Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Proteomics01:33

Proteomics

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 proteomics...

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Evaluating the Performance of Photon- and Electron-Based Fragmentation Methods in Omnitrap-LCMS Analysis of <i>N</i>-Glycopeptides.

Analytical chemistry·2026
Same author

Spatial distribution of the proteome in the human body and in cancers.

Nature·2026
Same author

Integrated proteogenomic and metabolomic profiling of acute myeloid leukemias to identify molecular subtypes and associated therapy targets.

Nature cancer·2026
Same author

The inner nuclear membrane protein SUN1 regulates cullin-3 neddylation to maintain insulin signaling.

bioRxiv : the preprint server for biology·2026
Same author

Small-molecule binding-site discovery using silyl ether-enabled chemoproteomics.

Nature chemistry·2026
Same author

UBQLN2 links proteotoxicity with lipid metabolism in neurodegeneration.

Nature neuroscience·2026
Same journal

Platelet proteome links metabolism to reactivity in Essential Thrombocythemia.

Molecular & cellular proteomics : MCP·2026
Same journal

Genetic rescue of disrupted synaptic protein interaction network dynamics following SYNGAP1 reactivation.

Molecular & cellular proteomics : MCP·2026
Same journal

ASAP-ID: Proximity labelling with small tags.

Molecular & cellular proteomics : MCP·2026
Same journal

Proteome profiling reveals NQO2 activity contributing to proteasome inhibitor resistance in multiple myeloma cell lines.

Molecular & cellular proteomics : MCP·2026
Same journal

Depletion-Free Automated Enrichment of Serum Glycopeptides for High-Throughput Clinical Glycoproteomics.

Molecular & cellular proteomics : MCP·2026
Same journal

Extracellular Vesicles from Glioblastoma Cells Reflect 2D vs. 3D Culture Adaptation and Resistance to Temozolomide.

Molecular & cellular proteomics : MCP·2026
查看所有相关文章

相关实验视频

Updated: May 7, 2026

Identification of Protein Interaction Partners in Mammalian Cells Using SILAC-immunoprecipitation Quantitative Proteomics
12:53

Identification of Protein Interaction Partners in Mammalian Cells Using SILAC-immunoprecipitation Quantitative Proteomics

Published on: July 6, 2014

31.5K

基准测试SILAC 保护学 工作流程和数据分析平台

Ashley M Frankenfield1, Kevin L Yang2, Wan Nur Atiqah Binti Mazli3

  • 1Department of Chemistry, George Washington University, Washington, District of Columbia, USA.

Molecular & cellular proteomics : MCP
|May 2, 2025
PubMed
概括
此摘要是机器生成的。

这项研究对细胞培养中的氨基酸稳定同位素标记 (SILAC) 蛋白质组学数据分析软件进行了基准测试. 它提供了选择平台的指导方针,以确保精确的蛋白质定量和改进实验设计.

关键词:
DDA DDA DDA DDA DDA DDA DDA DDA DDA DDA DDA DDA DDA DDA DDA DDA DDA时间 时间 时间 时间这就是SILACLAC.蛋白质营业额的变化蛋白质组学数据分析数据分析

更多相关视频

Quantitative Mass Spectrometric Profiling of Cancer-cell Proteomes Derived From Liquid and Solid Tumors
08:08

Quantitative Mass Spectrometric Profiling of Cancer-cell Proteomes Derived From Liquid and Solid Tumors

Published on: February 27, 2015

16.1K
SILAC Based Proteomic Characterization of Exosomes from HIV-1 Infected Cells
10:24

SILAC Based Proteomic Characterization of Exosomes from HIV-1 Infected Cells

Published on: March 3, 2017

10.7K

相关实验视频

Last Updated: May 7, 2026

Identification of Protein Interaction Partners in Mammalian Cells Using SILAC-immunoprecipitation Quantitative Proteomics
12:53

Identification of Protein Interaction Partners in Mammalian Cells Using SILAC-immunoprecipitation Quantitative Proteomics

Published on: July 6, 2014

31.5K
Quantitative Mass Spectrometric Profiling of Cancer-cell Proteomes Derived From Liquid and Solid Tumors
08:08

Quantitative Mass Spectrometric Profiling of Cancer-cell Proteomes Derived From Liquid and Solid Tumors

Published on: February 27, 2015

16.1K
SILAC Based Proteomic Characterization of Exosomes from HIV-1 Infected Cells
10:24

SILAC Based Proteomic Characterization of Exosomes from HIV-1 Infected Cells

Published on: March 3, 2017

10.7K

科学领域:

  • 蛋白质组学是指蛋白质组学.
  • 生物化学 生物化学
  • 计算生物学 计算生物学

背景情况:

  • 细胞培养中的氨基酸稳定同位素标记 (SILAC) 是蛋白质组学中一个关键的代谢标记技术.
  • 准确识别和量化同位素蛋白质变体对于基于SILAC的研究至关重要.
  • 缺乏SILAC数据分析平台的全面评估,阻碍了最佳的研究设计和执行.

研究的目的:

  • 系统地评估和比较各种SILAC数据分析工作流程和软件.
  • 为执行SILAC蛋白质组学的研究人员提供实用指南.
  • 为了解决不同SILAC分析平台的性能理解的关键差距.

主要方法:

  • 开发了一个基准测试管道,以评估五个软件包 (MaxQuant,Proteome Discoverer,FragPipe,DIA-NN,Spectronaut) 的十个SILAC数据分析工作流.
  • 评估包括使用数据依赖获取 (DDA) 和数据独立获取 (DIA) 方法进行静态和动态SILAC标签.
  • 通过使用来自HeLa和神经元培养的内部和仓库数据集的12个指标来评估性能.

主要成果:

  • 每个软件包在评估的绩效指标中都表现出明显的优缺点.
  • 大多数平台的动态范围限制约为100倍,以准确量化轻重比率.
  • 基于这些发现,不建议使用蛋白质发现器进行SILAC DDA分析.

结论:

  • 本研究介绍了SILAC数据分析平台的首次系统评估.
  • 建议使用多个软件包进行交叉验证,以提高SILAC量化可靠性.
  • 这些发现为SILAC蛋白质组学研究设计和数据分析决策提供了实际指导.