Copyright
©The Author(s) 2024.
World J Diabetes. May 15, 2024; 15(5): 1021-1044
Published online May 15, 2024. doi: 10.4239/wjd.v15.i5.1021
Published online May 15, 2024. doi: 10.4239/wjd.v15.i5.1021
Figure 1
Screening of research publications related to diabetes and metabolomic.
Figure 2 Analysis of publications related to metabolomics and diabetes.
A: Quantitative analysis of publications and citations; B: Analysis of annual changes in publications and citations.
Figure 3 National analysis of the relationship between metabolomics and diabetes.
A: Map of cooperation networks in all countries; B: Map of national central cooperation network; C: Density map of national cooperation network; D: Ranking map of publications in the top ten countries.
Figure 4 institution analysis of the relationship between metabolomics and diabetes.
A: Ranking of top ten institutional publications; B: Time chart of top five institutional publications; C: Organization cooperation network map with more than 500 citations; D: Central cooperation relationship diagram of institutions.
Figure 5 Journal analysis of the correlation between metabolomics and diabetes.
A: Ranking of publications in the top ten journals; B: Density heat map of journal publications with more than 200 citations; C: Core journal collection; D: Journal double graph overlay.
Figure 6 Fund analysis of the correlation between metabolomics and diabetes.
A: Map of the proportion of top ten fund; B: Frequency and number of countries in the top ten fund project.
Figure 7 Authors analysis of the relationship between metabolomics and diabetes.
A: Author collaboration network map; B: Co-citated collaboration network map.
Figure 8 Co-occurrence analysis of keywords related to metabolomics and diabetes.
A: Network map of top 50 keywords; B: Block map of frequency and proportion of top 50 keywords; C: Centrality network map of keywords; D: Top 40 keywords density heat map.
Figure 9 Keywords cluster analysis of correlation between metabolomics and diabetes.
A: Keywords clustering map label; B: Time variation map of keywords clustering; C: Multiple keywords correspondence analysis map; D: Clustering map of top 50 keywords.
Figure 10
Analysis of keywords related to metabolomics and diabetes by burst detection, including the top 82 burst words.
- Citation: Li H, Li L, Huang QQ, Yang SY, Zou JJ, Xiao F, Xiang Q, Liu X, Yu R. Global status and trends of metabolomics in diabetes: A literature visualization knowledge graph study. World J Diabetes 2024; 15(5): 1021-1044
- URL: https://www.wjgnet.com/1948-9358/full/v15/i5/1021.htm
- DOI: https://dx.doi.org/10.4239/wjd.v15.i5.1021