ArticleScientific reports2022
A deep learning method for miRNA/isomiR target detection.
Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- The Hidden Layer of MicroRNA Regulation in Gynecologic Cancers: IsomiRs, Arm Switching, and RNA Epitranscriptomic Modifications.International journal of molecular sciences · 2026Review
- Serum EV-Derived rno-let-7b-5p Is Associated with Lung-Adipose Alterations in Allergic Asthma.International journal of molecular sciences · 2026Article
- rbpCNN: a biophysics-informed deep learning model for predicting piRNA and mRNA interactions.Scientific reports · 2026Article
- Predicting miRNA Targets at the isomiR Level.Methods in molecular biology (Clifton, N.J.) · 2026Article
- New characteristics of MiRNA and IsomiR interactions with mRNA.Scientific reports · 2025Article
- Utilizing RNA-seq data in monotone iterative generalized linear model to elevate prior knowledge quality of the circRNA-miRNA-mRNA regulatory axis.BMC bioinformatics · 2025Article
- A deep learning method to integrate extracelluar miRNA with mRNA for cancer studies.Bioinformatics (Oxford, England) · 2024Article
- Synthesis and Regulation of miRNA, Its Role in Oncogenesis, and Its Association with Colorectal Cancer Progression, Diagnosis, and Prognosis.Diagnostics (Basel, Switzerland) · 2024Review
- Empowering prediction of miRNA-mRNA interactions in species with limited training data through transfer learning.Heliyon · 2024Article
- Exploring miRNA-target gene pair detection in disease with coRmiT.Briefings in bioinformatics · 2024Article
- A computational modeling of pri-miRNA expression.PloS one · 2024Article
- MicroRNA Transcriptomes Reveal Prevalence of Rare and Species-Specific Arm Switching Events During Zebrafish Ontogenesis.Evolutionary bioinformatics online · 2024Article
- Using Attribution Sequence Alignment to Interpret Deep Learning Models for miRNA Binding Site Prediction.Biology · 2023Article
- Determinants of Functional MicroRNA Targeting.Molecules and cells · 2023Review
- Review
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Accurate identification of microRNA (miRNA) targets at base-pair resolution has been an open problem for over a decade. The recent discovery of miRNA isoforms (isomiRs) adds more complexity to this problem. Despite the existence of many methods, none considers isomiRs, and their performance is still suboptimal. We hypothesize that by taking the isomiR-mRNA interactions into account and applying a deep learning model to study miRNA-mRNA interaction features, we may improve the accuracy of miRNA target predictions. We developed a deep learning tool called DMISO to capture the intricate features of miRNA/isomiR-mRNA interactions. Based on tenfold cross-validation, DMISO showed high precision (95%) and recall (90%). Evaluated on three independent datasets, DMISO had superior performance to five tools, including three popular conventional tools and two recently developed deep learning-based tools. By applying two popular feature interpretation strategies, we demonstrated the importance of the miRNA regions other than their seeds and the potential contribution of the RNA-binding motifs within miRNAs/isomiRs and mRNAs to the miRNA/isomiR-mRNA interactions.
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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 Socratic graph.