ReviewEBioMedicine2024
Machine learning for catalysing the integration of noncoding RNA in research and clinical practice.
Review in EBioMedicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 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
17 citing papers in PubMed.
- Integration of the circulating miRNome and clinical information to predict 90-day mortality in elderly COVID-19 subphenotypes.iScience · 2026Article
- Integrative multi-omics analyses reveal nuclear noncoding RNA-mediated regulatory landscape in Alzheimer's disease.Archives of pharmacal research · 2026Article
- Predicting piRNA-Disease Associations Based on Dual-View Learning and Multi-head Self-Attention Mechanism Fusion.Interdisciplinary sciences, computational life sciences · 2026Article
- MicroRNAs in oncology: a translational perspective in the era of AI.Nature reviews. Clinical oncology · 2026Review
- Machine learning mortality prediction model for cyclosporine therapy in pediatric aplastic anemia.Annals of hematology · 2026Article
- Review
- Machine learning for extracellular vesicles enables diagnostic and therapeutic nanobiotechnology.Journal of nanobiotechnology · 2026Review
- Large Language Models for Non-Coding RNA Biomarker Discovery in Breast Cancer.Methods in molecular biology (Clifton, N.J.) · 2026Article
- Mechanisms of Action and Biomarker Potential of ncRNAs in Hepatocellular Carcinoma and Liver Fibrosis: A Review.Analytical cellular pathology (Amsterdam) · 2026Review
- CKAP2, miR-941, miR-548 and LINC02577 as biomarkers for early diagnosis in colorectal cancer.Scientific reports · 2025Article
- MicroRNA mapping of bronchial aspirate for molecular phenotyping and prognostication in patients on mechanical ventilation.Molecular therapy. Nucleic acids · 2025Article
- The European BestAgeing Study on microRNA candidates reveals distinct signatures with diagnostic and prognostic potential in cardiovascular disease.BMC medicine · 2025Article
- Computational identification and validation of non-coding rna biomarkers in gastrointestinal cancer.Functional & integrative genomics · 2025Review
- Integrating AI and RNA biomarkers in cancer: advances in diagnostics and targeted therapies.Cell communication and signaling : CCS · 2025Review
- From molecules to meaning: non-coding RNAs as biomarkers in obstructive sleep apnea.Biomarkers in medicine · 2025Article
- Circular RNA-based liquid biopsy: a promising approach for monitoring drug resistance in cancer.Cancer drug resistance (Alhambra, Calif.) · 2025Review
- Machine Learning and Mendelian Randomization Reveal Molecular Mechanisms and Causal Relationships of Immune-Related Biomarkers in Periodontitis.Mediators of inflammation · 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.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The human transcriptome predominantly consists of noncoding RNAs (ncRNAs), transcripts that do not encode proteins. The noncoding transcriptome governs a multitude of pathophysiological processes, offering a rich source of next-generation biomarkers. Toward achieving a holistic view of disease, the integration of these transcripts with clinical records and additional data from omic technologies ("multiomic" strategies) has motivated the adoption of artificial intelligence (AI) approaches. Given their intricate biological complexity, machine learning (ML) techniques are becoming a key component of ncRNA-based research. This article presents an overview of the potential and challenges associated with employing AI/ML-driven approaches to identify clinically relevant ncRNA biomarkers and to decipher ncRNA-associated pathogenetic mechanisms. Methodological and conceptual constraints are discussed, along with an exploration of ethical considerations inherent to AI applications for healthcare and research. The ultimate goal is to provide a comprehensive examination of the multifaceted landscape of this innovative field and its clinical implications.
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.