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@article{2309937,
author = {Chareshneu, Aliaksei and Midlik, Adam and Ionescu, CrinaandMaria and Rose, Alexander and Horský, Vladimír and Cantara, Alessio and Svobodová, Radka and Berka, Karel and Sehnal, David},
article_number = {W1},
doi = {http://dx.doi.org/10.1093/nar/gkad411},
keywords = {3D structure; visualization; biomacromolecules; organelle- and cell-sized models},
language = {eng},
issn = {0305-1048},
journal = {Nucleic Acids Research},
title = {Mol* Volumes and Segmentations: visualization and interpretation of cell imaging data alongside macromolecular structure data and biological annotations},
url = {https://doi.org/10.1093/nar/gkad411},
volume = {51},
year = {2023}
}
TY - JOUR
ID - 2309937
AU - Chareshneu, Aliaksei - Midlik, Adam - Ionescu, Crina-Maria - Rose, Alexander - Horský, Vladimír - Cantara, Alessio - Svobodová, Radka - Berka, Karel - Sehnal, David
PY - 2023
TI - Mol* Volumes and Segmentations: visualization and interpretation of cell imaging data alongside macromolecular structure data and biological annotations
JF - Nucleic Acids Research
VL - 51
IS - W1
SP - "W326"-"W330"
EP - "W326"-"W330"
PB - Oxford University Press
SN - 03051048
KW - 3D structure
KW - visualization
KW - biomacromolecules
KW - organelle- and cell-sized models
UR - https://doi.org/10.1093/nar/gkad411
N2 - Segmentation helps interpret imaging data in a biological context. With the development of powerful tools for automated segmentation, public repositories for imaging data have added support for sharing and visualizing segmentations, creating the need for interactive web-based visualization of 3D volume segmentations. To address the ongoing challenge of integrating and visualizing multimodal data, we developed Mol* Volumes and Segmentations (Mol*VS), which enables the interactive, web-based visualization of cellular imaging data supported by macromolecular data and biological annotations. Mol*VS is fully integrated into Mol* Viewer, which is already used for visualization by several public repositories. All EMDB and EMPIAR entries with segmentation datasets are accessible via Mol*VS, which supports the visualization of data from a wide range of electron and light microscopy experiments. Additionally, users can run a local instance of Mol*VS to visualize and share custom datasets in generic or application-specific formats including volumes in .ccp4, .mrc, and .map, and segmentations in EMDB-SFF .hff, Amira .am, iMod .mod, and Segger .seg. Mol*VS is open source and freely available at https://molstarvolseg.ncbr.muni.cz/.
ER -
CHARESHNEU, Aliaksei, Adam MIDLIK, Crina-Maria IONESCU, Alexander ROSE, Vladimír HORSKÝ, Alessio CANTARA, Radka SVOBODOVÁ, Karel BERKA and David SEHNAL. Mol* Volumes and Segmentations: visualization and interpretation of cell imaging data alongside macromolecular structure data and biological annotations. \textit{Nucleic Acids Research}. Oxford University Press, 2023, vol.~51, W1, p.~''W326''-''W330'', 5 pp. ISSN~0305-1048. Available from: https://dx.doi.org/10.1093/nar/gkad411.
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