ReviewFrontiers in molecular biosciences2021
Artificial Intelligence in Epigenetic Studies: Shedding Light on Rare Diseases.
Review in Frontiers in molecular biosciences, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 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
20 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Pooled it
- Critical review of artificial intelligence in synthetic biology: DBTL cycle applications, challenges, and design rules for microbial strain engineering.World journal of microbiology & biotechnology · 2026Review
- Epigenetic Alterations Induced by Smoking and Their Intersection with Artificial Intelligence: A Narrative Review.International journal of environmental research and public health · 2025Review
- Epigenetics of Endometrial Cancer: The Role of Chromatin Modifications and Medicolegal Implications.International journal of molecular sciences · 2025Review
- Review
- Convergence of evolving artificial intelligence and machine learning techniques in precision oncology.NPJ digital medicine · 2025Article
- The Use of AI for Phenotype-Genotype Mapping.Methods in molecular biology (Clifton, N.J.) · 2025Article
- Circulating Tumor DNA in Cervical Cancer: Clinical Utility and Medico-Legal Perspectives.Oncology research · 2025Review
- Expanding Upon Genomics in Rare Diseases: Epigenomic Insights.International journal of molecular sciences · 2024Review
- The Value of Smartwatches in the Health Care Sector for Monitoring, Nudging, and Predicting: Viewpoint on 25 Years of Research.Journal of medical Internet research · 2024Review
- Epigenetics in thyroid cancer: a bibliometric analysis.Endocrine connections · 2024Article
- Designing Epigenome Editors: Considerations of Biochemical and Locus Specificities.Methods in molecular biology (Clifton, N.J.) · 2024Article
- The Potential for Artificial Intelligence Applied to Epigenetics.Mayo Clinic proceedings. Digital health · 2023Article
- Artificial intelligence in rare disease diagnosis and treatment.Clinical and translational science · 2023Review
- Predicting Duodenal Cancer Risk in Patients with Familial Adenomatous Polyposis Using Machine Learning Model.The Turkish journal of gastroenterology : the official journal of Turkish Society of Gastroenterology · 2023Article
- Epigenomic signatures reveal mechanistic clues and predictive markers for autism spectrum disorder.Molecular psychiatry · 2023Review
- Scoping review and classification of deep learning in medical genetics.Genetics in medicine : official journal of the American College of Medical Genetics · 2022Article
- Predicting High Blood Pressure Using DNA Methylome-Based Machine Learning Models.Biomedicines · 2022Article
- Deep Learning for Human Disease Detection, Subtype Classification, and Treatment Response Prediction Using Epigenomic Data.Biomedicines · 2021Review
- Analyzing Modern Biomolecules: The Revolution of Nucleic-Acid Sequencing - Review.Biomolecules · 2021Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
More than 7,000 rare diseases (RDs) exist worldwide, affecting approximately 350 million people, out of which only 5% have treatment. The development of novel genome sequencing techniques has accelerated the discovery and diagnosis in RDs. However, most patients remain undiagnosed. Epigenetics has emerged as a promise for diagnosis and therapies in common disorders (e.g., cancer) with several epimarkers and epidrugs already approved and used in clinical practice. Hence, it may also become an opportunity to uncover new disease mechanisms and therapeutic targets in RDs. In this "big data" age, the amount of information generated, collected, and managed in (bio)medicine is increasing, leading to the need for its rapid and efficient collection, analysis, and characterization. Artificial intelligence (AI), particularly deep learning, is already being successfully applied to analyze genomic information in basic research, diagnosis, and drug discovery and is gaining momentum in the epigenetic field. The application of deep learning to epigenomic studies in RDs could significantly boost discovery and therapy development. This review aims to collect and summarize the application of AI tools in the epigenomic field of RDs. The lower number of studies found, specific for RDs, indicate that this is a field open to expansion, following the results obtained for other more common disorders.
Indexed as
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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.