使用Scopus数据库对2000年至2023年化学信息学/定量构效关系文献进行文献计量分析，以用于数据科学中的预测建模。
A bibliometric analysis of the Cheminformatics/QSAR literature (2000-2023) for predictive modeling in data science using the SCOPUS database.
作者信息
Banerjee Arkaprava, Roy Kunal, Gramatica Paola
机构信息
Drug Theoretics and Cheminformatics Laboratory, Department of Pharmaceutical Technology, Jadavpur University, Kolkata, 700 032, India.
QSAR Research Unit On Environmental Chemistry and Ecotoxicology, Department of Theoretical and Applied Sciences (DiSTA), University of Insubria, Varese, Italy.
出版信息
Mol Divers. 2024 Dec 5. doi: 10.1007/s11030-024-11056-8.
A bibliometric analysis of the Cheminformatics/QSAR articles published in the present century (2000-2023) is presented based on a SCOPUS search made in October 2024 using a given set of search criteria. The obtained results of 52,415 documents against the specific query are analyzed based on the number of documents per year, contributions of different countries and Institutes in Cheminformatics/QSAR publications, the contributions of researchers based on the number of documents, appearance in the top-cited articles, h-index, composite c-score (ns), and the newly introduced q-score. Finally, a list of the top 50 Cheminformatics/QSAR researchers is presented. An analysis is also made for the content of the top-cited articles during the period 2000-2023 in comparison to those before 2000 to capture the trend of changes in the Cheminformatics/QSAR research. The limiting factors of any bibliometric analysis are also briefly presented.
基于2024年10月使用给定搜索标准在SCOPUS数据库中进行的搜索，对本世纪（2000 - 2023年）发表的化学信息学/定量构效关系（QSAR）文章进行了文献计量分析。根据每年的文献数量、不同国家和机构在化学信息学/QSAR出版物中的贡献、基于文献数量的研究人员贡献、在高被引文章中的出现情况、h指数、综合c分数（ns）以及新引入的q分数，对针对特定查询获得的52415篇文献的结果进行了分析。最后，列出了化学信息学/QSAR领域排名前50的研究人员名单。还对2000 - 2023年期间高被引文章的内容与2000年之前的文章进行了比较分析，以把握化学信息学/QSAR研究的变化趋势。同时简要介绍了任何文献计量分析的限制因素。
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