ArticleNature communications2023
Epitranscriptomic subtyping, visualization, and denoising by global motif visualization.
Article in Nature communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Decoding causal m6A: a bioinformatics roadmap for psychiatric disorders.Briefings in bioinformatics · 2026Review
- m6AConquer: a consistently quantified and orthogonally validated database for the N6-methyladenosine (m6A) epitranscriptome.Nucleic acids research · 2026Article
- Exploring the mFunctional & integrative genomics · 2025Article
- Bayesian optimized parameter selection for density-based clustering applied to single molecule localization microscopy.Communications biology · 2025Article
- A tango between NSUN2 and TET2: defining both the fate and origin of RNA.Science China. Life sciences · 2025Article
- Statistical modeling of single-cell epitranscriptomics enabled trajectory and regulatory inference of RNA methylation.Cell genomics · 2025Article
- Detecting a wide range of epitranscriptomic modifications using a nanopore-sequencing-based computational approach with 1D score-clustering.Nucleic acids research · 2025Article
- m6A-methylase METTL3 promotes retinal angiogenesis through modulation of metabolic reprogramming in RPE cells.Journal of neuroinflammation · 2024Article
- The role of structure in regulatory RNA elements.Bioscience reports · 2024Review
- Substrate diversity of NSUN enzymes and links of 5-methylcytosine to mRNA translation and turnover.Life science alliance · 2024Article
- Mechanisms and clinical landscape of N6-methyladenosine (m6A) RNA modification in gastrointestinal tract cancers.Molecular and cellular biochemistry · 2024Review
- TheRNA (New York, N.Y.) · 2024Article
- The Quiet Giant: Identification, Effectors, Molecular Mechanism, Physiological and Pathological Function in mRNA 5-methylcytosine Modification.International journal of biological sciences · 2024Review
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Advances in sequencing technologies have empowered epitranscriptomic profiling at the single-base resolution. Putative RNA modification sites identified from a single high-throughput experiment may contain one type of modification deposited by different writers or different types of modifications, along with false positive results because of the challenge of distinguishing signals from noise. However, current tools are insufficient for subtyping, visualization, and denoising these signals. Here, we present iMVP, which is an interactive framework for epitranscriptomic analysis with a nonlinear dimension reduction technique and density-based partition. As exemplified by the analysis of mRNA m
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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.