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. 2023 Nov 15:13:1222797.
doi: 10.3389/fonc.2023.1222797. eCollection 2023.

Quantitative study of bioinformatics analysis on glioma: a bibliometric analysis

Xiaobing Yang  1   2   3 , Dulegeqi Man  4 , Peng Zhao #  1   2   3 , Xingang Li #  1   2   3
Affiliations

Quantitative study of bioinformatics analysis on glioma: a bibliometric analysis

Xiaobing Yang et al. Front Oncol. .

Abstract

Background: The bioinformatics analysis on glioma has been a hot point recently. The purpose of this study was to provide an overview of the research in this field using a bibliometric method.

Methods: The Web of Science Core Collection (WOSCC) database was used to search for literature related to the bioinformatics analysis of gliomas. Countries, institutions, authors, references, and keywords were analyzed using VOSviewer, CiteSpace, and Microsoft Excel software.

Result: China was the most productive country, while the USA was the most cited. Capital Medical University had the largest number of publications and citations. Institutions tend to collaborate more with other institutions in their countries rather than foreign ones. The most productive and most cited author was Jiang Tao. Two citation paths were identified, with literature in basic research journals often cited in clinical journals. Immune-related vocabularies appeared frequently in recent studies.

Conclusion: Glioma bioinformatics analyses spanned a wide range of fields. The international communication in this field urgently needs to be strengthened. Glioma bioinformatics approaches are developing from basic research to clinical applications. Recently, immune-related research has become a focus.

Keywords: Citespace; VOSviewer; bibliometric analysis; bioinformatic; glioma.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Flowchart of the analysed and excluded articles.
Figure 2
Figure 2
Trends in publications and citations.
Figure 3
Figure 3
(A) Collaboration network of countries/regions. (B) Citation network of countries/regions. (C) Top 10 countries by publications. (D) Top 10 countries by total citations.
Figure 4
Figure 4
(A) Coauthorship analysis of institutions according to clusters. (B) The timestamp visualization of coauthorship among institutions. (C) Citation network of institutions according to clusters. (D) The timestamp visualization of relationships among institutions.
Figure 5
Figure 5
(A) Coauthorship analysis of authors according to clusters. (B) The timestamp visualization of coauthorship among authors. (C) Citation network of authors according to clusters. (D) The timestamp visualization of relationships among authors.
Figure 6
Figure 6
(A) Cocitation analysis of references according to clusters. (B) Density map of cocited analysis of references.
Figure 7
Figure 7
Visualization map of the top 25 references with the strongest citation bursts from 2003 to 2022.
Figure 8
Figure 8
The dual-map overlay of journals. The more papers the journal publishes, the longer the vertical axis of the ellipse, and the greater the number of authors, the longer the horizontal axis of the ellipse.
Figure 9
Figure 9
(A) Overlay map of keywords. (B) The timestamp visualization of keywords.
See this image and copyright information in PMC

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