首页> 美国卫生研究院文献>other >Formalization Annotation and Analysis of Diverse Drug and Probe Screening Assay Datasets Using the BioAssay Ontology (BAO)
【2h】

Formalization Annotation and Analysis of Diverse Drug and Probe Screening Assay Datasets Using the BioAssay Ontology (BAO)

机译:形式化注释和多样化的药品的分析与探讨筛选使用生物测定本体分析数据集(BaO)

代理获取
本网站仅为用户提供外文OA文献查询和代理获取服务,本网站没有原文。下单后我们将采用程序或人工为您竭诚获取高质量的原文,但由于OA文献来源多样且变更频繁,仍可能出现获取不到、文献不完整或与标题不符等情况,如果获取不到我们将提供退款服务。请知悉。

摘要

Huge amounts of high-throughput screening (HTS) data for probe and drug development projects are being generated in the pharmaceutical industry and more recently in the public sector. The resulting experimental datasets are increasingly being disseminated via publically accessible repositories. However, existing repositories lack sufficient metadata to describe the experiments and are often difficult to navigate by non-experts. The lack of standardized descriptions and semantics of biological assays and screening results hinder targeted data retrieval, integration, aggregation, and analyses across different HTS datasets, for example to infer mechanisms of action of small molecule perturbagens. To address these limitations, we created the BioAssay Ontology (BAO). BAO has been developed with a focus on data integration and analysis enabling the classification of assays and screening results by concepts that relate to format, assay design, technology, target, and endpoint. Previously, we reported on the higher-level design of BAO and on the semantic querying capabilities offered by the ontology-indexed triple store of HTS data. Here, we report on our detailed design, annotation pipeline, substantially enlarged annotation knowledgebase, and analysis results. We used BAO to annotate assays from the largest public HTS data repository, PubChem, and demonstrate its utility to categorize and analyze diverse HTS results from numerous experiments. BAO is publically available from the NCBO BioPortal at . BAO provides controlled terminology and uniform scope to report probe and drug discovery screening assays and results. BAO leverages description logic to formalize the domain knowledge and facilitate the semantic integration with diverse other resources. As a consequence, BAO offers the potential to infer new knowledge from a corpus of assay results, for example molecular mechanisms of action of perturbagens.
机译:在制药行业,以及最近在公共部门,正在为探针和药物开发项目生成大量的高通量筛选(HTS)数据。由此产生的实验数据集正越来越多地通过可公开访问的存储库进行分发。但是,现有的存储库缺少足够的元数据来描述实验,并且通常难以由非专家进行导航。缺乏生物学测定和筛选结果的标准化描述和语义,阻碍了跨不同HTS数据集的目标数据检索,整合,聚集和分析,例如,无法推断出小分子微扰的作用机理。为了解决这些局限性,我们创建了BioAssay Ontology(BAO)。 BAO的开发重点是数据集成和分析,可通过与格式,分析设计,技术,目标和终点有关的概念对分析和筛选结果进行分类。先前,我们报道了BAO的更高级别设计以及HTS数据的本体索引三元存储提供的语义查询功能。在这里,我们将报告我们的详细设计,注释管道,大幅扩展的注释知识库以及分析结果。我们使用BAO注释了最大的公共HTS数据存储库PubChem中的化验,并展示了其用于分类和分析来自众多实验的各种HTS结果的实用性。 BAO可以从NCBO BioPortal的网站上公开获得。 BAO提供受控的术语和统一的范围,以报告探针和药物发现筛选测定和结果。 BAO利用描述逻辑来规范领域知识,并促进与各种其他资源的语义集成。因此,BAO提供了从检测结果的语料库中推断新知识的潜力,例如微扰剂的分子作用机理。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
代理获取

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号