Abstract
Abstract The Kyoto Encyclopedia of Genes and Genomes (KEGG) Pathway is a database that contains a graphical representation of cellular processes. Cellular processes are basic systems involving biochemical reactions at the cellular level such as transport, catabolism, metabolism, growth and cell death. The KEGG Pathway information is shown through the use of graphs, in which the molecular interactions between genes, processes and chemical compounds are represented. This paper proposes to perform Data Analytics using the Big Data Analytics Life Cycle methodology to enrich the metabolic pathways of the KEGG Pathway database by applying the Target Fishing technique.
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