Evidence map›Paper›PMID 35594308›Full record

ArticlePloS one2022

A polynomial invariant for a new class of phylogenetic networks.

Joan Carles Pons, Tomás M Coronado, Michael Hendriksen, Andrew Francis

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2022. 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
0.6field-weighted citation impact, top 36% of its field
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, 7 citations in OpenAlex.

  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

4 authors at 3 institutions in 2 countries.

Joan Carles PonsDepartment of Mathematics and Computer Science, University of the Balearic Islands, Palma, Spain.ORCID 0000-0002-0313-3357
Tomás M CoronadoDepartment of Mathematics and Computer Science, University of the Balearic Islands, Palma, Spain.
Michael HendriksenSchool of Mathematics and Statistics, University of Melbourne, Melbourne, Australia.
Andrew FrancisCentre for Research in Mathematics and Data Science, Western Sydney University, Parramatta, Australia.
Universitat de les Illes Balears · ESThe University of Melbourne · AUWestern Sydney University · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Invariants for complicated objects such as those arising in phylogenetics, whether they are invariants as matrices, polynomials, or other mathematical structures, are important tools for distinguishing and working with such objects. In this paper, we generalize a complete polynomial invariant on trees to a class of phylogenetic networks called separable networks, which will include orchard networks. Networks are becoming increasingly important for their ability to represent reticulation events, such as hybridization, in evolutionary history. We provide a function from the space of internally multi-labelled phylogenetic networks, a more generic graph structure than phylogenetic networks where the reticulations are also labelled, to a polynomial ring. We prove that the separability condition allows us to characterize, via the polynomial, the phylogenetic networks with the same number of leaves and same number of reticulations by considering their internally labelled versions. While the invariant for trees is a polynomial in [Formula: see text] where n is the number of leaves, the invariant for internally multi-labelled phylogenetic networks is an element of [Formula: see text], where r is the number of reticulations in the network. When the networks are considered without leaf labels the number of variables reduces to r + 2.

Indexed as

Mathematical ConceptsModels, GeneticAlgorithmsBiological EvolutionPhylogeny

Identifiers

PMID35594308
PMCPMC9122212
OpenAlexW4280595454

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.