Evidence map›Paper›PMID 38019422›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2024

Bioinformatics Methods for Prediction of Gene Families Encoding Extracellular Peptides.

Loup Tran Van Canh, Sébastien Aubourg

Open access · greenAbstract read
PubMed Publisher
In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2024. 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
2.5field-weighted citation impact, top 9% 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

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. SPlant biotechnology journal · 2026
    Article
  2. 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

2 authors at 2 institutions in 1 country.

Loup Tran Van CanhInstitut Agro, INRAE, IRHS, SFR QUASAV, Université d'Angers, Angers, France.
Sébastien AubourgInstitut Agro, INRAE, IRHS, SFR QUASAV, Université d'Angers, Angers, France.
Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement · FRUniversité d'Angers · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Genes encoding small secreted peptides are widely distributed among plant genomes but their detection and annotation remains challenging. The bioinformatics protocol described here aims to identify as exhaustively as possible secreted peptide precursors belonging to a family of interest. First, homology searches are performed at the protein and genome levels. Next, multiple sequence alignments and predictions of a secretion signal are used to define a set of homologous proteins sharing features of secreted peptide precursors. These protein sequences are then used as input of motif detection and profile-based tools to build representative matrices and profiles that are used iteratively as guides to scan again the proteome and genome until family completion.

Indexed as

Computational BiologyPeptidesAmino Acid SequenceBiological TransportGenome, PlantPeptidesConserved motifData miningPhytocytokinePIPSCOOPSecretion signal

Identifiers

PMID38019422
OpenAlexW4389146750

What OpenQuestion holds

Textmetadata
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.