Data Structures, Algorithms and Tools for Ontological Discovery

本体发现的数据结构、算法和工具

• 批准号: 9329349
• 负责人: Elissa J Chesler
• 金额: $ 36.32万
• 依托单位: JACKSON LABORATORY
• 依托单位国家: 美国
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-09-01 至 2020-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9329349
• 关键词: Address; Alcohol abuse; Alcohol dependence; Alcoholism; Alcohols; Algorithmic Software; Algorithms; Anxiety; Area; Automobile Driving; Behavior; Behavior Disorders; Behavioral; Bioinformatics; Biological; Biological Process; Categories; Chronic Disease; Combinatorics; Communities; Computers; Coupled; Data; Data Set; Databases; Development; Diagnostic; Disease; Drug Addiction; Environment; Genes; Genomics; Goals; Graph; Heterogeneity; Hyperactive behavior; Individual; Investigation; Knowledge Discovery; Leadership; Legal; Lifestyle-related condition; Maps; Methods; Molecular; Network-based; Neurosciences; Ontology; Organism; Pathology; Performance; Pharmaceutical Preparations; Phenotype; Process; Public Health; Quantitative Genetics; Research; Research Personnel; Resources; Scientist; Semantics; Structure; Substance abuse problem; Support System; System; Technology; Time; Validation; Work; addiction; base; biomedical ontology; combinatorial; computerized tools; cost effective; data modeling; data resource; design; disease classification; experimental analysis; experimental study; flexibility; functional genomics; gene interaction; gene product; genomic data; graph theory; improved; in vivo; innovation; interest; neurobehavioral; novel; psychosocial; public health relevance; social; therapy outcome; tool; validation studies

 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.

 描述（适用提供）：我们的总体目标是发现酒精中毒，成瘾，神经行为过程以及这些疾病之间的关系的共同基因组机制。为此，我们开发了一个知识发现环境GeneWeaver.org，它使用户能够在规格和实验类型中存储和集成功能基因组数据。我们将数据列入该系统围绕行为神经科学的数据，并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和主要公共资源中获得的。这些数据可以通过基于基因含量和研究描述的多种方法来查询。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，以找到与生物学过程集的高度相关的基因，并在酒精中毒，成瘾和相关疾病的各个方面之间找到​​关系。这些关系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，可行性和兴趣的发现进行验证研究。在续签时期，我们将以几种重要的方式扩展工作。首先，我们将扩大系统支持的生物分子实体的广度，无论是生物体还是分子类型，以更精确和深度捕获功能基因组学的范围。其次，我们将超越对功能基因组学研究导致的许多生物分子与这些实体之间关系的比较的比较，即我们将从集合比较过渡到网络比较。第三，我们将更明确地将系统应用于行为障碍的生物学比较，并评估诸如“焦虑”和“酒精中毒”或“活跃”和“成瘾”等术语的概念完整性，并确定这些神经行为疾病中重叠核心核心特征的生物学实体。