Mol* Volumes and Segmentations: visualization and interpretation of cell imaging data alongside macromolecular structure data and biological annotations.
Nucleic Acids Res
; 51(W1): W326-W330, 2023 07 05.
Article
em En
| MEDLINE
| ID: mdl-37194693
ABSTRACT
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/.
Texto completo:
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Base de dados:
MEDLINE
Assunto principal:
Processamento de Imagem Assistida por Computador
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Software
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Microscopia
Idioma:
En
Ano de publicação:
2023
Tipo de documento:
Article