ArticleScientific reports2020
miRNALoc: predicting miRNA subcellular localizations based on principal component scores of physico-chemical properties and pseudo compositions of di-nucleotides.
Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 14 papers.
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.
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.
Who cites it
14 citing papers in PubMed.
- Predicting circRNA subcellular localization by fusing circRNA sequence and network information.Scientific reports · 2026Article
- A comprehensive review on RNA subcellular localization prediction.Briefings in functional genomics · 2026Review
- RNALoc-LM: RNA subcellular localization prediction using pre-trained RNA language model.Bioinformatics (Oxford, England) · 2025Article
- PMiSLocMF: predicting miRNA subcellular localizations by incorporating multi-source features of miRNAs.Briefings in bioinformatics · 2024Article
- Advances in applications of artificial intelligence algorithms for cancer-related miRNA research.Zhejiang da xue xue bao. Yi xue ban = Journal of Zhejiang University. Medical sciences · 2024Review
- HormoNet: a deep learning approach for hormone-drug interaction prediction.BMC bioinformatics · 2024Article
- RNA trafficking and subcellular localization-a review of mechanisms, experimental and predictive methodologies.Briefings in bioinformatics · 2023Review
- Potential of miRNAs in Plasma Extracellular Vesicle for the Stratification of Prostate Cancer in a South African Population.Cancers · 2023Article
- Systematic analysis of different degrees of haemolysis on miRNA levels in serum and serum-derived extracellular vesicles from dogs.BMC veterinary research · 2022Article
- Circ-LocNet: A Computational Framework for Circular RNA Sub-Cellular Localization Prediction.International journal of molecular sciences · 2022Article
- EL-RMLocNet: An explainable LSTM network for RNA-associated multi-compartment localization prediction.Computational and structural biotechnology journal · 2022Article
- Prediction of RNA subcellular localization: Learning from heterogeneous data sources.iScience · 2021Review
- Advances in Computational Methodologies for Classification and Sub-Cellular Locality Prediction of Non-Coding RNAs.International journal of molecular sciences · 2021Review
- PMLocMSCAM: Predicting miRNA Subcellular Localisations by miRNA Similarities and Cross-Attention Mechanism.IET systems biologyArticle
Corrections and comments
- Erratum issued
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
MicroRNAs (miRNAs) are one kind of non-coding RNA, play vital role in regulating several physiological and developmental processes. Subcellular localization of miRNAs and their abundance in the native cell are central for maintaining physiological homeostasis. Besides, RNA silencing activity of miRNAs is also influenced by their localization and stability. Thus, development of computational method for subcellular localization prediction of miRNAs is desired. In this work, we have proposed a computational method for predicting subcellular localizations of miRNAs based on principal component scores of thermodynamic, structural properties and pseudo compositions of di-nucleotides. Prediction accuracy was analyzed following fivefold cross validation, where ~ 63-71% of AUC-ROC and ~ 69-76% of AUC-PR were observed. While evaluated with independent test set, > 50% localizations were found to be correctly predicted. Besides, the developed computational model achieved higher accuracy than the existing methods. A user-friendly prediction server "miRNALoc" is freely accessible at https://cabgrid.res.in:8080/mirnaloc/ , by which the user can predict localizations of miRNAs.
Indexed as
Identifiers
What OpenQuestion holds
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.