Evidence map›Paper›PMID 33053706›Full record

ArticleInternational journal of molecular sciences2020

How Machine Learning Methods Helped Find Putative Rye Wax Genes Among GBS Data.

Magdalena Góralska, Jan Bińkowski, Natalia Lenarczyk, Anna Bienias, Agnieszka Grądzielewska, Ilona Czyczyło-Mysza, Kamila Kapłoniak, Stefan Stojałowski, Beata Myśków

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in International journal of molecular sciences, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Functional Genomics for Plant Breeding.International journal of molecular sciences · 2021
    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

9 authors.

Magdalena GóralskaDepartment of Plant Genetics, Breeding and Biotechnology, West-Pomeranian University of Technology, Szczecin, ul. Słowackiego 17, 71-434 Szczecin, Poland.
Jan BińkowskiDepartment of Plant Genetics, Breeding and Biotechnology, West-Pomeranian University of Technology, Szczecin, ul. Słowackiego 17, 71-434 Szczecin, Poland.
Natalia LenarczykDepartment of Plant Genetics, Breeding and Biotechnology, West-Pomeranian University of Technology, Szczecin, ul. Słowackiego 17, 71-434 Szczecin, Poland.
Anna BieniasDepartment of Plant Genetics, Breeding and Biotechnology, West-Pomeranian University of Technology, Szczecin, ul. Słowackiego 17, 71-434 Szczecin, Poland.
Agnieszka GrądzielewskaInstitute of Plant Genetics, Breeding and Biotechnology, University of Life Sciences in Lublin, ul. Akademicka, 20-950 Lublin, Poland.
Ilona Czyczyło-MyszaPolish Academy of Sciences, The Franciszek Górski Institute of Plant Physiology, Niezapominajek 21, 30-239 Kraków, Poland.
Kamila KapłoniakPolish Academy of Sciences, The Franciszek Górski Institute of Plant Physiology, Niezapominajek 21, 30-239 Kraków, Poland.
Stefan StojałowskiDepartment of Plant Genetics, Breeding and Biotechnology, West-Pomeranian University of Technology, Szczecin, ul. Słowackiego 17, 71-434 Szczecin, Poland.
Beata MyśkówDepartment of Plant Genetics, Breeding and Biotechnology, West-Pomeranian University of Technology, Szczecin, ul. Słowackiego 17, 71-434 Szczecin, Poland.ORCID 0000-0001-5062-9841

Funding

Narodowe Centrum Nauki 2015/17/B/NZ9/01694
6 · The paper itself

Abstract

The standard approach to genetic mapping was supplemented by machine learning (ML) to establish the location of the rye gene associated with epicuticular wax formation (glaucous phenotype). Over 180 plants of the biparental F

Indexed as

Genes, PlantMachine LearningWaxesBiomarkersChromosome MappingGenetic MarkersGenetics, PopulationGenotypePhenotypeQuantitative Trait LociSecaleBiomarkersGenetic MarkersWaxesfatty acid desaturase (FAD), genetic mapglaucousnessKeywords: ATP-binding cassette (ABC) transporterslarge-scale sequence-based markersSecale cereale L.

Identifiers

PMID33053706
PMCPMC7593958

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.