Arrowsmith Data Mining Techniques in Neuro-Informatics

描述(申请人提供)：传统搜索引擎(如PubMed) 可以识别Medline记录中包含的许多方面的信息，并提供 对某一特定主题的当前知识状态的指示。然而，这样的 对于在边境工作的调查人员来说，询问是不够的 科学发现，谁需要评估新的可能的意义 尚未进行实验的发现或假设的关系 测试过。Arrowsmith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来解决问题 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 在一对互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，仅仅是论文的标题 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 综合考虑时的推论。测试Arrowsmith用于 由科学界使用，一组现场测试员将接受培训 评估Arrowsmith分析用于 多学科神经科学组织的背景，这两个组织都有重要的 实验室和信息学部分。通过共享链接论文的效用 从Medline记录的其他字段中提取的术语，例如，摘要词或网格 主题词，也将进行评估。将提供访问Arrowsmith的权限 通过一个网站进行升级和扩展，以适应更大的 也是公共的。最后，将评估Arrowsmith的分析是否可以 通过识别和提醒，帮助促进新的跨学科研究 独立处理问题的调查人员组成的互补小组 为了共同利益，最好的解决办法可能是共同努力。因为. Arrowsmith方法的通用性，它可以应用于广泛的 生物医学问题，实际上，在任何 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.