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The Arrowsmith Project: 2005 Status Report

机译:arrowsmith项目:2005年状态报告

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In the 1980s, Don Swanson proposed the concept of “undiscovered public knowledge,” and published several examples in which two disparate literatures (i.e., sets of articles having no papers in common, no authors in common, and few cross-citations) nevertheless held complementary pieces of knowledge that, when brought together, made compelling and testable predictions about potential therapies for human disorders. In the 1990s, Don and I published more predictions together and created a computer-assisted search strategy (“Arrowsmith”). At first, the so-called one-node search was emphasized, in which one begins with a single literature (e.g., that dealing with a disease) and searches for a second unknown literature having complementary knowledge (e.g. that dealing with potential therapies). However, we soon realized that the two-node search is better aligned to the information practices of most biomedical investigators: in this case, the user chooses two literatures and then seeks to identify meaningful links between them. Could typical biomedical investigators learn to carry out Arrowsmith analyses? Would they find routine occasions for using such a sophisticated tool? Would they uncover significant links that affect their experiments? Four years ago, we initiated a project to answer these questions, working with several neuroscience field testers. Initially we expected that investigators would spend several days learning how to carry out searches, and would spend several days analyzing each search. Instead, we completely re-designed the user interface, the back-end databases, and the methods of processing linking terms, so that investigators could use Arrowsmith without any tutorial at all, and requiring only minutes to carry out a search. The Arrowsmith Project now hosts a suite of free, public tools. It has launched new research spanning medical informatics, genomics and social informatics, and has, indeed, assisted investigators in formulating new experiments, with direct impact on basic science and neurological diseases.
机译:在20世纪80年代,Don Swanson提出了“未被发现的公共知识”的概念,并发表了几个例子,其中两个不同的文献(即没有共同的论文的文章,没有共同的作者,少数跨国公司)仍然存在互补的知识,当聚集在一起时,对人类疾病的潜在疗法进行了引人注目和可测试的预测。在20世纪90年代,唐和我一起发布了更多的预测,并创建了一种计算机辅助搜索策略(“arrowsmith”)。首先,强调了所谓的单节点搜索,其中一个人从单一文献(例如,处理疾病)开始,并搜索具有互补知识的第二个未知文献(例如,处理潜在疗法)。但是,我们很快意识到两节点搜索更好地对齐到大多数生物医学调查人员的信息实践:在这种情况下,用户选择两个文献,然后寻求识别它们之间的有意义链接。典型的生物医学调查人员可以学会进行箭头分析吗?他们会发现使用这种复杂的工具的例行吗?他们会发现影响他们实验的重要链接吗?四年前,我们启动了一个项目来回答这些问题,使用几个神经科学现场测试人员。最初,我们预计调查人员将花几天学习如何进行搜索,并将花费几天分析每个搜索。相反,我们完全重新设计了用户界面,后端数据库和处理链接条款的方法,因此调查人员可以在没有任何教程的情况下使用arrowsmith,并且只需要分钟来执行搜索。 arrowsmith项目现在举办免费公共工具套件。它推出了新的研究跨越医学信息,基因组学和社会信息学,并确实有助于调查人员在制定新的实验中,直接影响基础科学和神经疾病。

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