Evidence map›Paper›PMID 39132289›Full record

ArticleBioinformatics advances2024

Marker discovery in the large.

Beatriz Vieira Mourato, Ivan Tsers, Svenja Denker, Fabian Klötzl, Bernhard Haubold

Abstract read
In one paragraph

Article in Bioinformatics advances, 2024. 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. Article
  4. Fast detection of unique genomic regions.Computational and structural biotechnology journal · 2025
    Review
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

5 authors.

Beatriz Vieira MouratoResearch Group Bioinformatics, Max-Planck-Institute for Evolutionary Biology, 24306 Plön, Schleswig-Holstein, Germany.
Ivan TsersResearch Group Bioinformatics, Max-Planck-Institute for Evolutionary Biology, 24306 Plön, Schleswig-Holstein, Germany.
Svenja DenkerResearch Group Bioinformatics, Max-Planck-Institute for Evolutionary Biology, 24306 Plön, Schleswig-Holstein, Germany.
Fabian KlötzlCambridge CB2 1LB, United Kingdom.
Bernhard HauboldResearch Group Bioinformatics, Max-Planck-Institute for Evolutionary Biology, 24306 Plön, Schleswig-Holstein, Germany.ORCID https://orcid.org/0000-0001-9442-4012

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Motivation: Markers for diagnostic polymerase chain reactions are routinely constructed by taking regions common to the genomes of a target organism and subtracting the regions found in the targets' closest relatives, their neighbors. This approach is implemented in the published package Fur, which originally required memory proportional to the number of nucleotides in the neighborhood. This does not scale well. Results: Here, we describe a new version of Fur that only requires memory proportional to the longest neighbor. In spite of its greater memory efficiency, the new Fur remains fast and is accurate. We demonstrate this by applying it to simulated sequences and comparing it to an efficient alternative. Then we use the new Fur to extract markers from 120 reference bacteria. To make this feasible, we also introduce software for automatically finding target and neighbor genomes and for assessing markers. We pick the best primers from the 10 most sequenced reference bacteria and show their excellent Availability and implementation: Fur is available from github.com/evolbioinf/fur, in the Docker image hub.docker.com/r/beatrizvm/mapro, and in the Code Ocean capsule 10.24433/CO.7955947.v1.

Identifiers

PMID39132289
PMCPMC11310107

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.