期刊文献+

国际肝干细胞研究文献可视化分析 被引量:3

Visualization analysis in international liver stem cells research
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摘要 目的对国际肝干细胞研究文献进行可视化分析,为把握重点研究方向、选择前沿技术课题、进行科学合理的科技布局提供决策信息支持。方法利用文献计量学方法和信息可视化方法对WebofScience中的SCIE数据库收录的国际肝干细胞研究文献的时间、国别、机构、期刊、学科、主题进行分析。结果科学引文索引扩展版(SCIE)收录了1092篇肝干细胞研究文献,自2000年开始文献数量进入快速增长期;在文献数量上中国与美国、日本差距较大;肝干细胞研究属多学科交叉领域,但发表期刊相对集中;其研究基本上经历了肝干细胞的发现辨认、来源和基础应用研究阶段;研究前沿有肝干细胞的识别和移植后鉴定、参与肝再生机制、诱导分化、外源基因的表达等。结论中国应加大肝干细胞资金投入、加强与顶级科研院所的交流合作、自主创新,引导肝干细胞从基础研究向临床研究转化。 Objective To provide decisionmaking information support for recognizing research trends, selecting frontier science and technology, shaping reasonable science and technology distribution, a visualization analysis was applied to the international liver stem cell research. Methods Based on bibliometric method and visualization analysis tools, various fields including publication years, countries of publications, journals and organizations were analyzed exhaustively on publications of international liver stem cells which were searched in Science Citation Index Expanded (SCIE).In addition, details on main subjects, evolution and research fronts were presented in this paper. Results 1092 publications were searched in SCIE,which were growing rapidly since 2000.The production of China is far behind United States of America and Japan. Publications were distributed in concentrated journals but involved multidisciplinary. Liver stem cells research evolution basically experienced identification,sources,basic application. Research fronts include cell identifications, liver regeneration, cell differentiation, expression of exogenous genes,etc. Conclusion China should increase the liver stem cell funding, strengthen cooperation with the top institutes, independent innovation, leading liver stem cells research from basic research to clinical research.
出处 《解剖学报》 CAS CSCD 北大核心 2010年第2期318-322,共5页 Acta Anatomica Sinica
基金 中国医学科学院医学信息研究所中央级公益性基本科研业务费资助项目(08R1029)
关键词 肝干细胞 文献计量学 可视化分析 共词分析 共引分析 聚类分析 Liver stem cell Bibliometrics Visualization analysis Co-word analysis Co-citation analysis Cluster analysis
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