Dose-Dependent RTF Approach in Data2Dynamics

The main purpose of this file is to archive the current version of our code for the dose dependent RTF modelling that was used to produce the results for our publication Rachel et al. Dynamic modelling of signalling pathways when ODEs are not feasible that is submitted to Bioinformatics. The actual code for this can be found in the subfolder arFramework3/Examples/DoseDependentRTF with explanations in the ReadMe file. To make the code runable and to archive the current version we upload our software Data2Dynamics (30.10.2024) reduced by some not needed folders. 

For the current version of Data2Dynamics see https://github.com/Data2Dynamics and for the dose dependent RTF modelling see https://github.com/Data2Dynamics/d2d/tree/master/arFramework3/Examples/DoseDependentRTF.

Data2Dynamics is a project with many contributors that can not all be mentioned here: https://github.com/Data2Dynamics/d2d/graphs/contributors

For Third-Party Software see: https://github.com/Data2Dynamics/d2d/wiki/Copyright

Cite:

• Data2Dynamics: a modeling environment tailored to parameter estimation in dynamical systems. Raue A., et al. Bioinformatics, 31(21), 3558-3560, 2015.
• Lessons Learned from Quantitative Dynamical Modeling in Systems Biology. Raue A., et al. PLOS ONE, 8(9), e74335, 2013.
• A New Approximation Approach for Transient Differential Equation Models - Kreutz C. Front. Phys., 8, 70, 2020.