Paper Info
Title
Development of Network Analysis and Visualization System for KEGG Pathways
Abstract
Big data refers to informationalization technology for extracting valuable information through the use and analysis of large-scale data and, based on that data, deriving plans for response or predicting changes. With the development of software and devices for next generation sequencing, a vast amount of bioinformatics data has been generated recently. Also, bioinformatics data based big-data technology is rising rapidly as a core technology by the bioinformatician, biologist and big-data scientist. KEGG pathway is bioinformatics data for understanding high-level functions and utilities of the biological system. However, KEGG pathway analysis requires a lot of time and effort because KEGG pathways are high volume and very diverse. In this paper, we proposed a network analysis and visualization system that crawl user interest KEGG pathways, construct a pathway network based on a hierarchy structure of pathways and visualize relations and interactions of pathways by clustering and selecting core pathways from the network. Finally, we construct a pathway network collected by starting with an Alzheimer's disease pathway and show the results on clustering and selecting core pathways from the pathway network.
Year
DOI
Venue
2015
10.3390/sym7031275
SYMMETRY-BASEL
Keywords
Field
DocType
network analysis,network cluster,network visualization,KEGG pathway,bioinformatics
Graph drawing,Data mining,Visualization,Computer science,KEGG,Software,Disease Pathway,Network analysis,Cluster analysis,Big data
Journal
Volume
Issue
ISSN
7
3.0
2073-8994
Citations 
PageRank 
References 
0
0.34
6
Authors
3
Name
Order
Citations
PageRank
Dongmin Seo14910.64
Min Ho Lee2226.85
Seok Jong Yu3182.15