Big data refers to informationalization technology for extracting valuable information\nthrough the use and analysis of large-scale data and, based on that data, deriving plans for\nresponse or predicting changes. With the development of software and devices for next\ngeneration sequencing, a vast amount of bioinformatics data has been generated recently.\nAlso, bioinformatics data based big-data technology is rising rapidly as a core technology\nby the bioinformatician, biologist and big-data scientist. KEGG pathway is bioinformatics\ndata for understanding high-level functions and utilities of the biological system. However,\nKEGG pathway analysis requires a lot of time and effort because KEGG pathways are high\nvolume and very diverse. In this paper, we proposed a network analysis and visualization\nsystem that crawl user interest KEGG pathways, construct a pathway network based on a\nhierarchy structure of pathways and visualize relations and interactions of pathways by\nclustering and selecting core pathways from the network. Finally, we construct a pathway\nnetwork collected by starting with an Alzheimer�s disease pathway and show the results on\nclustering and selecting core pathways from the pathway network.
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