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Title: Pathway based Human Disease Clustering and Similarity Analysis Tool Using Frequent Structure Mining
Authors: Mendoza, Delwyn
Keywords: Disease Pathways
Disease Similarity
frequent subgraphs
Hierarchical Clusterning
Issue Date: May-2018
Abstract: Methods in establishing and understanding human disease similarity are in continuous development as the result from these methods may provide new insights in the fi eld of medicine. Furthermore being able to mine and visualize frequent subgraphs enables the users to view the shared components and relations among the specifi ed diseases. Through the use of a graph mining algorithm called FP-GraphMiner and the pathway database of Kyoto Encyclopedia of Genes and Genomes, graph representation and frequent subgraph mining on human diseases is now possible. Disease Similarity Analyzer is a tool which aims to show disease similarity using hierarchical clustering and visualize frequent substructures in human disease pathways using FP-GraphMiner algorithm.
Appears in Collections:Computer Science SP

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