https://3demmethods.i2pc.es/index.php?action=history&feed=atom&title=2024Gaifas_Blik 2026-05-24T18:03:44Z Revision history for this page on the wiki MediaWiki 1.44.2 https://3demmethods.i2pc.es/index.php?title=2024Gaifas_Blik&diff=4654&oldid=prev 2024-08-09T06:15:10Z

<p>Created page with &quot;== Citation == Gaifas, Lorenzo / Kirchner, Moritz A. / Timmins, Joanna / Gutsche, Irina. Blik is an extensible 3D visualisation tool for the annotation and analysis of cryo-electron tomography data. 2024. PLoS biology, Vol. 22, No. 4, p. e3002447 == Abstract == Powerful, workflow-agnostic and interactive visualisation is essential for the ad hoc, humanin- the-loop workflows typical of cryo-electron tomography (cryo-ET). While several tools exist for visualisation and...&quot;</p> <p><b>New page</b></p><div>== Citation ==<br /> <br /> Gaifas, Lorenzo / Kirchner, Moritz A. / Timmins, Joanna / Gutsche, Irina. Blik is an extensible 3D visualisation tool for the annotation and analysis of cryo-electron tomography data. 2024. PLoS biology, Vol. 22, No. 4, p. e3002447<br /> <br /> == Abstract ==<br /> <br /> Powerful, workflow-agnostic and interactive visualisation is essential for the ad hoc, humanin-<br /> the-loop workflows typical of cryo-electron tomography (cryo-ET). While several tools<br /> exist for visualisation and annotation of cryo-ET data, they are often integrated as part of<br /> monolithic processing pipelines, or focused on a specific task and offering limited reusability<br /> and extensibility. With each software suite presenting its own pros and cons and tools tailored<br /> to address specific challenges, seamless integration between available pipelines is<br /> often a difficult task. As part of the effort to enable such flexibility and move the software ecosystem<br /> towards a more collaborative and modular approach, we developed blik, an opensource<br /> napari plugin for visualisation and annotation of cryo-ET data (source code: https://<br /> github.com/brisvag/blik). blik offers fast, interactive, and user-friendly 3D visualisation<br /> thanks to napari, and is built with extensibility and modularity at the core. Data is handled<br /> and exposed through well-established scientific Python libraries such as numpy arrays and<br /> pandas dataframes. Reusable components (such as data structures, file read/write, and<br /> annotation tools) are developed as independent Python libraries to encourage reuse and<br /> community contribution. By easily integrating with established image analysis tools—even<br /> outside of the cryo-ET world—blik provides a versatile platform for interacting with cryo-<br /> ET data. On top of core visualisation features—interactive and simultaneous visualisation of<br /> tomograms, particle picks, and segmentations—blik provides an interface for interactive<br /> tools such as manual, surface-based and filament-based particle picking, and image segmentation,<br /> as well as simple filtering tools. Additional self-contained napari plugins developed<br /> as part of this work also implement interactive plotting and selection based on particle<br /> features, and label interpolation for easier segmentation. Finally, we highlight the differences<br /> with existing software and showcase blik’s applicability in biological research.<br /> Introduction<br /> Cryo-electron tomography (cryo-ET) is a powerful three-dimensional (3D) cryo-electron<br /> microscopy (cryo-EM) imaging technique for visualisation and structural analysis of biological<br /> <br /> == Keywords ==<br /> <br /> == Links ==<br /> <br /> https://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.3002447<br /> <br /> == Related software ==<br /> <br /> == Related methods ==<br /> <br /> == Comments ==</div>

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