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Mol* Volumes and Segmentations: visualization and interpretation of cell imaging data alongside macromolecular structure data and biological annotations.
Chareshneu, Aliaksei; Midlik, Adam; Ionescu, Crina-Maria; Rose, Alexander; Horský, Vladimír; Cantara, Alessio; Svobodová, Radka; Berka, Karel; Sehnal, David.
Afiliación
  • Chareshneu A; National Centre for Biomolecular Research, Faculty of Science, Masaryk University, 625 00 Brno, Czech Republic.
  • Midlik A; National Centre for Biomolecular Research, Faculty of Science, Masaryk University, 625 00 Brno, Czech Republic.
  • Ionescu CM; Biological Data Management and Analysis Core Facility, Centre for Structural Biology, CEITEC - Central European Institute of Technology, Masaryk University, 625 00 Brno, Czech Republic.
  • Rose A; National Centre for Biomolecular Research, Faculty of Science, Masaryk University, 625 00 Brno, Czech Republic.
  • Horský V; Mol* Consortium, San Diego, CA 92109, USA.
  • Cantara A; National Centre for Biomolecular Research, Faculty of Science, Masaryk University, 625 00 Brno, Czech Republic.
  • Svobodová R; Biological Data Management and Analysis Core Facility, Centre for Structural Biology, CEITEC - Central European Institute of Technology, Masaryk University, 625 00 Brno, Czech Republic.
  • Berka K; National Centre for Biomolecular Research, Faculty of Science, Masaryk University, 625 00 Brno, Czech Republic.
  • Sehnal D; Biological Data Management and Analysis Core Facility, Centre for Structural Biology, CEITEC - Central European Institute of Technology, Masaryk University, 625 00 Brno, Czech Republic.
Nucleic Acids Res ; 51(W1): W326-W330, 2023 07 05.
Article en 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/.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Procesamiento de Imagen Asistido por Computador / Programas Informáticos / Microscopía Idioma: En Revista: Nucleic Acids Res Año: 2023 Tipo del documento: Article País de afiliación: República Checa

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Procesamiento de Imagen Asistido por Computador / Programas Informáticos / Microscopía Idioma: En Revista: Nucleic Acids Res Año: 2023 Tipo del documento: Article País de afiliación: República Checa