⟨10.1007/978-3-642-33412-2_56⟩. ⟨hal-01523039⟩



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