Effective data visualization strategies in untargeted metabolomics

可视化 代谢组学 领域(数学) 数据科学 透视图(图形) 计算机科学 口译(哲学) 数据可视化 计算生物学 数据挖掘 生物 生物信息学 人工智能 数学 纯数学 程序设计语言
作者
Kevin Mildau,Henry Ehlers,Mara Meisenburg,Elena Del Pup,Robert A. Koetsier,Laura Rosina Torres Ortega,Niek De Jonge,Kumar Saurabh Singh,Dora Ferreira,Kgalaletso Othibeng,Fidele Tugizimana,Florian Huber,Justin J. J. van der Hooft
出处
期刊:Natural Product Reports [Royal Society of Chemistry]
标识
DOI:10.1039/d4np00039k
摘要

Covering: 2014 to 2023 for metabolomics, 2002 to 2023 for information visualizationLC-MS/MS-based untargeted metabolomics is a rapidly developing research field spawning increasing numbers of computational metabolomics tools assisting researchers with their complex data processing, analysis, and interpretation tasks. In this article, we review the entire untargeted metabolomics workflow from the perspective of information visualization, visual analytics and visual data integration. Data visualization is a crucial step at every stage of the metabolomics workflow, where it provides core components of data inspection, evaluation, and sharing capabilities. However, due to the large number of available data analysis tools and corresponding visualization components, it is hard for both users and developers to get an overview of what is already available and which tools are suitable for their analysis. In addition, there is little cross-pollination between the fields of data visualization and metabolomics, leaving visual tools to be designed in a secondary and mostly ad hoc fashion. With this review, we aim to bridge the gap between the fields of untargeted metabolomics and data visualization. First, we introduce data visualization to the untargeted metabolomics field as a topic worthy of its own dedicated research, and provide a primer on cutting-edge visualization research into data visualization for both researchers as well as developers active in metabolomics. We extend this primer with a discussion of best practices for data visualization as they have emerged from data visualization studies. Second, we provide a practical roadmap to the visual tool landscape and its use within the untargeted metabolomics field. Here, for several computational analysis stages within the untargeted metabolomics workflow, we provide an overview of commonly used visual strategies with practical examples. In this context, we will also outline promising areas for further research and development. We end the review with a set of recommendations for developers and users on how to make the best use of visualizations for more effective and transparent communication of results.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
ylky发布了新的文献求助10
4秒前
科研通AI2S应助浮浮世世采纳,获得10
4秒前
传奇3应助华中科技大学采纳,获得10
4秒前
情怀应助WN采纳,获得10
5秒前
5秒前
8秒前
朴实山兰完成签到,获得积分10
10秒前
12秒前
SciGPT应助ylky采纳,获得10
12秒前
小爪冰凉发布了新的文献求助10
12秒前
13秒前
量子星尘发布了新的文献求助10
13秒前
JamesPei应助科研小牛采纳,获得150
14秒前
Ava应助科研小牛采纳,获得10
14秒前
14秒前
忧郁盼夏发布了新的文献求助10
17秒前
marina关注了科研通微信公众号
17秒前
沐紫心完成签到 ,获得积分10
18秒前
科研通AI5应助suger采纳,获得10
18秒前
20秒前
八九发布了新的文献求助10
20秒前
23秒前
23秒前
一个好听的名字完成签到,获得积分10
24秒前
wbh发布了新的文献求助20
24秒前
24秒前
25秒前
Eddoes完成签到,获得积分10
25秒前
WN发布了新的文献求助10
26秒前
诚心的凌旋完成签到,获得积分10
26秒前
leanne发布了新的文献求助10
28秒前
机智思真完成签到,获得积分10
28秒前
29秒前
科研小牛完成签到,获得积分10
29秒前
归尘发布了新的文献求助10
29秒前
万物安生发布了新的文献求助10
29秒前
阿钉发布了新的文献求助10
29秒前
30秒前
张钦奎发布了新的文献求助10
30秒前
30秒前
高分求助中
A new approach to the extrapolation of accelerated life test data 1000
ACSM’s Guidelines for Exercise Testing and Prescription, 12th edition 500
‘Unruly’ Children: Historical Fieldnotes and Learning Morality in a Taiwan Village (New Departures in Anthropology) 400
Indomethacinのヒトにおける経皮吸収 400
Phylogenetic study of the order Polydesmida (Myriapoda: Diplopoda) 370
基于可调谐半导体激光吸收光谱技术泄漏气体检测系统的研究 350
Robot-supported joining of reinforcement textiles with one-sided sewing heads 320
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 遗传学 基因 物理化学 催化作用 冶金 细胞生物学 免疫学
热门帖子
关注 科研通微信公众号,转发送积分 3989378
求助须知:如何正确求助?哪些是违规求助? 3531442
关于积分的说明 11254002
捐赠科研通 3270126
什么是DOI,文献DOI怎么找? 1804887
邀请新用户注册赠送积分活动 882087
科研通“疑难数据库(出版商)”最低求助积分说明 809173