{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,13]],"date-time":"2026-01-13T08:34:34Z","timestamp":1768293274643,"version":"3.49.0"},"reference-count":22,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2015,7,16]],"date-time":"2015-07-16T00:00:00Z","timestamp":1437004800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Symmetry"],"abstract":"<jats:p>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\u2019s disease pathway and show the results on clustering and selecting core pathways from the pathway network.<\/jats:p>","DOI":"10.3390\/sym7031275","type":"journal-article","created":{"date-parts":[[2015,7,16]],"date-time":"2015-07-16T10:11:44Z","timestamp":1437041504000},"page":"1275-1288","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Development of Network Analysis and Visualization System for KEGG Pathways"],"prefix":"10.3390","volume":"7","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3404-1172","authenticated-orcid":false,"given":"Dongmin","family":"Seo","sequence":"first","affiliation":[{"name":"Department of Biomedical Convergence Technology, Korea Institute of Science and Technology Information, Daejeon 305-806, Korea"},{"name":"Department of Big Data Science, University of Science & Technology, Daejeon 305-350, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Min-Ho","family":"Lee","sequence":"additional","affiliation":[{"name":"Department of Big Data Science, University of Science & Technology, Daejeon 305-350, Korea"},{"name":"Biomedical HPC Technology Research Center, Korea Institute of Science and Technology Information, Daejeon 305-806, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Seok","family":"Yu","sequence":"additional","affiliation":[{"name":"Department of Biomedical Convergence Technology, Korea Institute of Science and Technology Information, Daejeon 305-806, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2015,7,16]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"575","DOI":"10.5392\/JKCA.2013.13.12.575","article-title":"Intelligent Web Crawler for Supporting Big Data Analysis Services","volume":"13","author":"Seo","year":"2013","journal-title":"J. Korea Contents Assoc."},{"key":"ref_2","unstructured":"Sung, W.K., Lee, S.H., Jung, H.M., Park, K.S., Lee, S.W., Kim, S.T., Hwang, M.N., and Jo, M.H. (2013). Planning Research for Digging Promotion Works on Scientific Technology Big-Data and Maximizing Utilization, Ministry of Education and Science Technology."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"6131","DOI":"10.3390\/ijerph10116131","article-title":"Mobile, Cloud, and Big Data Computing: Contributions, Challenges, and New Directions in Telecardiology","volume":"10","author":"Hsieh","year":"2013","journal-title":"Int. J. Environ. Res. Public Health"},{"key":"ref_4","unstructured":"Yun, M.Y. (2012). 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Sci."}],"container-title":["Symmetry"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2073-8994\/7\/3\/1275\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T20:49:18Z","timestamp":1760215758000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2073-8994\/7\/3\/1275"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2015,7,16]]},"references-count":22,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2015,9]]}},"alternative-id":["sym7031275"],"URL":"https:\/\/doi.org\/10.3390\/sym7031275","relation":{},"ISSN":["2073-8994"],"issn-type":[{"value":"2073-8994","type":"electronic"}],"subject":[],"published":{"date-parts":[[2015,7,16]]}}}