ArticleNucleic acids research2020
mRNALoc: a novel machine-learning based in-silico tool to predict mRNA subcellular localization.
Article in Nucleic acids research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers.
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41 citing papers in PubMed, 74 citations in OpenAlex.
- Predicting membrane protein localization by deep learning on structure and chemistry.Protein science : a publication of the Protein Society · 2026Article
- Graph-based RNA structural representation reveals determinants of subcellular localization.Briefings in bioinformatics · 2026Article
- mRNALocator-imb: an imbalance-tolerant ensemble framework integrating random forest and transformer for mRNA subcellular localization prediction.Frontiers in genetics · 2026Article
- Decoding the interactions and functions of non-coding RNA with artificial intelligence.Nature reviews. Molecular cell biology · 2025Review
- mRNABench: A curated benchmark for mature mRNA property and function prediction.bioRxiv : the preprint server for biology · 2025Article
- LOCAS: multilabel mRNA localization with supervised contrastive learning.Briefings in bioinformatics · 2025Article
- LncRNA Subcellular Localization Across Diverse Cell Lines: An Exploration Using Deep Learning with InexactNon-coding RNA · 2025Article
- LGLoc as a new language model-driven graph neural network for mRNA localization.Scientific reports · 2025Article
- Article
- RNALoc-LM: RNA subcellular localization prediction using pre-trained RNA language model.Bioinformatics (Oxford, England) · 2025Article
- EDCLoc: a prediction model for mRNA subcellular localization using improved focal loss to address multi-label class imbalance.BMC genomics · 2024Article
- Deciphering 3'UTR Mediated Gene Regulation Using Interpretable Deep Representation Learning.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Article
- Guidelines for mitochondrial RNA analysis.Molecular therapy. Nucleic acids · 2024Review
- DRpred: A Novel Deep Learning-Based Predictor for Multi-Label mRNA Subcellular Localization Prediction by Incorporating Bayesian Inferred Prior Label Relationships.Biomolecules · 2024Article
- Identification of hub modules and therapeutic targets associated with CD8Scientific reports · 2024Article
- Advancing mRNA subcellular localization prediction with graph neural network and RNA structure.Bioinformatics (Oxford, England) · 2024Article
- Challenges in LncRNA Biology: Views and Opinions.Non-coding RNA · 2024Article
- mRCat: A Novel CatBoost Predictor for the Binary Classification of mRNA Subcellular Localization by Fusing Large Language Model Representation and Sequence Features.Biomolecules · 2024Article
- Expanding roles of circRNAs in cardiovascular diseases.Non-coding RNA research · 2024Review
- Optimization of FFPE preparation and identification of gene attributes associated with RNA degradation.NAR genomics and bioinformatics · 2024Article
Corrections and comments
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Recent evidences suggest that the localization of mRNAs near the subcellular compartment of the translated proteins is a more robust cellular tool, which optimizes protein expression, post-transcriptionally. Retention of mRNA in the nucleus can regulate the amount of protein translated from each mRNA, thus allowing a tight temporal regulation of translation or buffering of protein levels from bursty transcription. Besides, mRNA localization performs a variety of additional roles like long-distance signaling, facilitating assembly of protein complexes and coordination of developmental processes. Here, we describe a novel machine-learning based tool, mRNALoc, to predict five sub-cellular locations of eukaryotic mRNAs using cDNA/mRNA sequences. During five fold cross-validations, the maximum overall accuracy was 65.19, 75.36, 67.10, 99.70 and 73.59% for the extracellular region, endoplasmic reticulum, cytoplasm, mitochondria, and nucleus, respectively. Assessment on independent datasets revealed the prediction accuracies of 58.10, 69.23, 64.55, 96.88 and 69.35% for extracellular region, endoplasmic reticulum, cytoplasm, mitochondria, and nucleus, respectively. The corresponding values of AUC were 0.76, 0.75, 0.70, 0.98 and 0.74 for the extracellular region, endoplasmic reticulum, cytoplasm, mitochondria, and nucleus, respectively. The mRNALoc standalone software and web-server are freely available for academic use under GNU GPL at http://proteininformatics.org/mkumar/mrnaloc.
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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.