ArticleGenes2021
PlantMirP2: An Accurate, Fast and Easy-To-Use Program for Plant Pre-miRNA and miRNA Prediction.
Article in Genes, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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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.
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Who cites it
6 citing papers in PubMed.
- Application of Artificial Intelligence Technology in Plant MicroRNA Research: Progress, Challenges, and Prospects.International journal of molecular sciences · 2025Review
- Role of non-coding RNAs in quality improvement of horticultural crops: computational tools, databases, and algorithms for identification and analysis.Functional & integrative genomics · 2025Review
- AmiR-P3: An AI-based microRNA prediction pipeline in plants.PloS one · 2024Article
- CNNLSTMac4CPred: A Hybrid Model for N4-Acetylcytidine Prediction.Interdisciplinary sciences, computational life sciences · 2022Article
- The Multiverse of Plant Small RNAs: How Can We Explore It?International journal of molecular sciences · 2022Review
- Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
MicroRNAs (miRNAs) are a kind of short non-coding ribonucleic acid molecules that can regulate gene expression. The computational identification of plant miRNAs is of great significance to understanding biological functions. In our previous studies, we have put firstly forward and further developed a set of knowledge-based energy features to construct two plant pre-miRNA prediction tools (plantMirP and riceMirP). However, these two tools cannot be used for miRNA prediction from NGS (Next-Generation Sequencing) data. In addition, for further improving the prediction performance and accessibility, plantMirP2 has been developed. Based on the latest dataset, plantMirP2 achieves a promising performance: 0.9968 (Area Under Curve, AUC), 0.9754 (accuracy), 0.9675 (sensitivity) and 0.9876 (specificity). Additionally, the comparisons with other plant pre-miRNA tools show that plantMirP2 performs better. Finally, the webserver and stand-alone version of plantMirP2 are available.
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Registered trials
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.