Evidence map›Paper›PMID 35989607›Full record

ReviewPhilosophical transactions of the Royal Society of London. Series B, Biological sciences2022

Recent progress on methods for estimating and updating large phylogenies.

Paul Zaharias, Tandy Warnow

Abstract readReview
In one paragraph

Review in Philosophical transactions of the Royal Society of London. Series B, Biological sciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Genomic population structures of microbial pathogens.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2022
    Article
  7. EnteroBase: hierarchical clustering of 100 000s of bacterial genomes into species/subspecies and populations.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2022
    Article
  8. 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.

Paul ZahariasDepartment of Computer Science, University of Illinois Urbana-Champaign, Urbana, IL 61801, USA.ORCID 0000-0003-3550-2636
Tandy WarnowDepartment of Computer Science, University of Illinois Urbana-Champaign, Urbana, IL 61801, USA.ORCID 0000-0001-7717-3514

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With the increased availability of sequence data and even of fully sequenced and assembled genomes, phylogeny estimation of very large trees (even of hundreds of thousands of sequences) is now a goal for some biologists. Yet, the construction of these phylogenies is a complex pipeline presenting analytical and computational challenges, especially when the number of sequences is very large. In the past few years, new methods have been developed that aim to enable highly accurate phylogeny estimations on these large datasets, including divide-and-conquer techniques for multiple sequence alignment and/or tree estimation, methods that can estimate species trees from multi-locus datasets while addressing heterogeneity due to biological processes (e.g. incomplete lineage sorting and gene duplication and loss), and methods to add sequences into large gene trees or species trees. Here we present some of these recent advances and discuss opportunities for future improvements. This article is part of a discussion meeting issue 'Genomic population structures of microbial pathogens'.

Indexed as

Gene DuplicationGenomicsPhylogenySequence Alignmentmaximum likelihoodmultiple sequence alignmentphylogenetic placementphylogenomicsphylogeny estimationtaxon identification

Identifiers

PMID35989607
PMCPMC9393559

What OpenQuestion holds

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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.