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（性状，综合征等）。表型数据库，以促进旨在解开基因-疾病-关系的表型研究。虽然在分子水平（基因和蛋白质）的基因组研究一直在积极进行，但在功能基因组学研究，特别是表型研究方面进展甚微。然而，很快就会出现对医学和生物学更大整合的迫切需求，以及对相关创新信息学工具的迫切需求，以促进需要表型分析的研究。 数据显著阻碍表型研究进展的一个限制因素是缺乏跨数据库的相关表型的及时访问。本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），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。该项目的重点是研究和开发表型组织者系统（POS），该系统旨在自动化表型数据和知识的整合，组织和可视化过程。本项目的研究假设是：1）可以开发一个表型组织者系统来有效地处理表型 来自癌症和模式生物体系统数据库的数据和知识，以及2）POS，通过使用术语使用的上下文知识（语义、术语和概率），可以改善来自不同数据库的表型信息的合并和组织。测试这些假设的具体目标是：（一）模型和映射的术语组件的各种表型数据库使用扩展的语义网络;（二）创建一个知识库包含上下文属性的术语组件;和（三）开发网络启用的表型组织者系统的基础上的目标（一）和（二）。拟议中的研究可能提供一种独特的方法，通过改善获取来加速生物医学研究 表型数据和知识处理-语义表型（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，这些工具对于基因组，蛋白质组学和临床数据库的跨学科挖掘非常有价值。

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.