IEEE Computer Graphics and Applications (CG&A) bridges the theory and practice of computer graphics topics, including modeling, rendering, animation, (data) visualization, HCI/user interfaces, novel applications, hardware architectures, haptics, and virtual- and augmented-reality systems.

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CG&A is the oldest and still the only publication with such a breath of topics and its mix of opinion pieces and peer-reviewed research articles. We pride ourselves on both our high impact factor and fast turnaround time for submitted content.

Special Issue on Breakthroughs, Challenges, and Opportunities in Biological Data Visualization
Submission Date: 2025-02-21

The rapidly expanding data generated by advanced methods in biology is creating enormous  challenges at the interface between humans and biological data that can be represented and  analyzed visually. To meet these challenges, a blend of methodology from the visualization,  bioinformatics and biology domains is required. This methodology encompasses perception and  design knowledge, algorithm design, techniques for analyzing and visualizing big data,  statistics, and specific domain knowledge for different application problems. Powerful and  integrative visualization methods are necessary, as well as methods for visually communicating  the outcome of computational analytical methods and findings. 

This special issue aims to highlight new challenges in biological data visualization (BioVis), and  state-of-the-art solutions created by the vibrant BioVis community. We invite contributions on all  aspects of data visualization in biology, from molecular to cell, tissue, organism and population  biology. Topics of interest include, but are not limited to: 

    Genome and sequence data visualization, including genomic variation data, 3D and 4D genome visualization, and chromosome interaction maps
    Multivariate omics data visualization (transcriptomics, proteomics, metabolomics, etc.)
    Phylogenetic data visualization, as well as biological networks and pathways
    Neurobiology and developmental biology visualization, biological atlases and metadata 
    Macromolecular structures (e.g., protein or RNA structures) visualization
    Biological image data, such as microscopy data visualization 
    Visualization for the modeling and simulation of biological systems 
    Biovis systems and software frameworks, and integrating visualization and machine learning for biological analysis 
    Biological workflows or collaborative processes, processes for interdisciplinary collaboration between biology and visualization, and usability of visualization by biologists, including communicating uncertainty 
    New challenges, breakthroughs, and opportunities in biological data visualization