Chen Chou-Cheng, Ho Chung-Liang
Institute of Basic Medical Sciences, College of Medicine, National Cheng Kung University, Tainan, Taiwan.
Institute of Basic Medical Sciences, College of Medicine, National Cheng Kung University, Tainan, Taiwan ; Department of Pathology, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, Taiwan ; Infectious Disease and Signaling Research Center, National Cheng Kung University, Tainan, Taiwan, Department of Medical Laboratory Science and Biotechnology, College of Medicine, National Cheng Kung University, Tainan, Taiwan.
Bioinformation. 2014 Nov 27;10(11):708-10. doi: 10.6026/97320630010708. eCollection 2014.
While a huge amount of information about biological literature can be obtained by searching the PubMed database, reading through all the titles and abstracts resulting from such a search for useful information is inefficient. Text mining makes it possible to increase this efficiency. Some websites use text mining to gather information from the PubMed database; however, they are database-oriented, using pre-defined search keywords while lacking a query interface for user-defined search inputs. We present the PubMed Abstract Reading Helper (PubstractHelper) website which combines text mining and reading assistance for an efficient PubMed search. PubstractHelper can accept a maximum of ten groups of keywords, within each group containing up to ten keywords. The principle behind the text-mining function of PubstractHelper is that keywords contained in the same sentence are likely to be related. PubstractHelper highlights sentences with co-occurring keywords in different colors. The user can download the PMID and the abstracts with color markings to be reviewed later. The PubstractHelper website can help users to identify relevant publications based on the presence of related keywords, which should be a handy tool for their research.
http://bio.yungyun.com.tw/ATM/PubstractHelper.aspx and http://holab.med.ncku.edu.tw/ATM/PubstractHelper.aspx.
虽然通过搜索PubMed数据库可以获取大量有关生物文献的信息，但逐一审视此类搜索结果中的所有标题和摘要以寻找有用信息效率低下。文本挖掘能够提高这一效率。一些网站利用文本挖掘从PubMed数据库收集信息；然而，它们以数据库为导向，使用预定义的搜索关键词，却缺乏用于用户定义搜索输入的查询界面。我们展示了PubMed摘要阅读助手（PubstractHelper）网站，该网站结合了文本挖掘和阅读辅助功能，以实现高效的PubMed搜索。PubstractHelper最多可接受十组关键词，每组最多包含十个关键词。PubstractHelper文本挖掘功能背后的原理是，同一句子中包含的关键词可能相关。PubstractHelper会用不同颜色突出显示包含同时出现关键词的句子。用户可以下载带有颜色标记的 PMID 和摘要以便日后查看。PubstractHelper网站可以帮助用户根据相关关键词的存在来识别相关出版物，这对他们的研究来说应该是一个便捷的工具。
http://bio.yungyun.com.tw/ATM/PubstractHelper.aspx 和 http://holab.med.ncku.edu.tw/ATM/PubstractHelper.aspx。
