ArticleIEEE transactions on visualization and computer graphics2026
Design Space and Declarative Grammar for 3D Genomic Data Visualization.
Article in IEEE transactions on visualization and computer graphics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Uchimata: a toolkit for visualization of 3D genome structures on the web and in computational notebooks.Bioinformatics (Oxford, England) · 2026Article
- Uchimata: a toolkit for visualization of 3D genome structures on the web and in computational notebooks.ArXiv · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Various computational approaches predict chromatin structure, yielding concrete models that position genomic loci in physical space and help reveal genome organization and function. While prior visualization research has explored data and task abstractions for genomics, the design space for depicting these three-dimensional (3D) genome models-and associated genome-mapped data-remains unclear. In this paper, we investigate the visualization of genomic data with a spatial component. First, we systematically survey how 3D genome models are used and depicted in computational biology. We analyze over 300 papers with figures that visualize 3D genomic data and categorize the methods for visual representation. From this survey, we derive a design space for visualizing 3D genome data, identifying common patterns and key properties such as representation, visual channels, and composition. We position these findings within an existing genomics visualization taxonomy, refining and extending existing classifications. Second, we augment Gosling, a declarative visualization grammar for genomics, to support 3D genomic data. Our integration enables expressive authoring of visualizations that connect traditional genome-mapped information with 3D genome models, emphasizing their spatial characteristics. To demonstrate its utility, we employ our extended grammar to recreate interactive examples, showcasing its ability to represent complex visual designs. Comprehensive examples and an interactive editor are available at 3d.gosling-lang.org.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.