ArticlePloS one2014
Bayesian model comparison and parameter inference in systems biology using nested sampling.
Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
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- Approximate Bayesian inference in a model for self-generated gradient collective cell movement.Computational statistics · 2025Article
- Bayesian model selection for COVID-19 pandemic state estimation using extended Kalman filters: Case study for Saudi Arabia.PLOS global public health · 2024Article
- Localization of Noise in Biochemical Networks.ACS omega · 2023Article
- Exact Bayesian inference for the detection of graft-mobile transcripts from sequencing data.Journal of the Royal Society, Interface · 2022Article
- Likelihood-free nested sampling for parameter inference of biochemical reaction networks.PLoS computational biology · 2020Article
- It's about time: Analysing simplifying assumptions for modelling multi-step pathways in systems biology.PLoS computational biology · 2020Article
- Bayesian modeling reveals metabolite-dependent ultrasensitivity in the cyanobacterial circadian clock.Molecular systems biology · 2020Article
- A Probabilistic Approach to Explore Signal Execution Mechanisms With Limited Experimental Data.Frontiers in genetics · 2020Article
- A Bayesian framework for the analysis of systems biology models of the brain.PLoS computational biology · 2019Article
- Comprehensive Review of Models and Methods for Inferences in Bio-Chemical Reaction Networks.Frontiers in genetics · 2019Review
- Incorporating prior knowledge improves detection of differences in bacterial growth rate.BMC systems biology · 2015Article
- Dizzy-Beats: a Bayesian evidence analysis tool for systems biology.Bioinformatics (Oxford, England) · 2015Article
- SYSBIONS: nested sampling for systems biology.Bioinformatics (Oxford, England) · 2015Article
- Computationally Modeling Lipid Metabolism and Aging: A Mini-review.Computational and structural biotechnology journal · 2015Review
- Bayesian parameter inference and model selection by population annealing in systems biology.PloS one · 2014Article
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2 authors.
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Abstract
Inferring parameters for models of biological processes is a current challenge in systems biology, as is the related problem of comparing competing models that explain the data. In this work we apply Skilling's nested sampling to address both of these problems. Nested sampling is a Bayesian method for exploring parameter space that transforms a multi-dimensional integral to a 1D integration over likelihood space. This approach focuses on the computation of the marginal likelihood or evidence. The ratio of evidences of different models leads to the Bayes factor, which can be used for model comparison. We demonstrate how nested sampling can be used to reverse-engineer a system's behaviour whilst accounting for the uncertainty in the results. The effect of missing initial conditions of the variables as well as unknown parameters is investigated. We show how the evidence and the model ranking can change as a function of the available data. Furthermore, the addition of data from extra variables of the system can deliver more information for model comparison than increasing the data from one variable, thus providing a basis for experimental design.
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