Evidence map›Paper›PMID 32032999›Full record

ArticleAntibiotics (Basel, Switzerland)2020

Predicting Antimicrobial and Other Cysteine-Rich Peptides in 1267 Plant Transcriptomes.

Andrey Shelenkov, Anna Slavokhotova, Tatyana Odintsova

Open access · goldAbstract read
In one paragraph

Article in Antibiotics (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
1.6field-weighted citation impact, top 17% 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

19 citing papers in PubMed, 24 citations in OpenAlex.

  1. Article
  2. Article
  3. Complex of Defense Polypeptides of Wheatgrass (Plants (Basel, Switzerland) · 2024
    Article
  4. Review
  5. Review
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Diversity of International High-Risk Clones ofAntibiotics (Basel, Switzerland) · 2021
    Article
  12. Article
  13. Multiple Classes of Antimicrobial Peptides inJournal of natural products · 2021
    Article
  14. Article
  15. Article
  16. Review
  17. Article
  18. Antibacterial Peptides.Antibiotics (Basel, Switzerland) · 2020
    Article
  19. 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

3 authors at 3 institutions in 1 country.

Andrey ShelenkovVavilov Institute of General Genetics, Russian Academy of Sciences, Gubkina str. 3, Moscow 119991, Russia.ORCID 0000-0002-7409-077X
Anna SlavokhotovaVavilov Institute of General Genetics, Russian Academy of Sciences, Gubkina str. 3, Moscow 119991, Russia.
Tatyana OdintsovaVavilov Institute of General Genetics, Russian Academy of Sciences, Gubkina str. 3, Moscow 119991, Russia.ORCID 0000-0002-5563-9755
Central Research Institute of Epidemiology · RURussian Academy of Sciences · RUVavilov Institute of General Genetics · RU

Funding

Russian Science Foundation 16-16-00032
6 · The paper itself

Abstract

Antimicrobial peptides (AMPs) are a key component of innate immunity in various organisms including bacteria, insects, mammals, and plants. Their mode of action decreases the probability of developing resistance in pathogenic organisms, which makes them a promising object of study. However, molecular biology methods for searching for AMPs are laborious and expensive, especially for plants. Earlier, we developed a computational pipeline for identifying potential AMPs based on the cysteine motifs they usually possess. Since most motifs are too species-specific, a wide-scale screening of novel data is required to maintain the accuracy of searching algorithms. We have performed a search for potential AMPs in 1267 plant transcriptomes using our pipeline. On average, 50-150 peptides were revealed in each transcriptome. The data was verified by a BLASTp search in nr database to confirm peptide functions and by using random nucleotide sequences to estimate the fraction of erroneous predictions. The datasets obtained will be useful both for molecular biologists investigating AMPs in various organisms and for bioinformaticians developing novel algorithms of motif searching in transcriptomic and genomic sequences. The results obtained will represent a good reference point for future investigations in the fields mentioned above.

Indexed as

antimicrobial peptidesbioinformaticsmotif searchingplant transcriptome analysis

Identifiers

PMID32032999
PMCPMC7168108
OpenAlexW2412537182

What OpenQuestion holds

Textmetadata
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.