.png){kind=icon}
返回
Exploring and visualizing multidimensional data in translational research platforms
.png){kind=icon}
OA
AI
DOI：10.1093/bib/bbw080.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
The unprecedented advances in technology and scientific research over the past few years have provided the scientific community with new and more complex forms of data. Large data sets collected from single groups or cross-institution consortiums containing hundreds of omic and clinical variables corresponding to thousands of patients are becoming increasingly commonplace in the research setting. Before any core analyses are performed, visualization often plays a key role in the initial phases of research, especially for projects where no initial hypotheses are dominant. Proper visualization of data at a high level facilitates researcher's abilities to find trends, identify outliers and perform quality checks. In addition, research has uncovered the important role of visualization in data analysis and its implied benefits facilitating our understanding of disease and ultimately improving patient care. In this work, we present a review of the current landscape of existing tools designed to facilitate the visualization of multidimensional data in translational research platforms. Specifically, we reviewed the biomedical literature for translational platforms allowing the visualization and exploration of clinical and omics data, and identified 11 platforms: cBioPortal, interactive genomics patient stratification explorer, Igloo-Plot, The Georgetown Database of Cancer Plus, tranSMART, an unnamed data-cube-based model supporting heterogeneous data, Papilio, Caleydo Domino, Qlucore Omics, Oracle Health Sciences Translational Research Center and OmicsOffice (R) powered by TIBCO Spotfire. In a health sector continuously witnessing an increase in data from multifarious sources, visualization tools used to better grasp these data will grow in their importance, and we believe our work will be useful in guiding investigators in similar situations.
Keyword:
high-dimensional data
omics
data analytics
visualization
translational research
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:
7.7
论文数:
5.8K
被引数:
2.7W
机构
引用论文
分享收藏Translational research platforms integrating clinical and omics data: a review of publicly available solutions整合临床和组学数据的转化研究平台: 公开可用解决方案的综述OAAI
OAAI分享收藏分享收藏Network visualization and analysis of gene expression data using BioLayout Express3D.png)
NATURE PROTOCOLS
NATURE PROTOCOLSIF16
PREAI
分享收藏RD-Connect: An Integrated Platform Connecting Databases, Registries, Biobanks and Clinical Bioinformatics for Rare Disease ResearchRD-Connect: 一个连接数据库，注册表，生物库和临床生物信息学的集成平台，用于罕见疾病研究OAAI
OAAI分享收藏
查看更多内容