Ontologies and Biomedical Language Processing

描述(由申请人提供)：我们假设生物医学本体论和生物医学语言处理(BLP)的应用之间存在显著的协同效应，可用于改善这两项活动的质量和范围。越来越多的工作表明，这种协同效应可能存在，但对它们的潜力还没有进行系统的探索。我们建议开展一项有重点的努力，探索生物医学本体和生物医学语言处理相互应用的潜力和障碍。为了给我们的工作提供直接的生物学相关性，我们建议专注于自身免疫和肺部疾病的主题。我们将我们提出的探索归结为三个具体目标：(1)基于对生物医学语言处理社区用于文本语料库本体标注的过程和工具的评估，创建用于应用和维护生物医学本体的新工具和方法。特别是，我们将专注于通过大型本体创建有效搜索的新方法、注释的组合方法、有效捕获注释背后的证据以及使用自动建议进行手动确认。(2)评估BLP工具和技术应用于生物医学本体论的术语和定义时的效用，以丰富和互连正交本体论，并提供质量保证和质量控制机制。特别是，我们建议开发和评估用于连接本体内和本体之间的术语的方法，用于对照文献评估本体的完备性的方法，以及用于实现本体质量的自动可执行度量的方法。(3)比较人工标注和自动BLP标注的完备性和正确性。根据产生的数据，为人工和自动程序之间的最佳相互作用制定指导方针，以产生广泛、准确和有用的知识库。由于本体论是模式生物体数据库的中心组织工具，其质量以及使用的简易性和效率的改进将对模式生物体数据库产生重大影响，总体上加快翻译过程，并可能产生巨大的公共健康影响。

DESCRIPTION (provided by applicant): We hypothesize that there are significant synergies between the applications of biomedical ontologies and of biomedical language processing (BLP) which can be used to improve the quality and scope of both activities. A growing body of work suggests such synergies might exist, but there has yet to be a systematic exploration of their potential. We propose to carry out a focused effort to explore both the potential for, and obstacles to, the mutual application of biomedical ontologies and biomedical language processing. To provide immediate biological relevance to our work, we propose to focus on the topics of autoimmune and pulmonary disease. We group our proposed explorations into three specific aims: (1) Create novel tools and approaches for the application and maintenance of biomedical ontologies, based on an assessment of the processes and tools used for the ontological annotation of textual corpora in the biomedical language processing community. Particularly, we will focus on the creation of new methods for effective search through large ontologies, compositional approaches to annotation, effective capture of the evidence underlying annotations, and the use of automated suggestions for manual confirmation. (2) Evaluate the utility of BLP tools and techniques when applied to terms and definitions of biomedical ontologies, both to enrich and interconnect orthogonal ontologies, and to provide quality assurance and quality control mechanisms. Particularly, we propose to develop and evaluate methods for connecting terms within and across ontologies, for assessing completeness of an ontology against the literature, and for implementing automatically executable measures of ontology quality. (3) Compare the differences between annotations produced by manual procedures and those produced by automated BLP methods for completeness and correctness. Based on the resulting data, produce guidelines for the optimal interplay between manual and automatic procedures for producing broad, accurate and useful knowledge-bases. Because ontologies are the central organizing tool of the model organism databases, improvements in their quality and in the ease and efficiency of their use will have a major effect on the model organism databases, speed the translational process generally, and create a potentially large public health impact.