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

描述(由申请人提供)：由公共资助的筛查中心使用各种高通量和低通量筛查技术生成越来越大和多样化的数据集。这些数据中的大部分都是可以访问的。最大的小分子筛选结果公共存储库是PubChem，目前覆盖了37万种化合物的1500多种分析。在接下来的五年里，公开可获得的化验方法的数量预计将增长10倍以上。这一无价资源的用途目前是有限的，因为复杂和多样化的生物测定数据集中所包含的知识尚未形成形式，因此不能用于全面的计算分析或与其他数据来源相结合。这项提议就是为了挑战这一限制。在过去的十年里，生物学家开发了本体论，以促进对各种基因组计划中涌现的大量信息的分析和讨论。本体是对象和概念及其属性和关系的受控词汇表示。其目的是对特定领域的知识进行建模和共享，以便软件代理可以自动提取和关联信息。这项提议的目的是开发一个生物检测本体论、软件工具，并展示它们的实用性。生物分析本体论将连贯地描述各种生物分析(如PubChem中的那些)，重点放在复杂的基于细胞的分析上，特别是高含量的筛选数据。软件支持和开发包括构建本体术语和精选数据集的模块、将本体映射到筛选实验和其他本体的工具、以及在本体的上下文中标准化、重新格式化和聚合数据集的工具。我们将通过创建一个派生于PubChem的数据库并通过搜索界面将其提供给社区来演示我们方法的实用性。本体论和软件工具将促进各种背景下的生物检测筛选数据的分析，例如信号或代谢途径和间接的人类疾病。这些工具将使人们能够提取数据集，以对扰动剂和生物靶标(或途径)之间的特定相互作用进行建模，或者对依赖于分析技术的干扰进行建模。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，以便在他们自己和外部数据集的背景下利用本体。它将是模块化的和开源的。我们将开展各种合作，在社区中传播生物检测本体和软件，并促进它们的持续发展。 与公共卫生相关：该项目将开发一个生物检测本体论，以连贯地描述数百种不同的检测方法，用于研究药物等干扰剂如何改变细胞功能。与搜索现有分析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，以便进一步开发成为化学探针或治疗学的起点。

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.