Title

Pathway based human disease clustering and similarity analysis tool using frequent structure mining

College

College of Science

Department/Unit

Mathematics and Statistics Department

Document Type

Conference Proceeding

Source Title

2018 9th International Conference on Information, Intelligence, Systems and Applications, IISA 2018

Publication Date

2-1-2019

Abstract

©2018 IEEE Methods in establishing and understanding human disease similarity are in continuous development as the result from these methods may provide new insights in the field of medicine. Furthermore being able to mine and visualize frequent subgraphs enables the users to view the shared components and relations among the specified diseases. Through the use of a graph mining algorithm called FP-GraphMiner and the pathway database of Kyoto Encyclopedia of Genes and Genomes(KEGG), 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.

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Digitial Object Identifier (DOI)

10.1109/IISA.2018.8633639

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