在谷歌云平台上的交互式学习模块中了解蛋白质组量化
Kyle A O'Connell1,2, Benjamin Kopchick1,2, Thad Carlson1,2
1Center for Information Technology, National Institutes of Health, 9000 Rockville Pike, Bethesda MD, 20892, United States.
Briefings in bioinformatics
|July 23, 2024
概括
本研究介绍了一种基于云的交互式学习模块,用于定量蛋白质组学,利用谷歌云进行可访问的质谱数据分析. 它涵盖了使用R编程为研究人员的蛋白质量化,规范化和差异丰度分析.
科学领域:
- 蛋白质组学是指蛋白质组学.
- 生物信息学是一种生物信息学.
- 计算生物学 计算生物学
背景情况:
- 定量蛋白质组学是一个快速发展的领域,由高分辨率质谱学驱动.
- 分析各种蛋白质组数据类型 (例如DDA,DIA,TMT) 需要在规范化,统计设计和编程方面具备专业知识.
- 现有的学习资源可能缺乏交互式,基于云的平台,用于实践数据分析培训.
研究的目的:
- 为定量蛋白质组学分析开发一个交互式学习模块.
- 提供使用云资源进行质谱数据分析的可访问培训.
- 为研究人员介绍蛋白质量化,规范化和差异丰度分析.
主要方法:
- 在NIGMS沙盒平台内开发基于云的学习模块.
- 使用谷歌云进行交互式数据访问和分析.
- 在一个带有R内核的Jupyter笔记本电脑中演示TMT10plex数据分析,包括用limma模型进行规范化和差异丰度分析.
主要成果:
- 该模块促进了对质谱术语,规范化方法和R编程基础知识的学习.
- 学习者获得实践经验,通过谷歌云平台进行蛋白质分子研究.
- 该模块有效地展示了从原始强度到差异丰度的端到端蛋白质组数据分析.
结论:
- 该NIGMS沙盒学习模块提供了对定量蛋白质组学的可访问和交互式方法.
- 基于云的平台提高了复杂数据分析培训的可访问性.
- 该资源为研究人员提供了现代蛋白质组数据解释的基本技能.
关键词:
谷歌云平台是谷歌的云平台.质谱测量质谱测量质谱测量质量测量质谱测量质量测量质量测量质量测量质量测量质量测量质量测量质量测量质量测量质量测量质量测量质量测量质量测量质量测量质量测量质量测量质量测量质量测量质量测量蛋白质组学 蛋白质组学更多相关视频
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