Evidence map›Paper›PMID 40624344›Full record

ArticleJournal of molecular evolution2025

Stochastic Character Mapping: An Under-Exploited Approach to the Study of Molecular Evolution.

Simon Laurin-Lemay, Nicolas Rodrigue

Abstract read
In one paragraph

Article in Journal of molecular evolution, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

2 authors.

Simon Laurin-LemayDepartment of Biology, Carleton University, 209 Nesbitt Biology Building, 1125 Colonel By Drive, Ottawa, ON, Canada. simon.laurin-lemay@proton.me.ORCID 0000-0003-4994-8786
Nicolas RodrigueDepartment of Biology, Carleton University, 209 Nesbitt Biology Building, 1125 Colonel By Drive, Ottawa, ON, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Methods for the probabilistic mapping of the history of state changes over a phylogeny have been available for the study of molecular evolution for over two decades. In spite of this, such methods have yet to be adopted at large by most molecular evolutionary biologists. Here, we re-emphasize the potential of these stochastic mappings with examples pertaining to the study of the amino acid replacement process. We show how the features targeted by today's top-performing models could have been highlighted in a full phylogenetic context with an amino acid-level Jukes-Cantor model. We also demonstrate how stochastic mappings could be used for detecting CpG hypermutability, a site-dependent feature. We hope for a larger project utilizing mapping-based methods to provide of more fulsome characterization of molecular evolution, and to prioritize and assess modeling efforts. Finally, we draw attention to the options available within the PhyloBayes(-MPI) software for producing mappings under a large set of evolutionary models.

Indexed as

Evolution, MolecularCpG IslandsModels, GeneticPhylogenySoftwareStochastic ProcessesAmino acid replacement processBayesian inferenceModel assessmentNucleotide substitution

Identifiers

PMID40624344
PMCPMC12354545

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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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.