Evidence map›Paper›PMID 40380053›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2025

Prediction of miRNA Targets in Plants.

Shree P Pandey, Priyanka Pandey, Prashant K Srivastava

Abstract read
PubMed Publisher
In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2025. 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. 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

3 authors.

Shree P Pandey *College of Pastoral Agriculture Science and Technology, Lanzhou University, Lanzhou, China. shreepp@lzu.edu.cn.
Priyanka Pandey *College of Pastoral Agriculture Science and Technology, Lanzhou University, Lanzhou, China.
Prashant K SrivastavaNational Heart and Lung Institute, Imperial College, London, UK. prashant.srivastava@imperial.ac.uk.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

MicroRNAs (miRNAs) are the central component of an important layer of post-transcriptional regulation of gene expression. In plants, miRNAs target the transcripts in a manner that is generally highly sequence complementary. Extensive research is being made to study the genome-wide miRNA-mediated regulation of gene expression, which has resulted in the development of many tools for an in-silico prediction of miRNA targets. Although several tools have been developed for predicting miRNA targets in model plants, genome-wide analysis of miRNA targets is still a challenge for non-model species that lack dedicated tools. Here, we describe a computational procedure for studying miRNA-mediated interactions in plants, which is based on the fact that canonical miRNA target sites are highly complementary, the miRNAs negatively regulate the expression of their target genes and that miRNAs may form regulatory networks as one miRNA may target more than one transcript and vice-versa to modulate and fine-tune expression of the genome.

Indexed as

Computational BiologyMicroRNAsPlantsRNA, PlantGene Expression Regulation, PlantGene Regulatory NetworksSoftwareMicroRNAsRNA, PlantmiRNA, Target prediction, Genome-wide analysis, Next-generation sequencing, NGS, network analysis

Identifiers

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.