Zhang Yanyan, Mao Yukang, Fu Qiangqiang, Zhang Xiaoguang, Zhang Dong, Yue Yunhua, Yang Chuanxi
Department of Neurology, Yangpu Hospital, School of Medicine, Tongji University, Shanghai, China.
Department of Cardiology, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Suzhou, Jiangsu, China.
Front Neurosci. 2024 Oct 9;18:1414603. doi: 10.3389/fnins.2024.1414603. eCollection 2024.
Epigenetics has significantly evolved and emerged as important players in the pathogenesis of neurodegenerative diseases. However, a scientometric synthesis of such changes over time is currently lacking.
We conducted a comprehensive search of the Web of Science Core Collection from inception until November 5, 2022, using appropriate keywords. Our primary objective was to employ scientometric analysis to depict changes in keywords over time and to assess the structure and credibility of clusters. Additionally, we examined the network of research (countries, institutions, and authors) using CiteSpace and VOSviewer.
We identified 25 clusters with well-structured networks ( = 0.82) and highly credible clustering ( = 0.91) from 16,181 articles published between 1999 and 2022. Our findings are as follows: (a) the literature and research interest concerning the epigenetics of neurodegenerative diseases are continuously growing; (b) the three most productive countries are the USA, China, and Germany; (c) international collaborative relationships exist, alongside small, isolated collaboration networks of individual institutions.
The number and impact of global publications on the epigenetics of neurodegenerative diseases have expanded rapidly over the past 20 years. This review provides valuable guidelines for researchers interested in neurodegenerative diseases research.
表观遗传学已显著发展,并在神经退行性疾病的发病机制中成为重要因素。然而,目前缺乏对这些随时间变化的科学计量学综合分析。
我们使用适当的关键词,对科学网核心合集从创刊到2022年11月5日进行了全面检索。我们的主要目标是采用科学计量学分析来描述关键词随时间的变化,并评估聚类的结构和可信度。此外,我们使用CiteSpace和VOSviewer研究了研究网络(国家、机构和作者)。
我们从1999年至2022年发表的16181篇文章中识别出25个聚类,其网络结构良好( = 0.82)且聚类可信度高( = 0.91)。我们的研究结果如下:(a)关于神经退行性疾病表观遗传学的文献和研究兴趣在持续增长;(b)产出最多的三个国家是美国、中国和德国;(c)存在国际合作关系,以及个别机构的小型孤立合作网络。
在过去20年里,全球关于神经退行性疾病表观遗传学的出版物数量和影响力迅速扩大。本综述为对神经退行性疾病研究感兴趣的研究人员提供了有价值的指导方针。