Evidence map›Paper›PMID 28983516›Full record

ReviewNature ecology & evolution2017

A biologist's guide to Bayesian phylogenetic analysis.

Fabrícia F Nascimento, Mario Dos Reis, Ziheng Yang

Abstract readReview
In one paragraph

Review in Nature ecology & evolution, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 78 papers.

0numbers the graph read from it
0cells of the map it votes in
78citing 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

78 citing papers in PubMed.

  1. Trial
  2. Article
  3. Article
  4. Review
  5. Article
  6. Review
  7. Biological causes and impacts of rugged tree landscapes in phylodynamic inference.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  8. Trophic niche partitioning in giant clams.Communications biology · 2025
    Article
  9. Recent horizontal transfer of transposable elements inbioRxiv : the preprint server for biology · 2025
    Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Fungal systematics and evolution · 2025
    Article
  15. Article
  16. Article
  17. Review
  18. Article
  19. Article
  20. Article

18 more citing papers are in PubMed but not listed here.

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.

Fabrícia F NascimentoDepartment of Zoology, University of Oxford, Oxford, OX1 3PS, UK. f.nascimento@imperial.ac.uk.ORCID http://orcid.org/0000-0001-9426-6835
Mario Dos ReisSchool of Biological and Chemical Sciences, Queen Mary University of London, London, E1 4NS, UK.ORCID http://orcid.org/0000-0001-9514-3976
Ziheng YangDepartment of Genetics, Evolution and Environment, University College London, London, WC1E 6BT, UK. z.yang@ucl.ac.uk.ORCID http://orcid.org/0000-0003-3351-7981

Funding

Biotechnology and Biological Sciences Research Council BB/N000609/1
6 · The paper itself

Abstract

Bayesian methods have become very popular in molecular phylogenetics due to the availability of user-friendly software implementing sophisticated models of evolution. However, Bayesian phylogenetic models are complex, and analyses are often carried out using default settings, which may not be appropriate. Here, we summarize the major features of Bayesian phylogenetic inference and discuss Bayesian computation using Markov chain Monte Carlo (MCMC), the diagnosis of an MCMC run, and ways of summarising the MCMC sample. We discuss the specification of the prior, the choice of the substitution model, and partitioning of the data. Finally, we provide a list of common Bayesian phylogenetic software and provide recommendations as to their use.

Indexed as

Bayes TheoremEvolution, MolecularModels, GeneticPhylogenyMarkov ChainsMonte Carlo MethodSoftware

Identifiers

PMID28983516
PMCPMC5624502

What OpenQuestion holds

Textmetadata
LicenceTDM
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.