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A Web Tool for Generating High Quality Machine-readable Biological Pathways
Published on: February 8, 2017
BioBayes: a software package for Bayesian inference in systems biology.
Vladislav Vyshemirsky1, Mark Girolami
1Department of Computing Science, University of Glasgow, G12 8QQ, UK. vvv@dcs.gla.ac.uk
Bioinformatics (Oxford, England)
|July 18, 2008
Summary
This study introduces BioBayes, a software package for Bayesian inference in systems biology. It addresses uncertainties in kinetic parameters and model structures for biochemical systems.
Area of Science:
- Systems Biology
- Computational Biology
- Biochemical Modeling
Background:
- Mathematical modeling of biochemical systems involves uncertainties in kinetic parameters, model structure, and unobserved species behavior.
- Bayesian inference offers a robust framework for managing and predicting outcomes under these uncertain conditions.
Purpose of the Study:
- To present a software package, BioBayes, for applying Bayesian inferential methodology to systems biology problems.
- To provide a framework for Bayesian parameter estimation and model ranking in biochemical systems.
Main Methods:
- Utilizes ordinary differential equations to define models of biochemical systems.
- Implements Bayesian parameter estimation techniques.
- Incorporates evidential model ranking for comparing different model structures.
Main Results:
- The BioBayes package facilitates Bayesian parameter estimation for biochemical models.
- It enables evidential model ranking, allowing for the comparison and selection of the most supported models.
- The software is extensible, allowing for future module integration by developers.
Conclusions:
- BioBayes provides a unique and extensible solution for addressing uncertainty in biochemical systems modeling.
- The package offers a comprehensive framework for applying Bayesian inference in systems biology research.
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