ReviewNature reviews. Molecular cell biology2025
Decoding the interactions and functions of non-coding RNA with artificial intelligence.
Review in Nature reviews. Molecular cell biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 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
13 citing papers in PubMed.
- Application of artificial intelligence in head and neck squamous cell carcinoma.Annals of medicine · 2026Review
- Artificial intelligence driven diet-intestinal microbiota-host health integration: A four-dimensional paradigm for advancing host wellness research.iMetaOmics · 2026Review
- GRASSP: RNA language model-enhanced graph attention with adaptive gating for RNA-small molecule binding site prediction.Bioinformatics (Oxford, England) · 2026Article
- Intron retention in health and amyotrophic lateral sclerosis.Brain : a journal of neurology · 2026Review
- Regulation of PSAT1 and PHGDH by m6A in endocrine-resistant breast cancer cells.Biochimica et biophysica acta. Molecular basis of disease · 2026Article
- Prognostic RNA-splicing archetypes in breast cancer identified by extended pre-training of histopathology foundation models.Nature communications · 2026Article
- Viral non-coding RNA structure annotation and API-based data retrieval with Rfam and R2DT.bioRxiv : the preprint server for biology · 2026Article
- The gut-heart dialogue: an epigenetic perspective on myocardial infarction.NPJ biofilms and microbiomes · 2026Review
- Review
- The Era of Large-Scale Data in Biological Sciences.Advances in experimental medicine and biology · 2026Review
- Omics landscapes in molecular mechanisms withFood chemistry. Molecular sciences · 2025Review
- RNA language model and graph attention network for RNA and small molecule binding sites prediction.Bioinformatics (Oxford, England) · 2025Article
- Mechanism of exercise-derived circulating exosomes as a target for sarcopenia management.Frontiers in physiology · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
18 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In addition to encoding proteins, mRNAs have context-specific regulatory roles that contribute to many cellular processes. However, uncovering new mRNA functions is constrained by limitations of traditional biochemical and computational methods. In this Roadmap, we highlight how artificial intelligence can transform our understanding of RNA biology by fostering collaborations between RNA biologists and computational scientists to drive innovation in this fundamental field of research. We discuss how non-coding regions of the mRNA, including introns and 5' and 3' untranslated regions, regulate the metabolism and interactomes of mRNA, and the current challenges in characterizing these regions. We further discuss large language models, which can be used to learn biologically meaningful RNA sequence representations. We also provide a detailed roadmap for integrating large language models with graph neural networks to harness publicly available sequencing and knowledge data. Adopting this roadmap will allow us to predict RNA interactions with diverse molecules and the modelling of context-specific mRNA interactomes.
Indexed as
Identifiers
40537558What 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.