Sterzik, AnnaGillmann, ChristinaKrone, MichaelLawonn, KaiAngellini, MarcoGarth, ChristophKerren, Andreas2025-05-262025-05-2620251467-8659https://doi.org/10.1111/cgf.70155https://diglib.eg.org/handle/10.1111/cgf70155Molecular structure visualization is fundamental to molecular biology, aiding in understanding complex biological processes. While advancements in molecular visualization have greatly improved the representation of these structures, inherent uncertainties-such as inaccuracies in atomic positions or variability in secondary structure classifications-impact the accuracy of the visualizations. Uncertainty-aware visualization (UAV) emerged as a response to these challenges, integrating uncertainty into visual representations to improve data interpretation and decisionmaking. Despite extensive work on both molecular and uncertainty visualization (UV), there is a lack of comprehensive surveys addressing the intersection of these two fields. This paper provides a state-of-the-art review of UAV approaches for biomolecular structures. We propose a classification schema that organizes existing methods based on the type of molecule visualized, the manifestation of uncertainty, and the mapping of uncertainty to a visual representation. Using this framework, we identified research gaps and areas for future exploration in uncertainty-aware biomolecular structure visualization.Attribution 4.0 International License10.1111/cgf.7015528 pages