Visualization of Biomedical Data

@article{ODonoghue2018VisualizationOB,
  title={Visualization of Biomedical Data},
  author={Se{\'a}n I. O’Donoghue and Benedetta Frida Baldi and Susan J. Clark and Aaron E. Darling and James M. Hogan and Sandeep Kaur and Lena Maier-Hein and Davis J. McCarthy and William J. Moore and Esther Stenau and Jason R. Swedlow and Jenny Vuong and James B. Procter},
  journal={Annual Review of Biomedical Data Science},
  year={2018}
}
The rapid increase in volume and complexity of biomedical data requires changes in research, communication, and clinical practices. This includes learning how to effectively integrate automated analysis with high–data density visualizations that clearly express complex phenomena. In this review, we summarize key principles and resources from data visualization research that help address this difficult challenge. We then survey how visualization is being used in a selection of emerging… 

Figures and Tables from this paper

Grand Challenges in Bioinformatics Data Visualization
TLDR
Current and future grand challenges in bioinformatics data visualization are outlined, and the first publication venue dedicated to this subdiscipline is announced.
Tasks, Techniques, and Tools for Genomic Data Visualization
TLDR
Taxonomies for data, visualization, and tasks involved in genomic data visualization are proposed and a comprehensive review of published genomic visualization tools is provided in the context of the proposed taxonomies.
Morphing projections: a new visual technique for fast and interactive large-scale analysis of biomedical datasets
TLDR
The hypothesis is that the confluence of diverse complementary information from different domains on a highly interactive interface allows the user to discover relevant relationships or generate new hypotheses to be investigated by other means.
R/LinkedCharts: A novel approach for simple but powerful interactive data analysis
TLDR
R/LinkedCharts is presented, a framework that renders this task radically simple: Producing linked charts is as quickly done as is producing conventional static plots in R, requiring a data scientist to write only very few lines of simple R code to obtain complex and general visualization.
Trends & Opportunities in Visualization for Physiology: A Multiscale Overview
TLDR
The findings of this report may be used by visualization researchers to understand the overarching trends, challenges, and opportunities in visualization for physiology and to provide a foundation for discussion and future research directions in this area.
Statistics for Bioinformatics
TLDR
This chapter attempted to understand how statisticians develop and employ various strategies to investigate and analyze large-scale biological data, like multiple testing, unsupervised learning and data visualization, clustering, and bootstrapping.
Learning analytics in medical education: a turning point?
TLDR
This paper explores the origin of the concept, some of its advantages and implications, and the ability to visualize student data in novel ways, among other possibilities in the field of education.
Use ggbreak to Effectively Utilize Plotting Space to Deal With Large Datasets and Outliers
TLDR
An R package ggbreak is presented that allows users to create broken axes using ggplot2 syntax and increases the available visual space for a better presentation of the data and detailed annotation, thus improves the ability to interpret the data.
...
...

References

SHOWING 1-10 OF 149 REFERENCES
Visualization of omics data for systems biology
TLDR
How visualization tools are being used to help interpret protein interaction, gene expression and metabolic profile data is discussed, and emerging new directions are highlighted.
Visualizing genome and systems biology: technologies, tools, implementation techniques and trends, past, present and future
TLDR
The past, present and future of genomic and systems biology visualization is discussed, and the latest libraries and programming languages that enable more effective, efficient and faster approaches for visualizing biological concepts are focused on.
Visualizing multidimensional cancer genomics data
Cancer genomics projects employ high-throughput technologies to identify the complete catalog of somatic alterations that characterize the genome, transcriptome and epigenome of cohorts of tumor
An assessment of visualization tools for patient monitoring and medical decision making
TLDR
In an analysis of the UVa Hospital's Surgical Trauma Burn Intensive Care Unit (STBICU), the impacts that technology and data have on workflow and the value added to various stakeholders are examined.
Microreact: visualizing and sharing data for genomic epidemiology and phylogeography
TLDR
Microreact can act as an end point for any tool or bioinformatic pipeline that ultimately generates a tree, and provides a simple, yet powerful, visualization method that will aid research and discovery and the open sharing of datasets.
Visualization of image data from cells to organisms
TLDR
An overview of existing methods and tools for query, analyze and crosslink image data characterizing genes and proteins on a large scale are given.
Visualizing genomes: techniques and challenges
TLDR
This work provides a guide to genomic data visualization tools that facilitate analysis tasks by enabling researchers to explore, interpret and manipulate their data, and in some cases perform on-the-fly computations.
UCSF Chimera—A visualization system for exploratory research and analysis
TLDR
Two unusual extensions are presented: Multiscale, which adds the ability to visualize large‐scale molecular assemblies such as viral coats, and Collaboratory, which allows researchers to share a Chimera session interactively despite being at separate locales.
Cerebral: Visualizing Multiple Experimental Conditions on a Graph with Biological Context
TLDR
Cerebral, a system that uses a biologically guided graph layout and incorporates experimental data directly into the graph display and is concluded that Cerebral is a valuable tool for analyzing experimental data in the context of an interaction graph model.
Visualization of Biomolecular Structures: State of the Art
TLDR
The report presents a taxonomy that demonstrates which areas of molecular visualization have already been extensively investigated and where the field is currently heading, and discusses visualizations for molecular structures, strategies for efficient display regarding image quality and frame rate.
...
...