Dynamic notebooks for QSP usage case: Insulin Signaling in Type 2 Diabetes
Background: Currently the mathematical modeling is applied for drug discovery and development. The report preparation and presentation are time-demanding processes. Using the formats of dynamic reports like R Markdown, Jupiter or similar ones is a good decision because of the following:
- Reducing time for report writing and update;
- Easy results share, review, and reproduction;
- Usage of interactivity capabilities, testing of “what-if” scenarios.
Objectives: Application and testing several software configurations for the development and analysis of dynamic reports. Testing the integration of the Heta-based platform into the presented environments. Comparison of the capabilities and technical issues for different configurations.
Methods: We tested several configurations for dynamic reporting:
- Julia environment + HetaSimulator.jl + Jupiter notebooks.
- Julia environment + HetaSimulator.jl + Pluto.jl;
- R environment + heta-compiler + mrgsolve + R Markdown;
- R environment + heta-compiler + mrgsolve + Jupiter notebook;
Results: The dynamic report was created for each model and configuration. It included model code loading, single and Monte-Carlo simulations, and visualization plots. All settings and configuration files are shared on GitHub.
Discussion: The following features of modeling infrastructure is very important for successful and effective dynamic reports:
- representation of QSP model in human-readable format or another unified format,
- loading of a model from programming environment,
- Simulation engine available from programming environments, like R or Julia. If you use a standardized modeling environment like the Heta-based modeling platform and heta-compiler tool the development of a dynamic report requires no more than one hour.
- /julia : files to run in plain julia, scenarios tables for all notebooks
- /julia-jupiter : The Jupiter-based notebook, can be run with
using IJulia; notebook(dir=".")
in Julia - /julia-pluto : The Pluto-based notebook, can be run with
using Pluto; Pluto.run()
in Julia - /r-markdown : RMarkdown notebook, can be run from RStudio using
knit
mechanism - /r-jupiter : The Jupiter-based notebook, can be run with anaconda. Commands:
conda activate snowflakes
,jupyter notebook --notebook-dir=Y:/PLATFORMS/insulin-signaling-t2d/r-jupiter)
- /static : the result of the notebooks execution, not interactive: julia-jupiter.html, julia-pluto.html, r-markdown.html, r-jupiter.html
- /src : source files of QSP model, Heta-based format + downloaded SBML
- platform.json : Heta platform's declaration file
- README.md : this file
The model and data were reconstructed from the article:
Brannmark C, Nyman E, Fagerholm S, Bergenholm L, Ekstrand EM, Cedersund G, Stralfors P. Insulin Signaling in Type 2 Diabetes: Experimental and modeling analysis reveal mechanisms of insulin resistance in human adipocytes. Journal of biological chemistry. 2013 288(14):9867–9880. DOI: 10.1074/jbc.M112.432062
The SBML version was downloaded from BioModels https://www.ebi.ac.uk/biomodels/BIOMD0000000448
- @metelkin
The model and data in the study were reproduced from the published study. The authors of the original study are: Brannmark C, Nyman E, Fagerholm S, Bergenholm L, Ekstrand EM, Cedersund G, Stralfors P.