Stanford Center for Biomedical Informatics Research, Stanford University, Stanford, California 94305, USA.
J Am Med Inform Assoc. 2012 Jun;19(e1):e177-86. doi: 10.1136/amiajnl-2011-000631. Epub 2012 Apr 11.
Profiling the allocation and trend of research activity is of interest to funding agencies, administrators, and researchers. However, the lack of a common classification system hinders the comprehensive and systematic profiling of research activities. This study introduces ontology-based annotation as a method to overcome this difficulty. Analyzing over a decade of funding data and publication data, the trends of disease research are profiled across topics, across institutions, and over time.
This study introduces and explores the notions of research sponsorship and allocation and shows that leaders of research activity can be identified within specific disease areas of interest, such as those with high mortality or high sponsorship. The funding profiles of disease topics readily cluster themselves in agreement with the ontology hierarchy and closely mirror the funding agency priorities. Finally, four temporal trends are identified among research topics.
This work utilizes disease ontology (DO)-based annotation to profile effectively the landscape of biomedical research activity. By using DO in this manner a use-case driven mechanism is also proposed to evaluate the utility of classification hierarchies.
对资金机构、管理人员和研究人员来说，分析研究活动的分配和趋势是很有意义的。但是，缺乏通用的分类系统阻碍了对研究活动的全面和系统的分析。本研究介绍了基于本体论的注释方法来克服这一困难。通过分析十多年的资助数据和出版数据，本研究从多个角度分析了疾病研究的趋势，包括跨机构和跨时间的趋势。
本研究介绍并探讨了研究资助和分配的概念，并表明在特定的疾病领域，如高死亡率或高资助的疾病领域，可以确定研究活动的领导者。疾病主题的资助情况很容易根据本体论层次结构进行聚类，并且与资助机构的重点密切一致。最后，确定了四个研究主题的时间趋势。
本研究利用基于疾病本体论（DO）的注释有效地分析了生物医学研究活动的格局。通过以这种方式使用 DO，还提出了一种基于用例的机制来评估分类层次结构的效用。
