Development of Network Analysis and Visualization System for KEGG Pathways

Symmetry

Dongmin Seo²  Min-Ho Lee¹  Seok Jong Yu² 

[1] Department of Big Data Science, University of Science & Technology, Daejeon 305-350, Korea;Department of Biomedical Convergence Technology, Korea Institute of Science and Technology Information, Daejeon 305-806, Korea

关键词: network analysis;    network cluster;    network visualization;    KEGG pathway;    bioinformatics;   

DOI  :  10.3390/sym7031275

来源: mdpi

【 摘 要 】

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.

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland.