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，可用于提高这两项活动的质量和范围。越来越多的研究表明，这种协同效应可能存在，但尚未对其潜力进行系统的探索。我们建议开展重点工作，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，我们建议将重点放在自身免疫和肺部疾病的主题上。我们将我们提出的探索分为三个具体目标：(1)基于对生物医学语言处理社区中用于文本语料库本体论注释的过程和工具的评估，为生物医学本体的应用和维护创造新的工具和方法。特别是，我们将专注于创建通过大型本体进行有效搜索的新方法、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工具和技术在应用于生物医学本体术语和定义时的效用，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方法，用于连接本体内部和跨本体的术语，用于根据文献评估本体的完整性，以及用于实现本体质量的自动可执行度量。(3)比较手工过程生成的注释与自动化BLP方法生成的注释在完整性和正确性方面的差异。根据所得数据，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数据库的中心组织工具，其质量及其使用的便利性和效率的提高将对模式生物数据库产生重大影响，普遍加快转化过程，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.