Evidence map›Paper›PMID 32117419›Full record

ArticleFrontiers in genetics2019

Identification of Biological Pathways Contributing to Marbling in Skeletal Muscle to Improve Beef Cattle Breeding.

Zahra Roudbari, Susan L Coort, Martina Kutmon, Lars Eijssen, Jonathan Melius, Tomasz Sadkowski, Chris T Evelo

Open access · goldAbstract read
In one paragraph

Article in Frontiers in genetics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
2.1field-weighted citation impact, top 15% of its field
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

16 citing papers in PubMed, 25 citations in OpenAlex.

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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

7 authors at 3 institutions in 3 countries.

Zahra RoudbariDepartment of Animal Science, Faculty of Agriculture, University of Jiroft, Jiroft, Iran.
Susan L CoortDepartment of Bioinformatics-BiGCaT, NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht University, Maastricht, Netherlands.
Martina KutmonDepartment of Bioinformatics-BiGCaT, NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht University, Maastricht, Netherlands.
Lars EijssenDepartment of Bioinformatics-BiGCaT, NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht University, Maastricht, Netherlands.
Jonathan MeliusDepartment of Bioinformatics-BiGCaT, NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht University, Maastricht, Netherlands.
Tomasz SadkowskiDepartment of Physiological Sciences, Faculty of Veterinary Medicine, Warsaw University of Life Sciences - SGGW, Warsaw, Poland.
Chris T EveloDepartment of Bioinformatics-BiGCaT, NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht University, Maastricht, Netherlands.
Maastricht University · NLUniversity of Jiroft · IRWarsaw University of Life Sciences · PL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Red meat is an important dietary source that provides part of the nutritional requirements. Intramuscular fat, known as marbling, is located throughout skeletal muscle. Marbling is a trait of major economic relevance that positively influences sensory quality aspects. The aim of the present study was to identify and better understand biological pathways defining marbling in beef cattle. Pathway analysis was performed in PathVisio with publicly available transcriptomic data from semitendinosus muscle of well-marbled and lean-marbled beef. Moreover, for

Indexed as

curation pathway for cowimprove breeding selectionmarblingsignaling pathwaytranscriptomics profiling

Identifiers

PMID32117419
PMCPMC7019052
OpenAlexW3005101086

What OpenQuestion holds

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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.