Exploring biological research hotspots through a novel bibliometric approach

Chen, Shan, Wang, Junsha, Huang, Xinyu, Chen, Kailin, Fu, Limei and Ding, Yuanzhao 2026. Exploring biological research hotspots through a novel bibliometric approach. Computational Biology and Chemistry 120 (Part 1) , 108680. 10.1016/j.compbiolchem.2025.108680

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Abstract

Biological research is a crucial field of study, profoundly impacting every aspect of human life. The objective of this study is to utilize an innovative bibliometric analysis method to understand current research hotspots and future trends in biology. This novel bibliometric analysis method, based on the R programming language, offers a completely different approach than traditional VOSviewer, providing a more in-depth analysis. Based on the bibliometric analysis results, this paper also proposes potential future developments, namely, integrating big data with machine learning. By integrating existing data into large databases and then training models, this approach can provide deep insights and accurate predictions for the future.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Schools > Computer Science & Informatics
Additional Information:	License information from Publisher: LICENSE 1: Title: This article is under embargo with an end date yet to be finalised.
Publisher:	Elsevier
ISSN:	1476-9271
Date of Acceptance:	8 September 2025
Last Modified:	18 Sep 2025 09:46
URI:	https://orca.cardiff.ac.uk/id/eprint/181164

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