ReviewProtein science : a publication of the Protein Society2026
The evolving landscape of molecular visualization.
Review in Protein science : a publication of the Protein Society, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
1 citing paper in PubMed.
- The evolving landscape of molecular visualization.Protein science : a publication of the Protein Society · 2026Review
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
Molecular visualization plays a central role in structural biology, transforming data into representations that reveal how molecular form relates to function. Since the construction of the first protein models in the 1950s, visualization practices have evolved in tandem with experimental and computational advances, shaping both research and communication. Today's scientists rely on an expanding suite of digital tools to interpret structural, biophysical, and imaging data, while public repositories facilitate dissemination and education. Yet, as experimental methods capture ever more complex and dynamic molecular systems, the limitations of static visualizations have become apparent. Recent progress in animation, integrative modeling, and artificial intelligence offers new possibilities for representing molecular complexity and motion. This review traces the evolution of molecular visualization from physical models to dynamic, data-integrated animations and explores how emerging technologies promise to make visualization not only a medium of communication but also a tool for scientific exploration.
Indexed as
Identifiers
What OpenQuestion holds
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.