Evidence map›Paper›PMID 36287747›Full record

ArticleJournal of animal science and technology2022

Single nucleotide polymorphism marker combinations for classifying Yeonsan Ogye chicken using a machine learning approach.

Eunjin Cho, Sunghyun Cho, Minjun Kim, Thisarani Kalhari Ediriweera, Dongwon Seo, Seung-Sook Lee, Jihye Cha, Daehyeok Jin, Young-Kuk Kim, Jun Heon Lee

Abstract read
In one paragraph

Article in Journal of animal science and technology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

10 authors.

Eunjin ChoDepartment of Bio-AI Convergence, Chungnam National University, Daejeon 34134, Korea.ORCID https://orcid.org/0000-0003-4800-1603
Sunghyun ChoResearch and Development Center, Insilicogen Inc., Yongin 19654, Korea.ORCID https://orcid.org/0000-0002-2657-9159
Minjun KimDivision of Animal and Dairy Science, Chungnam National University, Daejeon 34134, Korea.ORCID https://orcid.org/0000-0002-8173-8431
Thisarani Kalhari EdiriweeraDepartment of Bio-AI Convergence, Chungnam National University, Daejeon 34134, Korea.ORCID https://orcid.org/0000-0001-9649-6925
Dongwon SeoDepartment of Bio-AI Convergence, Chungnam National University, Daejeon 34134, Korea.ORCID https://orcid.org/0000-0003-0548-7068
Seung-Sook LeeYeonsan Ogye Foundation, Nonsan 32910, Korea.ORCID https://orcid.org/0000-0002-1898-5448
Jihye ChaAnimal Genome & Bioinformatics, National Institute of Animal Science, Rural Development Administration, Wanju 55365, Korea.ORCID https://orcid.org/0000-0002-9705-2979
Daehyeok JinAnimal Genetic Resources Research Center, National Institute of Animal Science, Rural Development Administration, Hamyang 50000, Korea.ORCID https://orcid.org/0000-0001-5091-4271
Young-Kuk KimDepartment of Bio-AI Convergence, Chungnam National University, Daejeon 34134, Korea.ORCID https://orcid.org/0000-0002-8329-9348
Jun Heon LeeDepartment of Bio-AI Convergence, Chungnam National University, Daejeon 34134, Korea.ORCID https://orcid.org/0000-0003-3996-9209

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Genetic analysis has great potential as a tool to differentiate between different species and breeds of livestock. In this study, the optimal combinations of single nucleotide polymorphism (SNP) markers for discriminating the Yeonsan Ogye chicken (

Indexed as

Breed identificationMachineSingle nucleotide polymorphismYeonsan Ogye

Identifiers

PMID36287747
PMCPMC9574617

What OpenQuestion holds

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LicenceCC BY-NC
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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.