Bioassay Ontology and Software Tools to Integrate and Analyze Diverse Data Sets

用于整合和分析不同数据集的生物测定本体和软件工具

基本信息

批准号：
8527908
负责人：
Vance P Lemmon
金额：
$ 19.58万
依托单位：
UNIVERSITY OF MIAMI SCHOOL OF MEDICINE
依托单位国家：
美国
项目类别：
财政年份：
2012
资助国家：
美国
起止时间：
2012-09-07 至 2013-07-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8527908
关键词：
Amaze Apoptosis Binding Biochemical Bioinformatics Biological Biological Assay Biological Products Biology Cell physiology Cells Chemicals Collaborations Communities Complex Computer Analysis Computer software Controlled Vocabulary Data Data Aggregation Data Set Data Sources Databases Development Event Funding Gene Proteins Genes Genome Genomics Goals Housing Individual Knowledge Link Lipids Maps Measures Metabolic Pathway Mining Modeling Ontology Outcome Pathway interactions Pharmaceutical Preparations Phenotype Process Property Proteins Proteomics PubChem Resources Scientist Screening Result Screening procedure Signal Pathway Software Tools Standardization Structural Genes System Technology Therapeutic Time Work base biological systems high throughput screening human disease interest novel open source public health relevance repository research study response small molecule small molecule libraries software development tool web site wiki

项目摘要

DESCRIPTION (provided by applicant): Increasingly large and diverse data sets are being generated by publically funded screening centers using various high- and low-throughput screening technologies. Much of this data is accessible. The largest public repository of small molecule screening results is PubChem, currently covering over 1,500 assays for 370,000 compounds. The number of publically available assays is expected to grow more than 10 fold during the next five years. The utility of this invaluable resource is currently limited, because the knowledge contained in complex and diverse bioassay data sets is not formalized and therefore cannot be accessed for comprehensive computational analysis or integration with other data sources. This proposal is to attack this limitation. For the past ten years ontologies have been developed by biologists to facilitate the analysis and discussion of the massive amounts of information emerging from the various genome projects. An ontology is a controlled vocabulary representation of the objects and concepts and their properties and relationships. The purpose is to model and share domain-specific knowledge so that software agents can automatically extract and associate information. The aim of this proposal is to develop a bioassay ontology, software tools, and to demonstrate their utility. The bioassay ontology will coherently describe diverse biological assays (such as those in PubChem) with a focus on complex cell-based assays and in particular high-content screening data. Software support and development includes modules to build ontology terms and to curate data sets, tools to map the ontology onto screening experiments and other ontologies, and tools to standardize, reformat, and aggregate data sets in the context of the ontology. We will demonstrate the utility of our approach by creating a PubChem-derived database and making it available to the community via a search interface. The ontology and software tools will facilitate the analysis of bioassay screening data in various contexts, for example signaling or metabolic pathways and indirectly human disease. The tools will enable one to extract data sets for modeling specific interactions between perturbing agents and biological targets (or pathways), or to model assay technology-dependent interferences. End user software needs to provide ease of use for biologists and chemical biologists to utilize the ontology in the context of their own and external data sets. It will be modular and open source. We will develop various collaborations to disseminate the bioassay ontology and software in the community and to facilitate their ongoing development. PUBLIC HEALTH RELEVANCE: This project will develop a bioassay ontology to coherently describe the hundreds of different assays used to study how perturbing agents, such as drugs, alter cell function. Along with new software to search existing assay databases, this will enable scientists to more effectively identify and prioritize chemicals for further development into chemical probes or starting points for therapeutics.

描述（由申请人提供）：使用各种高通量和低通量筛选技术，公开资助的筛选中心正在生成越来越大且多样化的数据集。这些数据大部分都是可以访问的。小分子筛选结果最大的公共存储库是Pubchem，目前涵盖了370,000种化合物的1,500多种测定法。预计在未来五年内，公共可用测定的数量预计将增长10倍以上。目前，此宝贵资源的实用性是有限的，因为复杂和多样化的生物测定数据集中包含的知识未正式化，因此无法访问以进行全面的计算分析或与其他数据源集成。该建议是攻击这一限制。在过去的十年中，生物学家已经开发了本体论，以促进分析和讨论各种基因组项目中出现的大量信息。本体论是对象和概念及其属性和关系的受控词汇表示。目的是建模和共享特定于领域的知识，以便软件代理可以自动提取和关联信息。该建议的目的是开发生物测定本体论，软件工具，并证明其实用性。生物测定本体论将一致描述多种生物学测定（例如Pubchem的生物测定法），重点是基于复杂的细胞测定，尤其是高内含物筛选数据。软件支持和开发包括用于构建本体术语并策划数据集的模块，将本体论映射到筛选实验和其他本体学上的工具，以及在本体论文中标准化，重新格式化和汇总数据集的工具。我们将通过创建PubChem衍生的数据库并通过搜索界面来证明我们的方法的实用性。本体和软件工具将促进在各种情况下（例如信号传导或代谢途径以及间接人类疾病）中生物测定筛查数据的分析。这些工具将使人们能够提取数据集，以建模扰动剂和生物靶标（或途径）之间的特定相互作用，或者对技术依赖性研究的干扰进行建模。最终用户软件需要为生物学家和化学生物学家提供易用性，以便在自己和外部数据集的背景下利用本体。它将是模块化的开源。我们将开发各种合作，以传播社区中的生物测定本体论和软件，并促进其持续发展。公共卫生相关性：该项目将开发生物测定本体论，以一致描述用于研究扰动剂（例如药物）如何改变细胞功能的数百种不同测定。与搜索现有测定数据库的新软件一起，这将使科学家能够更有效地识别和优先考虑化学物质，以进一步开发化学探针或治疗剂的起点。