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相关概念视频

Proteomics01:33

Proteomics

7.2K
A proteome is the entire set of proteins that a cell type produces. We can study proteomes using the knowledge of genomes because genes code for mRNAs, and the mRNAs encode proteins. Although mRNA analysis is a step in the right direction, not all mRNAs are translated into proteins.
Proteomics is the study of proteomes' function. It involves the large-scale systematic study of the proteome to denote the protein complement expressed by a genome. Scientist Mark Wilkins coined the term...
7.2K

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相关实验视频

Updated: May 31, 2025

A Streamlined Approach for Mass Spectrometry-Based Proteomics Using Selected Tissue Regions
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A Streamlined Approach for Mass Spectrometry-Based Proteomics Using Selected Tissue Regions

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一个用户友好的命令行工具,简化了定量蛋白质学中的差异表达式分析.

Witold E Wolski1,2, Jonas Grossmann1,2, Leonardo Schwarz1,2

  • 1Functional Genomics Center Zurich (FGCZ) - University of Zurich/ETH Zurich, Winterthurerstrasse 190, CH-8057 Zurich, Switzerland.

Journal of proteome research
|January 24, 2025
PubMed
概括
此摘要是机器生成的。

质谱是定量蛋白质组学的关键. 对于复杂的实验,prolfquapp工具简化了微分表达式分析 (DEA),为研究人员提供了可访问的,集成的数据处理和可视化.

关键词:
不同的表达分析分析差异表达分析.蛋白质组学 蛋白质组学统计软件 统计软件工作流程的工作流程.

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An Optimized Quantitative Pull-Down Analysis of RNA-Binding Proteins Using Short Biotinylated RNA
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An Optimized Quantitative Pull-Down Analysis of RNA-Binding Proteins Using Short Biotinylated RNA

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Simultaneous Affinity Enrichment of Two Post-Translational Modifications for Quantification and Site Localization
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Simultaneous Affinity Enrichment of Two Post-Translational Modifications for Quantification and Site Localization

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Last Updated: May 31, 2025

A Streamlined Approach for Mass Spectrometry-Based Proteomics Using Selected Tissue Regions
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An Optimized Quantitative Pull-Down Analysis of RNA-Binding Proteins Using Short Biotinylated RNA
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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:

  • 质谱是定量蛋白质组学的基础,使相对蛋白质定量和差异表达分析 (DEA) 成为可能.
  • 交互式DEA工具对复杂的实验变得不切实际,这些实验涉及许多样本,组和已识别的蛋白质.

研究的目的:

  • 开发一个命令行接口工具prolfquapp,简化DEA用于大规模定量蛋白质组学.
  • 让非程序员能够执行DEA并将其集成到工作流管理系统中.
  • 为了简化复杂的蛋白质组学实验的数据处理和结果可视化.

主要方法:

  • Prolfquapp为DEA提供了一个命令行界面.
  • 它生成动态的HTML报告,用于探索微分表达式结果.
  • 它利用了prolfqua R包中的高级统计模型.

主要成果:

  • Prolfquapp简化了DEA,使得非程序员也可以使用它.
  • 动态HTML报告有助于探索复杂的实验结果,包括重复测量和多个解释变量.
  • 支持多个输出格式 (XLSX,SummarizedExperiment,等级文件) 进行进一步分析.

结论:

  • 普罗尔夫奎普为大规模定量蛋白质组学提供了一个用户友好的,集成的解决方案.
  • 它将高效的数据处理与洞察力,准备出版的输出相结合.
  • 使用电子表格软件,Shiny应用程序或基因组丰富分析工具进行进一步的交互式分析.