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Mass spectrometry is a powerful characterization technique that can identify and separate a wide variety of compounds ranging from chemical to biological entities, based on their mass-to-charge ratio (m/z). The instruments that allow this detection, known as mass spectrometers, have three components: an ion source, a mass analyzer, and a detector. These spectrometers differ based on the nature of their ion source and analyzers.Matrix-assisted laser desorption ionization (MALDI) is a commonly...
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The issues and trends in healthcare delivery are constantly changing. The COVID-19 pandemic is one recent issue that wreaked havoc on healthcare systems, causing a shortage of healthcare workers, high demand for medicines and supplies, and increased medical expenditure due to a lack of insurance. Other issues include rising healthcare costs and care fragmentation.
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Quality documentation and reporting share essential characteristics that ensure they are practical and valuable resources for those who use them. These characteristics are:
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ClarID:生物医学元数据集成的人类可读和紧标识符规范.

Manuel Rueda1,2, Ivo G Gut1,2

  • 1Centro Nacional de Análisis Genómico, C/Baldiri Reixac 4, 08028 Barcelona, Spain.

medRxiv : the preprint server for health sciences
|September 15, 2025
PubMed
概括

ClarID提供了一个统一的框架,用于生成生物医学对象和生物标本的人类和机器可读的标识符. 这个系统嵌入了关键的元数据,增强了研究中的数据集成和分析.

科学领域:

  • 生物医学信息学 生物医学信息学
  • 数据管理数据管理
  • 基因组学就是基因组学.

背景情况:

  • 生物医学研究经常使用对象和生物标本的简单ID (例如,UUID),缺乏嵌入式语义信息.
  • 对上下文元数据 (组织类型,诊断) 的单独存储使数据整合,队列选择和分析复杂化.
  • 现有的结构化条形码系统往往局限于特定的联盟或领域,缺乏统一的,可扩展的框架.

研究的目的:

  • 开发一个域异性规范 (ClarID),用于创建对受试者和生物标本的统一,人类和机器可读的标识符.
  • 将关键的上下文元数据直接嵌入到这些标识符中,提高数据可追溯性和可访问性.
  • 为生成,解码和验证这些结构化标识符提供一个开源工具 (ClarID-Tools).

主要方法:

  • 开发了ClarID,这是一个支持人类可读和紧的"stub"标识符格式的规范.
  • 实现了ClarID-Tools,这是一个开源命令行工具,使用YAML代码库处理表格元数据 (CSV/TSV).
  • 该工具生成,解码和验证标识符,包括QR码功能,支持批量和单个样本处理.

主要成果:

  • 将ClarID应用于基因组数据共享 (GDC) 数据集,为超过113,000份临床记录和4,255份生物标本记录生成可解释的标识符.
关键词:
生物样本的标识符.整合健康数据的整合.进行元数据协调协调.基于本体学的注释.结构化的条形码编码主体标识符 主体标识符

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  • 证明了ClarID在从现有数据集中创建结构化,可解释的标识符的实用性.
  • 所有材料,包括脚本和数据,都是公开的,可以通过GitHub和Google Colab复制.

    • 结论:

    • 通过将上下文嵌入到结构化标识符中,ClarID弥合了不透明的登录号和丰富的元数据方案之间的差距.
    • 克拉里德框架提高了数据可追溯性,简化了下游分析,并通过可配置的代码库提供了适应性.
    • 开源的ClarID-Tools软件免费提供,包括全面的文档和可重复的管道.