Arrowsmith Data Mining Techniques in Neuro-Informatics

描述（由申请人提供）：传统的搜索引擎（例如，PubMed） 可以识别Medline记录中包含的信息的许多方面， 对给定主题的当前知识状态的指示。但这种 调查人员在边境工作时， 科学发现，谁需要评估新的可能的意义， 尚未通过实验验证的发现或假设关系 测试.“阿罗史密斯”是一种计算机辅助策略，旨在解决这一问题 通过促进识别存在的信息， 隐式地在数据库内或跨数据库。它通过识别标题来做到这一点 在一对不相交的文献中共享的单词，过滤掉 可能是非信息性的词语，以及仅仅是论文标题 在共享给定标题词的每个文献中，允许用户评估 这两组论文是否暗示了一种具有生物学意义的 当我们一起考虑的时候。为了测试Arrowsmith的可行性， 科学界使用，一组现场测试人员将接受培训， 评估阿罗史密斯分析的可行性和实用性，当用于 多学科神经科学团体的背景下， 实验室和信息学组成部分。通过共享链接文件的效用 取自Medline记录其他字段的术语，例如，抽象词或MeSH 主题词也将被评估。将提供对Arrowsmith的访问 通过一个网站，将升级和扩大，以适应更大的 公众也是。最后，将评估Arrowsmith分析是否可以 帮助促进新的跨学科研究， 独立解决问题的互补研究小组 共同利益，最好通过共同努力来解决。因为 阿罗史密斯方法的一般性，它可以应用于广泛的 生物医学问题，事实上，进行搜索内或跨任何 包含文本材料的数据库。

DESCRIPTION (provided by applicant): Conventional search engines (e.g., PubMed) can identify many facets of information contained in Medline records and give an indication of the current state of knowledge on a given topic. However, such queries are insufficient for investigators operating at the frontiers of scientific discovery, who need to assess the possible significance of new findings or hypothesized relationships that have not yet been experimentally tested. "Arrowsmith" is a computer-assisted strategy designed to address this problem by facilitating the identification of information that is present implicitly within or across databases. It does this by identifying title words that are shared across a pair of disjoint literatures, filtering out words that are likely to be non-informative, and justaposing titles of papers in each literature that share a given title word, allowing the user to assess whether the two sets of papers are suggestive of a biologically meaningful inference when considered together. To test the feasibility of Arrowsmith for use by the scientific community, a set of field testers will be trained to evaluate the feasibility and utility of Arrowsmith analyses when used in the context of multi-disciplinary neuroscience groups that have both significant laboratory and informatics components. The utility of linking papers via shared terms taken from other fields of Medline records, e.g., abstract words or MeSH subject headings, will also be evaluated. Access to Arrowsmith will be provided via a Web site that will be upgraded and expanded to accommodate the larger public as well. Finally, it will be assessed whether Arrowsmith analyses can help facilitate new interdisciplinary research by identifying and alerting complementary groups of investigators who independently are tackling problems of joint interest, that may be best addressed by working together. Because of the generality of the Arrowsmith approach, it may be applied to a wide range of biomedical problems and, indeed, to conduct searches within or across any databases that contain textual material.