ArticleNature communications2018
A computational framework to study sub-cellular RNA localization.
Article in Nature communications, 2018. 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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Who cites it
41 citing papers in PubMed, 73 citations in OpenAlex.
- Single-cell profiling reveals pervasive heterogeneity in subcellular RNA localization.bioRxiv : the preprint server for biology · 2026Article
- A comprehensive review on RNA subcellular localization prediction.Briefings in functional genomics · 2026Review
- Chemical inhibition of exon junction complex assembly impairs mRNA localization and neural stem cells ciliogenesis.Nucleic acids research · 2025Article
- Decoding the interactions and functions of non-coding RNA with artificial intelligence.Nature reviews. Molecular cell biology · 2025Review
- Regulated localization of transposable element RNA during influenza A virus infection.EMBO reports · 2025Article
- LncRNA Subcellular Localization Across Diverse Cell Lines: An Exploration Using Deep Learning with InexactNon-coding RNA · 2025Article
- Incorporating spatial diffusion into models of bursty stochastic transcription.Journal of the Royal Society, Interface · 2025Article
- Geospatially informed representation of spatial genomics data with SpatialFeatureExperiment.bioRxiv : the preprint server for biology · 2025Article
- Statistical analysis supports pervasive RNA subcellular localization and alternative 3' UTR regulation.eLife · 2024Article
- Spatial omics advances for in situ RNA biology.Molecular cell · 2024Review
- A systematic evaluation of computational methods for cell segmentation.bioRxiv : the preprint server for biology · 2024Article
- A systematic evaluation of computational methods for cell segmentation.Briefings in bioinformatics · 2024Article
- Bento: a toolkit for subcellular analysis of spatial transcriptomics data.Genome biology · 2024Article
- The therapeutically actionable long non-coding RNA 'T-RECS' is essential to cancer cells' survival in NRAS/MAPK-driven melanoma.Molecular cancer · 2024Article
- The therapeutically actionable long non-coding RNA 'Research square · 2023Article
- Pairwise biosynthesis of ion channels stabilizes excitability and mitigates arrhythmias.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
- RNA trafficking and subcellular localization-a review of mechanisms, experimental and predictive methodologies.Briefings in bioinformatics · 2023Review
- Subcellular spatially resolved gene neighborhood networks in single cells.Cell reports methods · 2023Article
- Transcripts of the Prostate Cancer-Associated GeneInternational journal of molecular sciences · 2023Article
- Visualizing and Quantifying mRNA Localization at the Invasive Front of 3D Cancer Spheroids.Methods in molecular biology (Clifton, N.J.) · 2023Article
Corrections and comments
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Authors and funding
10 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
RNA localization is a crucial process for cellular function and can be quantitatively studied by single molecule FISH (smFISH). Here, we present an integrated analysis framework to analyze sub-cellular RNA localization. Using simulated images, we design and validate a set of features describing different RNA localization patterns including polarized distribution, accumulation in cell extensions or foci, at the cell membrane or nuclear envelope. These features are largely invariant to RNA levels, work in multiple cell lines, and can measure localization strength in perturbation experiments. Most importantly, they allow classification by supervised and unsupervised learning at unprecedented accuracy. We successfully validate our approach on representative experimental data. This analysis reveals a surprisingly high degree of localization heterogeneity at the single cell level, indicating a dynamic and plastic nature of RNA localization.
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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 OpenQuestion graph.