Pathway based human disease clustering and similarity analysis tool using frequent structure mining
College of Science
Mathematics and Statistics Department
2018 9th International Conference on Information, Intelligence, Systems and Applications, IISA 2018
©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.
Digitial Object Identifier (DOI)
Mendoza, D., Lao, A., & Solano, G. (2019). Pathway based human disease clustering and similarity analysis tool using frequent structure mining. 2018 9th International Conference on Information, Intelligence, Systems and Applications, IISA 2018 https://doi.org/10.1109/IISA.2018.8633639