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Pleione: A tool for statistical and multi-objective calibration of Rule-based models
Rodrigo Santibáñez1,2, Daniel Garrido2, Alberto J M Martin3
1Network Biology Lab, Centro de Genómica y Bioinformática, Facultad de Ciencias, Universidad Mayor, Santiago, 8580745, Chile.
Scientific Reports
|October 24, 2019
Summary
This study introduces Pleione, a new software for calibrating Rule-Based Models (RBMs) in systems biology. Pleione enhances RBM analysis by efficiently distributing simulations and incorporating tests for model-data fitness.
Area of Science:
- Systems Biology
- Computational Biology
- Biophysics
Background:
- Mathematical models are crucial for simulating biological systems.
- Ordinary Differential Equation (ODE) models are common but can be complex.
- Rule-Based Models (RBMs) offer conciseness and flexibility but often lack analytical tools due to intensive simulations.
Purpose of the Study:
- To present Pleione, a novel software tool for calibrating RBMs.
- To address the computational challenges in simulating and analyzing RBMs.
- To facilitate the use of RBMs for reproducing experimental data.
Main Methods:
- Developed Pleione software for parameter calibration of RBMs.
- Implemented distributed stochastic simulations and calculations within Pleione.
- Integrated equivalence tests for assessing RBM fitness against experimental data.
Main Results:
- Pleione successfully calibrated RBMs, demonstrating efficiency in calculation time.
- The software achieved significant error reduction in model simulations.
- Equivalence tests confirmed the fitness of calibrated RBMs compared to experimental data.
Conclusions:
- Pleione provides a robust solution for calibrating RBMs, overcoming simulation and analysis limitations.
- The software is versatile, tested across various simulators, models, and computing infrastructures.
- Pleione facilitates deeper analysis and application of RBMs in systems biology research.
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