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Related Experiment Video

Updated: Jun 12, 2026

Segmentation and Measurement of Fat Volumes in Murine Obesity Models Using X-ray Computed Tomography

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Visualizing Volumetric and Segmentation Data using Mol* Volumes & Segmentations 2.0.

Aliaksei Chareshneu^1,2, Alessio Cantara^1,2, Dominick Tichý¹

¹National Centre for Biomolecular Research, Faculty of Science, Masaryk University, Brno, Czech Republic.

Current Protocols

|December 9, 2024

Summary

This summary is machine-generated.

Mol* Volumes & Segmentations (Mol* VS) 2.0 enhances web-based visualization of molecular data. This update introduces user-friendly annotation editing and shareable file generation, improving accessibility for researchers.

Keywords:

3D visualization tools annotation data large‐scale datasets segmentation data volumetric data

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Area of Science:

Structural Biology
Biophysics
Computational Biology

Background:

Increasing availability of experimental volumetric and segmentation data requires efficient web-based visualization tools.
Current solutions are scarce, limiting data interpretation and dissemination.
Previous Mol* VS version lacked annotation editing and seamless sharing capabilities, and required programming expertise.

Purpose of the Study:

To present Mol* Volumes & Segmentations (Mol* VS) 2.0, an improved web application for visualizing volumetric, segmentation, and annotation data.
To introduce user-friendly features for annotation editing and data sharing.
To provide protocols for utilizing Mol* VS 2.0 across various scales of molecular complex visualization.

Main Methods:

Development of the Annotation Editor, a graphical interface for editing annotations.
Introduction of the Volumes & Segmentations Toolkit (VSToolkit) for generating shareable visualization data files.
Outlining protocols for setting up and visualizing data using VSToolkit and Mol* VS 2.0.

Main Results:

Mol* VS 2.0 offers a user-friendly interface for editing annotations and generating shareable visualization files.
Protocols demonstrate the visualization of diverse data types, including geometric and lattice segmentations, multiple time frames, and volume channels.
The VSToolkit facilitates the creation of user-constructed database entries and supports server API deployment.

Conclusions:

Mol* VS 2.0 significantly enhances the accessibility and usability of web-based visualization for molecular volumetric and segmentation data.
The new features address limitations of previous versions, enabling easier data interpretation and dissemination.
This advancement supports progress in the field of molecular complex visualization by providing robust and user-friendly tools.