# RTF: an R package for modelling time course data

## TL;DR

The RTF R package provides a new tool for modeling time course data in cellular signaling, offering an alternative to traditional ODE methods.

## Contribution

The novel contribution is an R implementation of the RTF approach, enabling model reduction and analysis of time and dose dependencies.

## Key findings

- The RTF package can model time course data and reduce model complexity to prevent overfitting.
- It supports analysis of experimental data or ODE model trajectories to capture dynamic behavior.
- The package generates low-dimensional representations to identify key targets of experimental perturbations.

## Abstract

The retarded transient function (RTF) approach serves as a complementary method to ordinary differential equations (ODEs) for modelling dynamics typically observed in cellular signalling processes. We introduce an R package that implements the RTF approach, originally implemented within the MATLAB-based Data2Dynamics modelling framework. This package facilitates the modelling of time and dose dependencies, and it includes the possibility of model reduction to minimize overfitting. It can be applied to experimental data or trajectories of ODE models to characterize their dynamics. Additionally, it can generate a low-dimensional representation based on the fitted RTF parameters of a set of time-resolved data, aiding in the identification of key targets of experimental perturbations.

The R package RTF is available at https://github.com/kreutz-lab/RTF.