Visualization of Biomedical Data

Abstract

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 biomedical research areas, including three-dimensional genomics, single-cell RNA sequencing (RNA-seq), the protein structure universe, phosphoproteomics, augmented reality–assisted surgery, and metagenomics. While specific research areas need highly tailored visualizations, there are common challenges that can be addressed with general methods and strategies. Also common, however, are poor visualization practices. We outline ongoing initiatives aimed at improving visualization practices in biomedical research via better tools, peer-to-peer learning, and interdisciplinary collaboration with computer scientists, science communicators, and graphic designers. These changes are revolutionizing how we see and think about our data.

Preparing scientists for a visual future

“…In genomics, for instance, interactive interfaces allow users to browse genomes, compare genomic sequences, examine RNA sequences, and analyze gene expression data [2]. In genomics, for instance, interactive interfaces allow users to browse genomes, compare genomic sequences, examine RNA sequences, and analyze gene expression data [2].…”

“…Visualizations are aiding understanding of relationships between organisms and their evolution [2]. Structural biologists use visualizations to understand and describe protein structure and function.…”

“…Recent advances enable biologists to image tissues, cells, and cellular structures in vivo, in real time and in 3D to gain insights into morphology and function [2]. Microscopy has been one of the oldest and most predominant methods to visualize biological phenomena and diagnose diseases.…”

“…Although our visual system is capable of managing incredibly dense visualizations [2], there are many examples where visualizations have gone wrong, leading to an overwhelmed viewer. In research and teaching, however, there is little to no emphasis on developing visualization skills, and therefore, many scientists are not comfortable with their abilities in creating coherent visuals.…”

“…However, examples of substandard visualizations are abundant-which could potentially lead to misinterpretation [2]. Most students independently figure out how to create visuals by need, often copying and editing existing illustrations.…”