ArticleNature communications2023
Dynamic characterization and interpretation for protein-RNA interactions across diverse cellular conditions using HDRNet.
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 28 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
28 citing papers in PubMed, 41 citations in OpenAlex.
- Review
- Breeding 5.0: Artificial intelligence (AI)-decoded germplasm for accelerated crop innovation.Journal of integrative plant biology · 2026Article
- K-attention: a biologically informed attention operator for data-efficient sequence-based omics modeling.Briefings in bioinformatics · 2026Article
- Post-transcriptional regulatory networks: The dynamic interplay of RNA-binding proteins.The FEBS journal · 2026Review
- Bridging sequence-structure motifs and genetic variants for genome-wide dynamic RNA-protein interaction profiling.Nature communications · 2026Article
- Accessibility in proteins and RNAs interactions prediction with machine learning: are we overlooking non-experts?Briefings in bioinformatics · 2026Review
- Augmented prediction of multi-species protein-RNA interactions using evolutionary conservation of RNA-binding proteins.Nature communications · 2026Article
- PRIME-BSPre: a genome-wide protein-RNA binding sites prediction method based on templates.BMC genomics · 2026Article
- Sequence-Based Models for RNA-Protein Interactions Imputation Might Be Insufficient for Novel Signal Prediction in eCLIP Data.International journal of molecular sciences · 2026Article
- Interpretation of RNA Universe and Coding Potential Using IntRNA.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- diPaRIS: Dynamic and Interpretable Protein-RNA Interactions Prediction With U-Shaped Network and Novel Structure Encoding.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Decoding the interactions and functions of non-coding RNA with artificial intelligence.Nature reviews. Molecular cell biology · 2025Review
- PaRPI predicts RNA-Protein interactions from cross-protocol and cross-batch RNA-binding protein datasets.Communications biology · 2025Article
- Base-resolution binding profile prediction of proteins on RNAs with deep learning.Nucleic acids research · 2025Article
- LncRNA-Protein Interactions: A Key to Deciphering LncRNA Mechanisms.Biomolecules · 2025Review
- Decoding RNA-Protein Interactions: Methodological Advances and Emerging Challenges.Advanced genetics (Hoboken, N.J.) · 2025Review
- RBPsuite 2.0: an updated RNA-protein binding site prediction suite with high coverage on species and proteins based on deep learning.BMC biology · 2025Article
- From computational models of the splicing code to regulatory mechanisms and therapeutic implications.Nature reviews. Genetics · 2025Review
- A deep learning model for characterizing protein-RNA interactions from sequences at single-base resolution.Patterns (New York, N.Y.) · 2025Article
- EnrichRBP: an automated and interpretable computational platform for predicting and analysing RNA-binding protein events.Bioinformatics (Oxford, England) · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 5 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
RNA-binding proteins play crucial roles in the regulation of gene expression, and understanding the interactions between RNAs and RBPs in distinct cellular conditions forms the basis for comprehending the underlying RNA function. However, current computational methods pose challenges to the cross-prediction of RNA-protein binding events across diverse cell lines and tissue contexts. Here, we develop HDRNet, an end-to-end deep learning-based framework to precisely predict dynamic RBP binding events under diverse cellular conditions. Our results demonstrate that HDRNet can accurately and efficiently identify binding sites, particularly for dynamic prediction, outperforming other state-of-the-art models on 261 linear RNA datasets from both eCLIP and CLIP-seq, supplemented with additional tissue data. Moreover, we conduct motif and interpretation analyses to provide fresh insights into the pathological mechanisms underlying RNA-RBP interactions from various perspectives. Our functional genomic analysis further explores the gene-human disease associations, uncovering previously uncharacterized observations for a broad range of genetic disorders.
Indexed as
Identifiers
What Socratic 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 Socratic graph.