Journal of Data and Information Science ›› 2019, Vol. 4 ›› Issue (4): 13-25.doi: 10.2478/jdis-2019-0018

• Research Paper • Previous Articles     Next Articles

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

Jane H. Qin1,2,,Jean J. Wang1,2,Fred Y. Ye1()   

  1. 1Jiangsu Key Laboratory of Data Engineering and Knowledge Service, School of Information Management, Nanjing University, Nanjing 210023, China
    2International Joint Informatics Laboratory (IJIL), Nanjing University - University of Illinois, Nanjing - Champaign, China - USA
  • Received:2019-09-24 Revised:2019-11-19 Online:2019-12-11 Published:2019-12-19
  • Contact: Jane H. Qin E-mail:yye@nju.edu.cn

Abstract:

Purpose: To reveal the research hotpots and relationship among three research hot topics in biomedicine, namely CRISPR, iPS (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.

Key words: co-occurrence, Network analysis, Information visualization, Biomedicine, Hot topics, CRISPR-Cas, iPS cell, Synthetic biology