Development of a system that generates spatial SBML models using deep learning

<p>This project aims at creating and implementing a system that automatically generates various spatial SBML models by comprehensively segmenting microscopic images of cells using deep learning and XitoSBML. The Systems Biology Markup Language (SBML) is a popular and widely accepted XML-based, open-source language for representing and exchanging models across analysis and simulation tools. By utilizing the capabilities of SBML via its spatial package, XitoSBML can create spatial SBML models from microscopic cellular images. However, this package has only been partially implemented and is still under development. A poignant requirement of this development process is a large number of test models, which can be provided as deliverables via this project to the SBML repository. Thus, this project will be able to contribute towards the development of the SBML Version 3 spatial package. Furthermore, the provision of several spatial SBML models will enable checking the compatibility of software tools that deal with spatial SBML models.</p>