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首页> 外文期刊>Journal of biomolecular screening: The official journal of the Society for Biomolecular Screening >Metadata Standard and Data Exchange Specifications to Describe, Model, and Integrate Complex and Diverse High- Throughput Screening Data from the Library of Integrated Network-based Cellular Signatures (LINCS)
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Metadata Standard and Data Exchange Specifications to Describe, Model, and Integrate Complex and Diverse High- Throughput Screening Data from the Library of Integrated Network-based Cellular Signatures (LINCS)

机译：元数据标准和数据交换规范，用于描述，建模和集成来自基于网络的集成蜂窝签名库（LINCS）的复杂和多样的高通量筛选数据

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摘要

The National Institutes of Health Library of Integrated Network-based Cellular Signatures (LINCS) program is generating extensive multidimensional data sets, including biochemical, genome-wide transcriptional, and phenotypic cellular response signatures to a variety of small-molecule and genetic perturbations with the goal of creating a sustainable, widely applicable, and readily accessible systems biology knowledge resource. Integration and analysis of diverse LINCS data sets depend on the availability of sufficient metadata to describe the assays and screening results and on their syntactic, structural, and semantic consistency. Here we report metadata specifications for the most important molecular and cellular components and recommend them for adoption beyond the LINCS project. We focus on the minimum required information to model LINCS assays and results based on a number of use cases, and we recommend controlled terminologies and ontologies to annotate assays with syntactic consistency and semantic integrity. We also report specifications for a simple annotation format (SAF) to describe assays and screening results based on our metadata specifications with explicit controlled vocabularies. SAF specifically serves to programmatically access and exchange LINCS data as a prerequisite for a distributed information management infrastructure. We applied the metadata specifications to annotate large numbers of LINCS cell lines, proteins, and small molecules. The resources generated and presented here are freely available.
机译：美国国立卫生研究院综合网络基于细胞的细胞标记（LINCS）程序正在生成广泛的多维数据集，包括针对各种小分子和遗传扰动的生化，全基因组转录和表型细胞反应特征创建可持续的，广泛适用的和易于访问的系统生物学知识资源。各种LINCS数据集的集成和分析取决于是否有足够的元数据来描述测定和筛选结果，以及它们的句法，结构和语义一致性。在这里，我们报告了最重要的分子和细胞成分的元数据规范，并建议将它们用于LINCS项目之外。我们专注于基于许多用例为LINCS分析和结果建模所需的最少信息，并且我们建议使用受控的术语和本体以句法一致性和语义完整性来注释分析。我们还会报告一种简单注释格式（SAF）的规范，以基于具有明确控制词汇的元数据规范来描述化验和筛选结果。 SAF专门用于以编程方式访问和交换LINCS数据，这是分布式信息管理基础结构的前提。我们使用元数据规范来注释大量LINCS细胞系，蛋白质和小分子。这里生成和提供的资源是免费的。

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