Data Structures, Algorithms and Tools for Ontological Discovery

 描述(由申请人提供)：我们的首要目标是发现酒精中毒、成瘾、神经行为过程的共同基因组机制以及这些障碍之间的关系。为此，我们开发了一个知识发现环境GeneWever.org，使用户能够存储和集成跨物种和实验类型的功能基因组数据。我们围绕行为神经科学将数据整理到这个系统中，特别强调酒精中毒和成瘾研究。许多其他数据集是从用户提交的内容和主要公共资源中获得的。这些数据可以根据基因含量和研究描述通过各种方式进行查询。用户定义的查询结果和用户输入数据通过一套新颖的图形算法和工具进行协调和集成，以找到与一组生物过程高度关联的基因，并找到酗酒、成瘾和相关障碍各方面之间的关系。这些关系主要是通过大规模实验从经验数据中发现的。我们将该系统应用于酒精中毒和成瘾研究中的问题，并对具有足够新颖性、可行性和趣味性的发现进行验证性研究。在我们的更新期间，我们将在几个重要方面扩展我们的工作。首先，我们将扩大系统支持的生物分子实体的广度，包括生物和分子类型，以更高的精度和深度捕捉功能基因组学的范围。其次，我们将超越功能基因组研究产生的多组生物分子的比较，而是这些实体之间的关系的比较，即我们将从集合比较过渡到网络比较。第三，我们将更明确地将该系统应用于行为障碍的生物学比较，以及对“焦虑”和“酗酒”或“多动”和“成瘾”等术语的概念完整性进行评估，并确定这些神经行为状况之间重叠的核心特征所在的生物实体。

 DESCRIPTION (provided by applicant): Our overarching goal is to discover the shared genomic mechanisms underlying alcoholism, addiction, neurobehavioral processes and the relations among these disorders. To do so we have developed a knowledge discovery environment, GeneWeaver.org, which enables users to store and integrate functional genomics data across species and experiment type. We curate data into this system around the behavioral neurosciences with a specific emphasis on alcoholism and addiction studies. Many other data sets are obtained from user submissions and major public resources. These data can be queried through a variety of means based on gene content and study description. User defined query results and user input data are harmonized and integrated through a suite of novel graph algorithms and tools to find genes highly associated to sets of biological processes and to find relations among aspects of alcoholism, addiction and related disorders. These relations are discovered primarily from empirical data via large-scale experimentation. We apply the system to questions in alcoholism and addiction research and perform validation studies on those findings which have sufficient novelty, feasibility and interest. In our renewal period, we will extend our work in several important ways. First, we will expand the breadth of biomolecular entities that the system supports, both by organism and molecular type, to capture the scope of functional genomics with greater precision and depth. Second, we will go beyond the comparison of the many sets of biomolecules that result from functional genomics studies to the comparison of relations among these entities, i.e., we will transition from set comparison to network comparison. Third, we will more explicitly apply the system to the biological comparison of behavioral disorders and the assessment of the conceptual integrity of terms such as "anxiety" and "alcoholism" or "hyperactivity" and "addiction" and to identify those biological entities that underlie core features of the overlap among these neurobehavioral conditions.