Evidence map›Paper›PMID 42209743›Full record

ArticleScientific reports2026

DupyliCate: mining, classifying, and characterizing gene duplications.

Shakunthala Natarajan, Boas Pucker

Abstract read
In one paragraph

Article in Scientific reports, 2026. 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. 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

2 authors.

Shakunthala NatarajanPlant Biotechnology and Bioinformatics, Institute for Cellular and Molecular Botany, University of Bonn, Kirschallee 1, 53115, Bonn, Germany.
Boas PuckerPlant Biotechnology and Bioinformatics, Institute for Cellular and Molecular Botany, University of Bonn, Kirschallee 1, 53115, Bonn, Germany. pucker@uni-bonn.de.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Paralogs, copies of a gene, form an important basis for novelty during evolution. Analysis of such gene duplications is important to understand the emergence of novel traits during evolution. DupyliCate is a Python tool that has been developed for this purpose. With the ability to process multiple datasets concurrently, flexible features, and parameters to set species-specific thresholds, DupyliCate offers a high-throughput method for gene copy identification and analysis. The different available parameters and modes are explored in detail based on Arabidopsis thaliana datasets. Proof of concept for the tool is presented by characterizing well known duplications in different plants, and its broad applicability is demonstrated by running it on diverse datasets including complex plant genome sequences with high heterozygosity. Further, two case studies involving the evolution of FLAVONOL SYNTHASE (FLS) genes in Brassicales, and the evolution of flavonol synthesis regulating myeloblastosis (MYB) transcription factors-MYB12 and MYB111 across a large number of plant species, are presented as exemplar use cases. The tool's applicability beyond plants is demonstrated on Escherichia coli, Saccharomyces cerevisiae, and Caenorhabditis elegans datasets. DupyliCate is available at: https://github.com/ShakNat/DupyliCate .

Indexed as

Computational BiologyData MiningGene DuplicationSoftwareArabidopsisEvolution, MolecularGenome, PlantComparative genomicsEvolutionExpression analysisGene duplicationsHigh-throughputKa/Ks

Identifiers

PMID42209743
PMCPMC13219399

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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.