Dizzy-Beats: a Bayesian evidence analysis tool for systems biology.

Stuart Aitken, Alastair M Kilpatrick, Ozgur E Akman

Abstract read

In one paragraph

Article in Bioinformatics (Oxford, England), 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it

0cells of the map it votes in

2citing papers in PubMed

–field-weighted citation impact

1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

Systems Bioinformatics: increasing precision of computational diagnostics and therapeutics through network-based approaches.Briefings in bioinformatics · 2019
Review
Optimisation of an exemplar oculomotor model using multi-objective genetic algorithms executed on a GPU-CPU combination.BMC systems biology · 2017
Article

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Stuart AitkenMRC Human Genetics Unit, IGMM, University of Edinburgh, Edinburgh EH4 2XU, UK, School of Informatics, University of Edinburgh, Edinburgh EH8 9AB, UK, Department of Pediatrics, University of California San Diego, La Jolla, CA 92093, USA, Centre for Systems, Dynamics and Control, College of Engineering, Mathematics & Physical Sciences, University of Exeter, Exeter EX4 4QF, UK.

Alastair M KilpatrickMRC Human Genetics Unit, IGMM, University of Edinburgh, Edinburgh EH4 2XU, UK, School of Informatics, University of Edinburgh, Edinburgh EH8 9AB, UK, Department of Pediatrics, University of California San Diego, La Jolla, CA 92093, USA, Centre for Systems, Dynamics and Control, College of Engineering, Mathematics & Physical Sciences, University of Exeter, Exeter EX4 4QF, UK MRC Human Genetics Unit, IGMM, University of Edinburgh, Edinburgh EH4 2XU, UK, School of Informatics, University of Edinburgh, Edinburgh EH8 9AB, UK, Department of Pediatrics, University of California San Diego, La Jolla, CA 92093, USA, Centre for Systems, Dynamics and Control, College of Engineering, Mathematics & Physical Sciences, University of Exeter, Exeter EX4 4QF, UK.

Ozgur E AkmanMRC Human Genetics Unit, IGMM, University of Edinburgh, Edinburgh EH4 2XU, UK, School of Informatics, University of Edinburgh, Edinburgh EH8 9AB, UK, Department of Pediatrics, University of California San Diego, La Jolla, CA 92093, USA, Centre for Systems, Dynamics and Control, College of Engineering, Mathematics & Physical Sciences, University of Exeter, Exeter EX4 4QF, UK.

Funding

Biotechnology and Biological Sciences Research Council BB/I023461/1

6 · The paper itself

Abstract

motivationModel selection and parameter inference are complex problems of long-standing interest in systems biology. Selecting between competing models arises commonly as underlying biochemical mechanisms are often not fully known, hence alternative models must be considered. Parameter inference yields important information on the extent to which the data and the model constrain parameter values.

resultsWe report Dizzy-Beats, a graphical Java Bayesian evidence analysis tool implementing nested sampling - an algorithm yielding an estimate of the log of the Bayesian evidence Z and the moments of model parameters, thus addressing two outstanding challenges in systems modelling. A likelihood function based on the L1-norm is adopted as it is generically applicable to replicated time series data. AVAILABILITY AND IMPLEMENTATION: http://sourceforge.net/p/bayesevidence/home/Home/.

Indexed as

SoftwareSystems BiologyAlgorithmsBayes TheoremLikelihood FunctionsModels, Biological

Identifiers

PMID25637558

DOI10.1093/bioinformatics/btv062

PMCPMC4443683

What OpenQuestion holds

Textmetadata

LicenceCC BY-NC

Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.