.png){kind=icon}
返回
A practical guide to interpreting and generating bottom-up proteomics data visualizations
.png){kind=icon}
OA
AI
DOI：10.1002/pmic.202100103.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Mass-spectrometry based bottom-up proteomics is the main method to analyze proteomes comprehensively and the rapid evolution of instrumentation and data analysis has made the technology widely available. Data visualization is an integral part of the analysis process and it is crucial for the communication of results. This is a major challenge due to the immense complexity of MS data. In this review, we provide an overview of commonly used visualizations, starting with raw data of traditional and novel MS technologies, then basic peptide and protein level analyses, and finally visualization of highly complex datasets and networks. We specifically provide guidance on how to critically interpret and discuss the multitude of different proteomics data visualizations. Furthermore, we highlight Python-based libraries and other open science tools that can be applied for independent and transparent generation of customized visualizations. To further encourage programmatic data visualization, we provide the Python code used to generate all data figures in this review on GitHub ().
Keyword:
bottom-up proteomics
data visualization
open science
science communication
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
3.9
论文数:
7.6K
被引数:
1.1W
机构
引用论文
分享收藏分享收藏STRING: a web-server to retrieve and display the repeatedly occurring neighbourhood of a gene字符串: 一个web服务器，用于检索和显示重复出现的基因邻域.png)
NUCLEIC ACIDS RESEARCH
OAAI
NUCLEIC ACIDS RESEARCHIF13.1
OAAI分享收藏DIA-NN: neural networks and interference correction enable deep proteome coverage in high throughputDia-nn: 神经网络和干扰校正可实现高通量的深度蛋白质组覆盖NATURE METHODSOAAI
NATURE METHODSIF32.1
OAAI分享收藏
查看更多内容