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ModelMage: a tool for automatic model generation, selection and management.

Max Flöttmann¹, Jörg Schaber, Stephan Hoops

¹Max-Planck-Institute for Molecular Genetics, Ihnestr 63-73, 14195 Berlin, Germany. floettma@molgen.mpg.de

Genome Informatics. International Conference on Genome Informatics

|May 9, 2009

Summary

This summary is machine-generated.

ModelMage simplifies biological systems modeling by automating the generation, simulation, and selection of candidate models from a master model. This tool aids researchers in efficiently managing and discriminating between alternative hypotheses for biological systems.

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Area of Science:

Systems Biology
Computational Biology
Bioinformatics

Background:

Mathematical modeling is crucial for understanding biological systems, but generating and managing diverse candidate models is challenging and error-prone.
Researchers often need to compare multiple models representing alternative hypotheses to accurately represent biological processes.

Purpose of the Study:

To introduce ModelMage, a software tool designed to streamline the development, generation, simulation, and discrimination of candidate models in systems biology.
To provide a user-friendly approach for creating a defined set of model alternatives from a single master model.

Main Methods:

ModelMage automatically generates candidate models by systematically omitting species, modifiers, or reactions from a user-provided Systems Biology Markup Language (SBML) master model.
The tool integrates with COPASI for simulation and optimization, enabling automated fitting of generated models to experimental data.
Candidate models are ranked based on their fit to data, facilitating model selection.

Main Results:

ModelMage enables the rapid and automated creation of a limited, user-defined set of alternative biological models.
The software facilitates efficient model discrimination through automated data fitting and ranking.
All simulation and optimization capabilities of COPASI are incorporated into ModelMage.

Conclusions:

ModelMage significantly reduces the complexity and potential for errors in generating and managing candidate models for biological systems.
The tool empowers researchers to efficiently explore and select the most appropriate model for their data, accelerating biological discovery.