XitoSBML: A Modeling Tool for Creating Spatial Systems Biology Markup Language Models From Microscopic Images

Area of Science:

• Systems Biology
• Bioinformatics
• Computational Biology

Background:

• Accurate spatial modeling of cellular structures is crucial for understanding biological processes.
• Existing tools may lack the capability to directly translate microscopic images into detailed spatial models.
• Systems Biology Markup Language (SBML) is a standard for representing biological models.

Purpose of the Study:

• To introduce XitoSBML, an ImageJ plugin for creating SBML Level 3 Version 1 documents from microscopic cellular images.
• To facilitate the generation of spatial models that accurately represent three-dimensional cellular geometry.
• To enable simulations of biological systems using realistic cellular structures.

Main Methods:

• XitoSBML is implemented as a plug-in for ImageJ, a widely used image processing software.
• The tool processes microscopic cellular images to extract geometric information.
• It generates an SBML Level 3 Version 1 document encoding the spatial model.

Main Results:

• XitoSBML successfully creates SBML documents from cellular images.
• The generated models reflect the three-dimensional cellular geometry.
• The software is confirmed to be compatible with Windows, MacOS, and Linux operating systems.

Conclusions:

• XitoSBML provides a novel approach for building spatial models from image data.
• It enhances the ability to perform simulations based on realistic cellular geometry.
• The open-source availability and cross-platform compatibility of XitoSBML promote its adoption in systems biology research.