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ABC-SysBio specifications


Unique identifier OMICS_09022
Name ABC-SysBio
Software type Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux, Mac OS
Programming languages Python
Computer skills Advanced
Version 2.05
Stability Stable
Maintained Yes


No version available



  • person_outline Michael Stumpf

Publications for ABC-SysBio

ABC-SysBio citations


Combining a Toggle Switch and a Repressilator within the AC DC Circuit Generates Distinct Dynamical Behaviors

Cell Syst
PMCID: 5929911
PMID: 29574056
DOI: 10.1016/j.cels.2018.02.008

[…] The parameter exploration was carried out using Bayesian sampling techniques through the Approximate Bayesian Computation (ABC) using ABC-SysBio software (). The score functions, d(), are minimal for the optimal behavior scored. They were designed to capture a change from stable steady state to oscillations. This was evaluated on tr […]


ABrox—A user friendly Python module for approximate Bayesian computation with a focus on model comparison

PLoS One
PMCID: 5843277
PMID: 29518130
DOI: 10.1371/journal.pone.0193981

[…] The main advantages of ABrox compared to other software packages such as the R-package abc [] or the Python module ABC-SysBio [] are the domain-independence, meaning that it is not designed for a specific field of research, and its ease of use due to the GUI. The software DIYABC [] is another attempt at simplifyin […]


Modeling the architecture of the regulatory system controlling methylenomycin production in Streptomyces coelicolor

J Biol Eng
PMCID: 5625687
PMID: 29026441
DOI: 10.1186/s13036-017-0071-6

[…] er to assess the potential of the 48 candidate architectures to reproduce the known characteristics of the system, we perform model selection based on approximate Bayesian computation (ABC) using the ABC-SysBio software package. ABC-SysBio combines Bayes’ rule with sequential Monte Carlo (SMC) approaches to solve parameter inference and model selection problems in systems biology [–]. The procedur […]


Multi level and hybrid modelling approaches for systems biology

Comput Struct Biotechnol J
PMCID: 5565741
PMID: 28855977
DOI: 10.1016/j.csbj.2017.07.005

[…] , quite often parameters of a given layer represent variables for an upward layer . It is therefore important to review common practices to perform this task.In , the authors present a platform named ABC-SysBio which provides tools for parameter estimation and model selection in systems biology. Parameter estimation is performed with approximate Bayesian computation . ABC-SysBio is designed to wor […]


Protein degradation rate is the dominant mechanism accounting for the differences in protein abundance of basal p53 in a human breast and colorectal cancer cell line

PLoS One
PMCID: 5425217
PMID: 28489927
DOI: 10.1371/journal.pone.0177336

[…] Model comparison and parameter estimation were carried out with an Approximate Bayesian Computation (ABC) method combined with sequential Monte Carlo (SMC) sampling, [] implemented in the ABC-SysBio python package and complemented with the GPU-accelerated simulation tool, cudasim. [,] Each experiment made up of a pair of p53 distributions were analysed independently.The model was simul […]


BCM: toolkit for Bayesian analysis of Computational Models using samplers

BMC Syst Biol
PMCID: 5073811
PMID: 27769238
DOI: 10.1186/s12918-016-0339-3

[…] chains were sampling the correct, optimal mode. In this case, Stan required approximately six hours to generate the requested samples. BioBayes was able to reach apparent convergence in 4.5 days. For ABC-SysBio, and SYSBIONS using ellipsoidal sampling, the samplers did not reach convergence in 7 days (see Additional file ). […]


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ABC-SysBio institution(s)
Centre for Bioinformatics, Division of Molecular Biosciences; Institute of Mathematical Sciences, Department of Epidemiology and Public Health, School of Public Health, and Centre for Integrative Systems Biology, Imperial College London, London, UK

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