Evidence map›Paper›PMID 28377776›Full record

ArticleFrontiers in plant science2017

isomiR2Function: An Integrated Workflow for Identifying MicroRNA Variants in Plants.

Kun Yang, Gaurav Sablok, Guang Qiao, Qiong Nie, Xiaopeng Wen

Open access · goldAbstract read
In one paragraph

Article in Frontiers in plant science, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
6.1field-weighted citation impact, top 5% 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

14 citing papers in PubMed, 24 citations in OpenAlex.

  1. Prediction of miRNA Targets in Plants.Methods in molecular biology (Clifton, N.J.) · 2025
    Article
  2. An Overview of miRNA and miRNA Target Analysis Tools.Methods in molecular biology (Clifton, N.J.) · 2025
    Review
  3. athisomiRDB: A comprehensive database of Arabidopsis isomiRs.Database : the journal of biological databases and curation · 2024
    Article
  4. Article
  5. Article
  6. Review
  7. The Multiverse of Plant Small RNAs: How Can We Explore It?International journal of molecular sciences · 2022
    Review
  8. Review
  9. Article
  10. MicroRNAs Regulating Autophagy in Neurodegeneration.Advances in experimental medicine and biology · 2021
    Article
  11. Review
  12. Article
  13. Review
  14. 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

5 authors at 2 institutions in 2 countries.

Kun YangKey Laboratory of Plant Resources Conservation and Germplasm Innovation in Mountainous Region - Ministry of Education, Institute of Agro-bioengineering, Guizhou UniversityGuiyang, China; College of Life Sciences, Guizhou UniversityGuiyang, China.
Gaurav SablokClimate Change Cluster (C3), University of Technology Sydney Sydney, NSW, Australia.
Guang QiaoKey Laboratory of Plant Resources Conservation and Germplasm Innovation in Mountainous Region - Ministry of Education, Institute of Agro-bioengineering, Guizhou UniversityGuiyang, China; College of Life Sciences, Guizhou UniversityGuiyang, China.
Qiong NieKey Laboratory of Plant Resources Conservation and Germplasm Innovation in Mountainous Region - Ministry of Education, Institute of Agro-bioengineering, Guizhou UniversityGuiyang, China; College of Life Sciences, Guizhou UniversityGuiyang, China.
Xiaopeng WenKey Laboratory of Plant Resources Conservation and Germplasm Innovation in Mountainous Region - Ministry of Education, Institute of Agro-bioengineering, Guizhou UniversityGuiyang, China; College of Life Sciences, Guizhou UniversityGuiyang, China.
Guizhou University · CNUniversity of Technology Sydney · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In plants, post transcriptional regulation by non-coding RNAs (ncRNAs), in particular miRNAs (19-24 nt) has been involved in modulating the transcriptional landscape in developmental, biotic and abiotic interactions. In past few years, considerable focus has been leveraged on delineating and deciphering the role of miRNAs and their canonical isomiRs in plants. However, proper classification and accurate prediction of plant isomiRs taking into account the relative features by which we define isomiRs, such as templated or non-templated is still lacking. In the present research, we present isomiR2Function, a standalone easily deployable tool that allows for the robust and high-throughput discovery of templated and non-templated isomiRs. Additionally, isomiR2Function allows for identification of differentially expressed isomiRs and in parallel target prediction based on both transcripts or PARE-Seq either using Targetfinder or Cleaveland. isomiR2Function allows for the functional enrichment of the detected targets using TopGO package. Benchmarking of isomiR2Function revealed highly accurate prediction and classification of isomiRs as compared to the previously developed isomiR prediction tools. Additionally, the downstream implementation of additional features allows isomiR2Function to be classified as a single standalone tool for isomiR profiling from discovery to functional roles. All in all, isomiR2Function allows the streamline processing of the miRNA-seq for the identification and characterization of isomiRs with minimal efforts. isomiR2Function can be accessed through: https://github.com/347033139/isomiR2Function.

Indexed as

functional profilingisomiRsmiRNAsPARE-seqplantspost-transcriptional machinery

Identifiers

PMID28377776
PMCPMC5359237
OpenAlexW2601736435

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.