OAMiner: Integrative Knowledge Anchored Hypothesis Discovery

描述（由申请人提供）：本提案的目的是为了解决生物学和医学中对集成知识发现日益增长的需求，是为了发现、验证和确认关于基于图像、表型、通过利用多个概念性知识来源，在异构数据集中研究生物分子特征——最终支持“高通量”知识驱动的转化科学。为了提供一个可管理的项目范围，骨关节炎倡议（OAI）数据集将被用作开发和评估项目研究产品的主要、激励用例。该项目必然涉及由主题专家（sme）对系统培训和验证的初始假设进行分析。然而，我们提出的方法的最终目标是尽量减少人为干预的需要，以识别或验证知识锚定的假设。为了产生这样的假设，使用了四个相互关联的知识来源：1)通过传统文本挖掘和NLP分析在Medline数据库和相关全文库中发现的文章访问全文发表的生物医学文献；2)包含在国家医学图书馆统一医学语言系统（UMLS）中的公共可用本体；3)一个或多个包含表型和功能（如生活质量、心理、力量和表现测量）数据的数据库；计算机图像分析得到的特征（如股四头肌的横截面积）。

DESCRIPTION (provided by applicant):The objective of this proposal, which is designed to address the ever increasing need for integrated knowledge discovery in biology and medicine, is to enable the discovery, verification, and validation of hypotheses concerning interrelationships between image-based, phenotypic, and bio-molecular features in heterogeneous data sets by leveraging multiple conceptual knowledge sources - ultimately supporting "high throughput" knowledge-driven translational science. To provide for a manageable project scope, Osteoarthritis Initiative (OAI) data sets will be used as a primary, motivating use case for the development and evaluation of the projected research products. This project necessarily involves analysis of initial hypotheses by subject matter experts (SMEs) for system training and verification. However, the ultimate goal of our proposed approach is to minimize the need for human intervention to identify or validate knowledge-anchored hypotheses. In order to generate such hypotheses, four interrelated knowledge sources are used: 1) full-text published bio-medical literature accessed by both conventional text mining and NLP analyses of articles as found in the Medline database and associated full text repositories; 2) publically available ontologies included in the National Library of Medicine's Unified Medical Language System (UMLS); 3) one or more databases containing phenotypic and functional (e.g. quality of life, psychological, strength and performance measures) data; and 4) computerized-image analysis derived features (e.g. cross-sectional area of the quadriceps).