Evidence map›Paper›PMID 37217252›Full record

ArticleGenome research2023

A fast and scalable method for inferring phylogenetic networks from trees by aligning lineage taxon strings.

Louxin Zhang, Niloufar Abhari, Caroline Colijn, Yufeng Wu

Abstract read
In one paragraph

Article in Genome research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. A vector representation for phylogenetic trees.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2025
    Article
  4. 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.

Louxin ZhangDepartment of Mathematics and Centre for Data Science and Machine Learning, National University of Singapore, Singapore 119076, Singapore; matzlx@nus.edu.sg.ORCID 0000-0003-0260-824X
Niloufar AbhariDepartment of Mathematics, Simon Fraser University, Burnaby, British Columbia V5A 1S6, Canada.
Caroline ColijnDepartment of Mathematics, Simon Fraser University, Burnaby, British Columbia V5A 1S6, Canada.
Yufeng WuDepartment of Computer Science and Engineering and Institute for Systems Genomics, University of Connecticut, Storrs, Connecticut 06269, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The reconstruction of phylogenetic networks is an important but challenging problem in phylogenetics and genome evolution, as the space of phylogenetic networks is vast and cannot be sampled well. One approach to the problem is to solve the minimum phylogenetic network problem, in which phylogenetic trees are first inferred, and then the smallest phylogenetic network that displays all the trees is computed. The approach takes advantage of the fact that the theory of phylogenetic trees is mature, and there are excellent tools available for inferring phylogenetic trees from a large number of biomolecular sequences. A tree-child network is a phylogenetic network satisfying the condition that every nonleaf node has at least one child that is of indegree one. Here, we develop a new method that infers the minimum tree-child network by aligning lineage taxon strings in the phylogenetic trees. This algorithmic innovation enables us to get around the limitations of the existing programs for phylogenetic network inference. Our new program, named ALTS, is fast enough to infer a tree-child network with a large number of reticulations for a set of up to 50 phylogenetic trees with 50 taxa that have only trivial common clusters in about a quarter of an hour on average.

Indexed as

AlgorithmsGenomeHumansPhylogeny

Identifiers

PMID37217252
PMCPMC10538497

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.