SYSBIONS: nested sampling for systems biology.
basic_science · Level V
Where this comes from
- Record sourced from PubMed, PMID 25399028.
- Also identified by DOI 10.1093/bioinformatics/btu675 and PMC identifier 4325544.
- Licence recorded as CC BY.
- The licence permits redistribution, so the abstract is shown in full and the full text is available from the publisher.
Abstract
Model selection is a fundamental part of the scientific process in systems biology. Given a set of competing hypotheses, we routinely wish to choose the one that best explains the observed data. In the Bayesian framework, models are compared via Bayes factors (the ratio of evidences), where a model's evidence is the support given to the model by the data. A parallel interest is inferring the distribution of the parameters that define a model. Nested sampling is a method for the computation of a model's evidence and the generation of samples from the posterior parameter distribution. We present a C-based, GPU-accelerated implementation of nested sampling that is designed for biological applications. The algorithm follows a standard routine with optional extensions and additional features. We provide a number of methods for sampling from the prior subject to a likelihood constraint. The software SYSBIONS is available from http://www.theosysbio.bio.ic.ac.uk/resources/sysbions/ m.stumpf@imperial.ac.uk, robert.johnson11@imperial.ac.uk.
Medical subject headings
- Algorithms
- Models, Biological
- Software
- Systems Biology