Arrowsmith two-node search interface: A tutorial on finding meaningful links between two disparate sets of articles in MEDLINE

计算机科学 节点(物理) 多样性(控制论) 情报检索 接口(物质) 数据科学 服务(商务) 钥匙(锁) 人工智能 最大气泡压力法 工程类 经济 气泡 经济 并行计算 结构工程 计算机安全
作者
Neil R. Smalheiser,Vetle I. Torvik,Wei Zhou
出处
期刊:Computer Methods and Programs in Biomedicine [Elsevier]
卷期号:94 (2): 190-197 被引量:61
标识
DOI:10.1016/j.cmpb.2008.12.006
摘要

The Arrowsmith two-node search is a strategy that is designed to assist biomedical investigators in formulating and assessing scientific hypotheses. More generally, it allows users to identify biologically meaningful links between any two sets of articles A and C in PubMed, even when these share no articles or authors in common and represent disparate topics or disciplines. The key idea is to relate the two sets of articles via title words and phrases (B-terms) that they share. We have created a free, public web-based version of the two-node search tool (http://arrowsmith.psych.uic.edu), have described its development and implementation, and have presented analyses of individual two-node searches. In this paper, we provide an updated tutorial intended for end-users, that covers the use of the tool for a variety of potential scientific use case scenarios. For example, one can assess a recent experimental, clinical or epidemiologic finding that connects two disparate fields of inquiry--identifying likely mechanisms to explain the finding, and choosing promising follow-up lines of investigation. Alternatively, one can assess whether the existing scientific literature lends indirect support to a hypothesis posed by the user that has not yet been investigated. One can also employ two-node searches to search for novel hypotheses. Arrowsmith provides a service that cannot be carried out feasibly via standard PubMed searches or by other available text mining tools.
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