Semantic Approaches to Phenotypic Databases Analyses

该项目的长期目标是建立创新的信息学工具，能够自动查询和组织表型数据(特征、症状等)。跨表型数据库，以促进旨在解锁基因-疾病-关系的表型研究。虽然在分子水平(基因和蛋白质)的基因组研究已经得到了广泛的追求，但功能基因组学研究，尤其是表型研究进展甚微。然而，很快就会有对医学和生物学更好地整合的迫切需求，以及对相关创新信息学工具的迫切需求，以促进需要表型的研究 数据。一个严重阻碍表型研究进展的限制因素是缺乏及时获取数据库中相关表型的机会。这项申请建议采用多学科方法(信息学、基因组学和生物医学研究)来探索语义、概率和术语技术在表型数据和知识处理中的价值。该项目的重点是表型组织者系统(POS)的研究和开发，该系统旨在使表型数据和知识的整合、组织和可视化过程自动化。该项目将探索的假设是1)可以开发一个表型组织系统来有效地处理表型 来自癌症和模式生物系统数据库的数据和知识，以及2)POS，通过使用术语用法(语义、术语和概率)的上下文知识，可以改进来自不同数据库的表型信息的结合和组织。检验这些假设的具体目标是：(1)使用扩展的语义网络对各种表型数据库的术语组件进行建模和映射；(2)创建包含术语组件的上下文属性的知识库；(3)基于AIMS(1)和(2)开发网络使能的表型组织系统。拟议的研究可能提供一种独特的方法，通过改善获取机会来加速生物医学研究 到表型数据和知识处理--语义表现组(表型-基因组关系)。此外，这些研究的结果可能会产生创新的生物医学信息学工具，对基因组、蛋白质组和临床数据库的跨学科挖掘具有极高的价值。

The long-term goal of this project is to build innovative informatics tools, capable of automatically querying and organizing phenotypic data (traits, syndromes, etc.) across Phenotype databases, to facilitate phenotypic research that aims to unlock the gene-disease-relationships. While genomic research at the molecular level (genes and proteins) has been intensively pursued, little progress has been made in functional genomics research, especially phenotypic research. However, there will soon be a pressing demand for greater integration of medicine and biology, and for related innovative informatics tools to facilitate research requiring phenotypic data. One limiting factor that significantly hinders the progress of phenotypic research is the lack of timely access to relevant phenotypes across databases. This application proposes to adopt a multidisciplinary approach (informatics, genomics and biomedical research) to explore the value of semantic, probabilistic and terminological technologies in phenotypic data and knowledge processing. The project focuses on the research and development of the Phenotype Organizer System (POS), a system designed to automate the processes of integration, organization and visualization of phenotypic data and knowledge. The hypotheses to be explored in this project are 1) a Phenotype Organizer System can be developed to effectively handle phenotypic data and knowledge from cancer and Model Organism System Databases, and 2) POS, by using the contextual knowledge of term usage (semantic, terminological and probabilistic) can improve the incorporation and organization of phenotypic information from distinct databases. Specific aims to test these hypotheses are: (i) to model and map the terminological components of various phenotypic databases using extended semantic networks; (ii) to create a knowledge base containing the contextual properties of the terminological components; and (iii) to develop the Web-enabled Phenotype Organizer System based on aims (i) and (ii). The proposed research may provide a unique approach to accelerate biomedical research by improving access to phenotypic data and knowledge processing - the Semantic Phenome (phenotypic-genomic relations). Further, results from these studies may yield innovative biomedical informatics tools that could be highly valuable for interdisciplinary mining of genomic, proteomic and clinical databases.