Identifying the landscape of Alzheimer's disease research with network and content analysis
Identifying the landscape of Alzheimer's disease research with network and content analysis
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DOI：
10.1007/s11192-014-1372-x
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发表时间：
2015-01-01
期刊：
影响因子：
3.9
通讯作者：
Lee, Dahee
中科院分区：
文献类型：
--
作者：
Song, Min;Heo, Go Eun;Lee, Dahee
阿尔茨海默病（Alzheimer's disease，AD）是一种病因难以准确诊断的脑退行性疾病。随着AD患者数量的增加，研究人员一直在努力了解这种疾病并开发其治疗方法，例如医学实验和文献分析。在文献分析领域，传统的文献分析主要从作者、期刊、机构等宏观层面进行分析。然而，在宏观层面和微观层面的文献分析将允许更好地认识AD研究领域。因此，在这项研究中，我们采用了一个更全面的方法来分析广告文献，其中包括生产力分析（年份，期刊/论文集，作者和医学主题词），网络分析（共现频率，中心性和社区）和内容分析。为此，我们收集了从PubMed检索到的96，081篇文章的元数据。我们具体执行的概念图为基础的网络分析应用五个中心性措施映射后，从AD文献的UMLS概念之间的语义关系。我们还使用Dirichlet多项式回归主题建模技术分析了时间序列的主题趋势。结果表明，2013年是最富有成效的一年，《阿尔茨海默病杂志》是最富有成效的期刊。在发现AD相关PubMed文献中的核心生物学实体及其关系时，发现与糖原累积病的关系最常被提及。此外，我们分析了AD文献的16个主要主题，发现转基因小鼠主题有明显的增长趋势。
Alzheimer's disease (AD) is one of degenerative brain diseases, whose cause is hard to be diagnosed accurately. As the number of AD patients has increased, researchers have strived to understand the disease and develop its treatment, such as medical experiments and literature analysis. In the area of literature analysis, several traditional studies analyzed the literature at the macro level like author, journal, and institution. However, analysis of the literature both at the macro level and micro level will allow for better recognizing the AD research field. Therefore, in this study we adopt a more comprehensive approach to analyze the AD literature, which consists of productivity analysis (year, journal/proceeding, author, and Medical Subject Heading terms), network analysis (co-occurrence frequency, centrality, and community) and content analysis. To this end, we collect metadata of 96,081 articles retrieved from PubMed. We specifically perform the concept graph-based network analysis applying the five centrality measures after mapping the semantic relationship between the UMLS concepts from the AD literature. We also analyze the time-series topical trend using the Dirichlet multinomial regression topic modeling technique. The results indicate that the year 2013 is the most productive year and Journal of Alzheimer's Disease the most productive journal. In discovery of the core biological entities and their relationships resided in the AD related PubMed literature, the relationship with glycogen storage disease is founded most frequently mentioned. In addition, we analyze 16 main topics of the AD literature and find a noticeable increasing trend in the topic of transgenic mouse.