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Data2Dynamics: a modeling environment tailored to parameter estimation in dynamical systems.

A Raue1, B Steiert2, M Schelker3

  • 1Merrimack Pharmaceuticals Inc., Discovery Devision, Cambridge, MA 02139, USA.

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|July 5, 2015
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Summary
This summary is machine-generated.

This study introduces Data2Dynamics, a MATLAB-based environment for systems biology modeling. It addresses challenges in constructing biochemical reaction network models and parameter estimation for large datasets, enabling efficient analysis.

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Area of Science:

  • Systems Biology
  • Computational Biology
  • Biochemical Engineering

Background:

  • Ordinary differential equations are widely used for dynamical systems modeling in systems biology.
  • Constructing complex biochemical reaction network models and performing parameter estimation are critical challenges.

Purpose of the Study:

  • To present a novel modeling environment in MATLAB to address challenges in dynamical systems modeling.
  • To facilitate the construction of biochemical reaction network models and parameter estimation for large datasets and complex conditions.

Main Methods:

  • Developed a MATLAB-based modeling environment named Data2Dynamics.
  • Parallelized and compiled computationally intensive tasks (solving differential equations and sensitivity systems) into efficient C code.
  • Implemented various parameter estimation algorithms and frequentist/Bayesian uncertainty analysis methods.

Main Results:

  • The Data2Dynamics environment effectively handles the construction of dynamical models for large datasets.
  • Efficient and reliable parameter estimation is achieved through parallelized computations and diverse algorithms.
  • The implemented methods have been successfully applied to multiple research applications, leading to publications.

Conclusions:

  • Data2Dynamics provides a pioneering solution for complex dynamical systems modeling in systems biology.
  • The environment enhances efficiency and reliability in model construction and parameter estimation.
  • It serves as a valuable, open-source tool for the research community.