Ontologies and Biomedical Language Processing

描述（由申请人提供）：我们假设生物医学本体和生物医学语言处理（BLP）的应用之间存在显著的协同作用，可以用于提高这两种活动的质量和范围。越来越多的工作表明，这种协同作用可能存在，但尚未对其潜力进行系统的探索。我们建议进行集中的努力，探索的潜力，和障碍，生物医学本体和生物医学语言处理的相互应用。为了给我们的工作提供直接的生物学相关性，我们建议关注自身免疫性疾病和肺部疾病的主题。我们将我们提出的探索分为三个具体目标：（1）创建新的工具和方法的应用和维护的生物医学本体，在生物医学语言处理社区的文本语料库的本体注释的过程和工具的评估的基础上。特别是，我们将专注于创建新的方法，通过大型本体有效搜索，组合方法注释，有效捕获注释的证据，并使用自动化建议进行手动确认。(2)评估BLP工具和技术在应用于生物医学本体的术语和定义时的实用性，以丰富和互连正交本体，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的方法，用于连接术语内和跨本体，用于评估对文献的本体的完整性，并实现自动执行的本体质量的措施。(3)比较手工过程生成的注释和自动化BLP方法生成的注释的完整性和正确性。根据所产生的数据，为人工和自动程序之间的最佳相互作用制定准则，以建立广泛、准确和有用的知识库。由于本体论是模式生物数据库的中心组织工具，因此其质量以及其使用的易用性和效率的改进将对模式生物数据库产生重大影响，通常会加速翻译过程，并产生潜在的巨大公共卫生影响。

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.