ReviewExperimental & molecular medicine2024
Big data and deep learning for RNA biology.
Review in Experimental & molecular medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers, 1 of them a synthesis that pooled it.
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
32 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Deep learning in single-cell and spatial transcriptomics data analysis: advances and challenges from a data science perspective.Briefings in bioinformatics · 2025Pooled it
- TIMEL: Deep learning-statistical integration reveals spatial stromal and immune signatures of aggressive colon cancer.Journal of pathology informatics · 2026Article
- K-attention: a biologically informed attention operator for data-efficient sequence-based omics modeling.Briefings in bioinformatics · 2026Article
- Artificial intelligence in biologic drug discovery: A review of methodological evolution and therapeutic applications.Acta pharmaceutica Sinica. B · 2026Review
- The Use of Deep Learning in RNA Therapeutic Development.ACS nano · 2026Review
- scMEDAL: interpretable single-cell transcriptomics analysis with batch effect visualization via deep mixed-effects autoencoder.Nature communications · 2026Article
- Harnessing Deep Learning Models for Guide RNA Optimization and Off-Target Prediction in CRISPR Systems.Biotechnology journal · 2026Review
- A novel NLP-based method and algorithm to discover RNA-binding protein (RBP) motifs, contexts, binding preferences, and interactions.RNA (New York, N.Y.) · 2026Article
- RNA-binding proteins and ribonucleoproteins as determinants of immunity.Nature reviews. Immunology · 2026Review
- Machine learning-based integration of transcriptome and digital pathology for predicting chemoresistance in muscle-invasive bladder cancer.Experimental & molecular medicine · 2026Article
- Integrating single-cell and single-nucleus datasets improves bulk RNA-seq deconvolution.Cell reports methods · 2026Article
- GRIP-Lung: Generative Model of Response to Drug-Induced Perturbation in Lung Cancer.International journal of molecular sciences · 2026Article
- Design and evaluation of semantically-valid negative samples integration techniques for scalable semi-automated drug repurposing prediction pipelines in rare disease research.BMC bioinformatics · 2026Article
- AI-Based Prediction of Gene Expression in Single-Cell and Multiscale Genomics and Transcriptomics.International journal of molecular sciences · 2026Review
- Identifying potential biomarkers for type 2 diabetes in the adipose tissue of older adults via multiple machine learning algorithms.Scientific reports · 2025Article
- From nucleotides to numbers: a comprehensive review of RNA feature extraction methods for computational modelling.Briefings in bioinformatics · 2025Review
- Interpretation of RNA Universe and Coding Potential Using IntRNA.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- ResNet50 and Single-Cell Multi-Omics analysis identify key cellular and molecular features in pediatric acute lymphoblastic leukemia.Annals of hematology · 2025Article
- Bioinformatics and machine learning reveal novel prognostic biomarkers in head and neck squamous cell carcinoma.Journal of applied genetics · 2025Article
- PAL-AI reveals genetic determinants that control poly(A)-tail length during oocyte maturation, with relevance to human fertility.Nature communications · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
The exponential growth of big data in RNA biology (RB) has led to the development of deep learning (DL) models that have driven crucial discoveries. As constantly evidenced by DL studies in other fields, the successful implementation of DL in RB depends heavily on the effective utilization of large-scale datasets from public databases. In achieving this goal, data encoding methods, learning algorithms, and techniques that align well with biological domain knowledge have played pivotal roles. In this review, we provide guiding principles for applying these DL concepts to various problems in RB by demonstrating successful examples and associated methodologies. We also discuss the remaining challenges in developing DL models for RB and suggest strategies to overcome these challenges. Overall, this review aims to illuminate the compelling potential of DL for RB and ways to apply this powerful technology to investigate the intriguing biology of RNA more effectively.
Indexed as
Identifiers
What 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.