ArticleNature communications2025
ERNIE-RNA: an RNA language model with structure-enhanced representations.
Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.
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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.
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Who cites it
25 citing papers in PubMed.
- AI foundation models for RNA biology.RNA biology · 2026Review
- Accurate RNA-Ligand Binding Site Prediction Based on a Multi-Channel Graph Neural Network.Interdisciplinary sciences, computational life sciences · 2026Article
- From rules to foundation models: a comprehensive review of machine learning approaches for siRNA design.NAR genomics and bioinformatics · 2026Review
- GRASSP: RNA language model-enhanced graph attention with adaptive gating for RNA-small molecule binding site prediction.Bioinformatics (Oxford, England) · 2026Article
- A token-pruning framework enables efficient representation of the human genome for RNA modification analysis.Bioinformatics (Oxford, England) · 2026Article
- RNA-Lexis: a probabilistic algorithm using a non-parametric segmentation logic to detect meaningful sequences in RNA.Nucleic acids research · 2026Article
- Intron retention in health and amyotrophic lateral sclerosis.Brain : a journal of neurology · 2026Review
- Machine Learning for RNA-Targeting Drug Design.Journal of chemical information and modeling · 2026Review
- Advancing bioinformatics with language models: components, applications, and perspectives.Briefings in bioinformatics · 2026Review
- Machine Learning for CRISPR-Based Diagnostics.International journal of molecular sciences · 2026Review
- Applications of large-scale artificial intelligence models in bioinformatics.Quantitative biology (Beijing, China) · 2026Review
- Detecting and quantifying overparametrization in RNA language models with REDIAL.bioRxiv : the preprint server for biology · 2026Article
- Augmented prediction of multi-species protein-RNA interactions using evolutionary conservation of RNA-binding proteins.Nature communications · 2026Article
- Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning.Briefings in bioinformatics · 2026Article
- The DNA dialect: a comprehensive guide to pretrained genomic language models.Molecular systems biology · 2026Review
- CoBRA: compound binding site prediction using RNA language model.Briefings in bioinformatics · 2026Article
- Unlocking the undruggable spliceosome: generative AI and structural dynamics in cancer therapy.Frontiers in cell and developmental biology · 2026Review
- mRNABERT: advancing mRNA sequence design with a universal language model and comprehensive dataset.Nature communications · 2025Article
- HydraRNA: a hybrid architecture based full-length RNA language model.Genome biology · 2025Article
- Advances in Methods for Accurate Prediction of RNA-Small Molecule Binding Sites: From Isolated to AI-Integrated Strategies.Pharmaceuticals (Basel, Switzerland) · 2025Review
Corrections and comments
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Authors and funding
11 authors.
Funding
Abstract
Existing RNA language models (RLMs) largely overlook structural information in RNA sequences, leading to incomplete feature extraction and suboptimal performance on downstream tasks. In this study, we present ERNIE-RNA (Enhanced Representations with Base-Pairing Restriction for RNA Modeling), an RNA pre-trained language model based on a modified BERT (Bidirectional Encoder Representations from Transformers). Notably, ERNIE-RNA's attention maps exhibit superior ability to capture RNA structural features through zero-shot prediction, outperforming conventional methods like RNAfold and RNAstructure, suggesting that ERNIE-RNA naturally develops comprehensive representations of RNA architecture during pre-training. Moreover, after fine-tuning, ERNIE-RNA achieves state-of-the-art (SOTA) performance across various downstream tasks, including RNA structure and function predictions. In summary, ERNIE-RNA provides versatile features that can be effectively applied to a wide range of research tasks. Our findings highlight that integrating key knowledge-based priors into the BERT framework may enhance the performance of other language models.
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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 Socratic graph.