Skip to content

Health-Universe/spt-app1

 
 

Repository files navigation

spt-app logo

spt-app: web application of SPT model

This project provides the visualization of the simulation results at https://sptmodel.streamlit.app.

Simulation of zonation-function relationships in the liver using coupled multiscale models: Application to drug-induced liver injury Steffen Gerhäusser, Lena Lambers, Luis Mandl, Julian Franquinet, Tim Ricken, Matthias König bioRxiv 2024.03.26.586870; doi: https://doi.org/10.1101/2024.03.26.586870

Installation

To run the example applications install the requirements:

cd spt-app
mkvirtualenv spt_app --python=python3.11
(protein_app) pip install -r requirements.txt

Run app

To run the app use:

streamlit run main/spt_app.py

License

The spt-app source is released under both the GPL and LGPL licenses version 2 or later. You may choose which license you choose to use the software under.

This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License or the GNU Lesser General Public License as published by the Free Software Foundation, either version 2 of the License, or (at your option) any later version.

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

Funding

Matthias König is supported by the Federal Ministry of Education and Research (BMBF, Germany) within the research network Systems Medicine of the Liver (LiSyM, grant number 031L0054) and by the German Research Foundation (DFG) within the Research Unit Programme FOR 5151 "QuaLiPerF (Quantifying Liver Perfusion-Function Relationship in Complex Resection - A Systems Medicine Approach)" by grant number 436883643 and by grant number 465194077 (Priority Programme SPP 2311, Subproject SimLivA).

© 2024 Matthias König

Releases

No releases published

Packages

No packages published

Languages

  • Python 98.3%
  • Shell 1.7%