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Proteomics

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...

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相关实验视频

Updated: May 24, 2025

A Strategy for Sensitive, Large Scale Quantitative Metabolomics

A Strategy for Sensitive, Large Scale Quantitative Metabolomics

Published on: May 27, 2014

逆代谢学指南 - - 大数据发现战略的框架.

Vincent Charron-Lamoureux^1,2, Helena Mannochio-Russo^1,2, Santosh Lamichhane³

¹Collaborative Mass Spectrometry Innovation Center, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, La Jolla, CA, USA.

Nature protocols

|February 28, 2025

概括

反向代谢学使用双重质谱 (MS/MS) 光谱来挖掘公共数据以获得与表型相关的信息. 这种方法有助于从现有的光谱数据中发现代谢物的功能和生物相关性.

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An Integrated Workflow of Identification and Quantification on FDR Control-Based Untargeted Metabolome

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Author Spotlight: Emerging Technologies and Advanced Tools for Decoding Metabolomics Data Analysis

Author Spotlight: Emerging Technologies and Advanced Tools for Decoding Metabolomics Data Analysis

Published on: November 10, 2023

相关实验视频

Last Updated: May 24, 2025

A Strategy for Sensitive, Large Scale Quantitative Metabolomics

A Strategy for Sensitive, Large Scale Quantitative Metabolomics

Published on: May 27, 2014

An Integrated Workflow of Identification and Quantification on FDR Control-Based Untargeted Metabolome

An Integrated Workflow of Identification and Quantification on FDR Control-Based Untargeted Metabolome

Published on: September 20, 2022

Author Spotlight: Emerging Technologies and Advanced Tools for Decoding Metabolomics Data Analysis

Author Spotlight: Emerging Technologies and Advanced Tools for Decoding Metabolomics Data Analysis

Published on: November 10, 2023

科学领域:

代谢学代谢学代谢学
大数据科学大数据科学
生物信息学是一种生物信息学.

背景情况:

未定位的代谢学产生双重质谱 (MS/MS) 数据用于代谢物识别和结构阐明.
越来越多的人对利用公共MS/MS数据库进行代谢物发现感兴趣.
传统的代谢学专注于预定义的研究问题,而反向代谢学则探索现有的数据,寻找新的关联.

研究的目的:

介绍和指导用户通过反向代谢学工作流程.
展示MS/MS光谱如何在公共数据库中作为搜索查询.
为了发现与代谢物相关的表型相关信息.

主要方法:

获取MS/MS光谱 (通用光谱标识符).
使用质谱搜索工具进行数据库搜索.
使用Reanalysis数据用户界面框架将光谱与元数据联系起来.
通过数据分析和潜在的分子网络验证发现.

主要成果:

描述的四部分过程使公共MS/MS存储库的有效数据挖掘成为可能.
使用MS/MS光谱的氨酸-胆酸,氨酸-C4:0和氨酸-C4:0.0的证明应用.
使用全球自然产品社会分子网络框架探索微生物生产者和健康状况和器官分配的协会.

结论:

反向代谢学提供了一个强大的策略,可以从大规模的MS/MS数据中提取生物学见解.
这种方法有助于发现代谢物的功能,分布和生物的关联.
概述的工作流提供了一个框架,用于重新分析现有的代谢学数据,以进行新的发现.