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A Metric Approach to Hot Topics in Biomedicine via Keyword Co-occurrence

Authors
  • Qin, Jane H.1, 2
  • Wang, Jean J.1, 2
  • Ye, Fred Y.1, 2
  • 1 Jiangsu Key Laboratory of Data Engineering and Knowledge Service, School of Information Management, Nanjing University, 210023 , (China)
  • 2 International Joint Informatics Laboratory (IJIL), Nanjing University – University of Illinois, Nanjing – Champaign, USA , (United States)
Type
Published Article
Journal
Journal of Data and Information Science
Publisher
Sciendo
Publication Date
Dec 27, 2019
Volume
4
Issue
4
Pages
13–25
Identifiers
DOI: 10.2478/jdis-2019-0018
Source
De Gruyter
Keywords
License
Green

Abstract

Purpose To reveal the research hotpots and relationship among three research hot topics in biomedicine, namely CRISPR, i PS (induced Pluripotent Stem) cell and Synthetic biology. Design/methodology/approach We set up their keyword co-occurrence networks with using three indicators and information visualization for metric analysis. Findings The results reveal the main research hotspots in the three topics are different, but the overlapping keywords in the three topics indicate that they are mutually integrated and interacted each other. Research limitations All analyses use keywords, without any other forms. Practical implications We try to find the information distribution and structure of these three hot topics for revealing their research status and interactions, and for promoting biomedical developments. Originality/value We chose the core keywords in three research hot topics in biomedicine by using h-index.

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