Literature DB >> 18632751

BioBayes: a software package for Bayesian inference in systems biology.

Vladislav Vyshemirsky1, Mark Girolami.   

Abstract

MOTIVATION: There are several levels of uncertainty involved in the mathematical modelling of biochemical systems. There often may be a degree of uncertainty about the values of kinetic parameters, about the general structure of the model and about the behaviour of biochemical species which cannot be observed directly. The methods of Bayesian inference provide a consistent framework for modelling and predicting in these uncertain conditions. We present a software package for applying the Bayesian inferential methodology to problems in systems biology.
RESULTS: Described herein is a software package, BioBayes, which provides a framework for Bayesian parameter estimation and evidential model ranking over models of biochemical systems defined using ordinary differential equations. The package is extensible allowing additional modules to be included by developers. There are no other such packages available which provide this functionality.

Mesh:

Year:  2008        PMID: 18632751     DOI: 10.1093/bioinformatics/btn338

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  21 in total

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2.  Calibration of dynamic models of biological systems with KInfer.

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Journal:  Eur Biophys J       Date:  2009-08-11       Impact factor: 1.733

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5.  Well-tempered MCMC simulations for population pharmacokinetic models.

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Journal:  J Pharmacokinet Pharmacodyn       Date:  2020-07-31       Impact factor: 2.745

6.  ABC-SysBio--approximate Bayesian computation in Python with GPU support.

Authors:  Juliane Liepe; Chris Barnes; Erika Cule; Kamil Erguler; Paul Kirk; Tina Toni; Michael P H Stumpf
Journal:  Bioinformatics       Date:  2010-07-15       Impact factor: 6.937

7.  In silico model-based inference: an emerging approach for inverse problems in engineering better medicines.

Authors:  David J Klinke; Marc R Birtwistle
Journal:  Curr Opin Chem Eng       Date:  2015-11-01       Impact factor: 5.163

8.  A framework for parameter estimation and model selection from experimental data in systems biology using approximate Bayesian computation.

Authors:  Juliane Liepe; Paul Kirk; Sarah Filippi; Tina Toni; Chris P Barnes; Michael P H Stumpf
Journal:  Nat Protoc       Date:  2014-01-23       Impact factor: 13.491

9.  Data Driven Mathematical Model of FOLFIRI Treatment for Colon Cancer.

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Journal:  Cancers (Basel)       Date:  2021-05-27       Impact factor: 6.639

10.  Nested sampling for parameter inference in systems biology: application to an exemplar circadian model.

Authors:  Stuart Aitken; Ozgur E Akman
Journal:  BMC Syst Biol       Date:  2013-07-30
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