Background:
Molecular communication (MC) uses signaling molecules to transmit information between bio-chemical communication nodes. In the human body, similar mechanisms already enable natural processes such as cellular signaling. Synthetic MC systems aim to exploit these principles for applications such as early disease detection, targeted drug delivery, and health monitoring.
MIGHT – A Model for MC in Vessel Networks:
The cardiovascular system is a key application domain for in-body MC. To study molecule transport in such environments, we developed the Mixture of Inverse Gaussians for Hemodynamic Transport (MIGHT) model, which describes the advection-diffusion driven propagation of signaling molecules in complex vessel networks (VNs) and predicts molecule concentrations over time and space.
Project Aim:
To make the MIGHT model more accessible to researchers, this project aims to develop a graphical user interface (GUI) in Python. The GUI will allow users to design VNs, set system parameters, run simulations, and visualize molecule transport and received signals within the network.
Project Objectives:
- Review and understand the MIGHT model.
- Simplify and improve the structure of existing object-oriented Python code for the model.
- Create a GUI for the MIGHT model, including the following functionalities:
1) A window for drawing VNs by hand/loading VNs from memory/saving VNs to memory.
2) Buttons for simulating fluid flow and molecule transport in the VN, including color-coding of flow rates, molecule concentrations, and the plotting of received signals.
3) Plotting of selected model applications, including the structural reduction of VNs and the color-coding of the molecule transport importance of all vessels in the VN. - Publication of the developed GUI, including the backend model code.
Prerequisites:
- Basic understanding of mathematical modeling
- Advanced programming skills in Python
A full description of the project can be found here. Depending on the type of project (Bachelor Thesis/Research Project), the scope can be adjusted. In case you are interested in pursuing this project, please contact Timo Jakumeit (timo.jakumeit@fau.de) or Dr.-Ing. Maximilian Schäfer (max.schaefer@fau.de).