数据挖掘在生物信息学中的应用——文献计量学视角

Application of data mining in bioinformatics——bibliometrics perspective

基因组和蛋白质结构与功能方面已积累了海量数据。如何从海量数据中获取有效信息成为生物信息学迫切要解决的问题。本文以相关主题词检索文献,分析了该领域历年文章数量、发文最多的机构和作者、被引用频次居前论文、期刊载文量,并对关键词和被引用频次居前论文的作者进行共现分析。我们发现,生物信息学中运用数据挖掘方法的文献逐年增多,该领域30.1%的文献发表在十个期刊上,分类、聚类、特征选择和支持向量机等数据挖掘方法使用较多。本研究描绘了生物信息学与数据挖掘这一交叉领域的研究概况,为后续数据挖掘方法与生物信息学研究相结合提供帮助。

Massive data is accumulated in the aspects of genome,structure and function of protein. How to access effective information is the challenge of bioinformatics. We search the literature with the related subject heading,analyze the number of literature each year,the research organizations and authors publishing most papers,the highly cited frequency papers and the number of papers in journals,and explore the keywords and authors of highly cited frequency literatures with co-occurrence analysis respectively. The results show that the literature using data mining methods increases yearly and that the literature publishes in ten journals accounts for 30.1 percentage,and that classification,clustering,feature selection and support vector machine are mostly used the methods in bioinformatics. This study depicts the overview of the crossing field of data mining and bioinformatics. It is helpful for combining the bioinformatics with data mining.