Smalheiser Neil R, Torvik Vetle I, Zhou Wei
Department of Psychiatry and Psychiatric Institute, MC912, University of Illinois at Chicago, 1601W. Taylor Street, Chicago, IL 60612, USA.
Comput Methods Programs Biomed. 2009 May;94(2):190-7. doi: 10.1016/j.cmpb.2008.12.006. Epub 2009 Jan 30.
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.
阿罗史密斯双节点搜索是一种旨在协助生物医学研究人员制定和评估科学假设的策略。更一般地说,它允许用户在PubMed中识别任意两组文章A和C之间具有生物学意义的联系,即使这两组文章没有共同的文章或作者,并且代表不同的主题或学科。关键思想是通过它们共享的标题词和短语(B术语)将这两组文章联系起来。我们创建了一个免费的、基于网络的双节点搜索工具公共版本(http://arrowsmith.psych.uic.edu),描述了其开发和实施过程,并展示了对单个双节点搜索的分析。在本文中,我们为最终用户提供了一个更新的教程,涵盖了该工具在各种潜在科学用例场景中的使用。例如,人们可以评估最近一项将两个不同研究领域联系起来的实验、临床或流行病学发现——识别解释该发现的可能机制,并选择有前景的后续研究方向。或者,人们可以评估现有科学文献是否为用户提出的尚未研究的假设提供间接支持。人们还可以使用双节点搜索来寻找新的假设。阿罗史密斯提供了一项通过标准PubMed搜索或其他可用文本挖掘工具无法切实可行地执行的服务。