Evidence map›Paper›PMID 34685867›Full record

ArticlePlants (Basel, Switzerland)2021

The Semi-Supervised Strategy of Machine Learning on the Gene Family Diversity to Unravel Resveratrol Synthesis.

Jun-Tae Song, Dong-U Woo, Yejin Lee, Sung-Hoon Choi, Yang-Jae Kang

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Plants (Basel, Switzerland), 2021. 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

5 authors.

Jun-Tae SongDivision of Bio & Medical Bigdata Department (BK4 Program), Gyeongsang National University, Jinju 52828, Korea.
Dong-U WooDivision of Bio & Medical Bigdata Department (BK4 Program), Gyeongsang National University, Jinju 52828, Korea.
Yejin LeeDivision of Bio & Medical Bigdata Department (BK4 Program), Gyeongsang National University, Jinju 52828, Korea.
Sung-Hoon ChoiDivision of Bio & Medical Bigdata Department (BK4 Program), Gyeongsang National University, Jinju 52828, Korea.
Yang-Jae KangDivision of Bio & Medical Bigdata Department (BK4 Program), Gyeongsang National University, Jinju 52828, Korea.ORCID 0000-0002-4313-7088

Funding

Cooperative Research Program for National Agricultural Genome Program PJ01347303
6 · The paper itself

Abstract

Resveratrol is a phytochemical with medicinal benefits, being well-known for its presence in wine. Plants develop resveratrol in response to stresses such as pathogen infection, UV radiation, and other mechanical stress. The recent publications of genomic sequences of resveratrol-producing plants such as grape, peanut, and eucalyptus can expand our molecular understanding of resveratrol synthesis. Based on a gene family count matrix of

Indexed as

gene family expansionmachine learningresveratrol synthesissynthetic biotechnology

Identifiers

PMID34685867
PMCPMC8538884

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.