AIMC Topic: CpG Islands
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Deciphering dysregulation and CpG methylation in hepatocellular carcinoma using multi-omics and machine learning.
Epigenomics
Jul 29, 2024
This study investigates the altered expression and CpG methylation patterns of histone demethylase in hepatocellular carcinoma (HCC), aiming to uncover insights and promising diagnostics biomarkers. Leveraging TCGA-LIHC multi-omics data, we employe...
Decoding depression: a comprehensive multi-cohort exploration of blood DNA methylation using machine learning and deep learning approaches.
Translational psychiatry
Jul 15, 2024
The causes of depression are complex, and the current diagnosis methods rely solely on psychiatric evaluations with no incorporation of laboratory biomarkers in clinical practices. We investigated the stability of blood DNA methylation depression sig...
Image-based deep learning model using DNA methylation data predicts the origin of cancer of unknown primary.
Neoplasia (New York, N.Y.)
Jun 28, 2024
Cancer of unknown primary (CUP) is a rare type of metastatic cancer in which the origin of the tumor is unknown. Since the treatment strategy for patients with metastatic tumors depends on knowing the primary site, accurate identification of the orig...
Prediction of DNA methylation-based tumor types from histopathology in central nervous system tumors with deep learning.
Nature medicine
May 17, 2024
Precision in the diagnosis of diverse central nervous system (CNS) tumor types is crucial for optimal treatment. DNA methylation profiles, which capture the methylation status of thousands of individual CpG sites, are state-of-the-art data-driven mea...
Machine learning unveils an immune-related DNA methylation profile in germline DNA from breast cancer patients.
Clinical epigenetics
May 15, 2024
BACKGROUND: There is an unmet need for precise biomarkers for early non-invasive breast cancer detection. Here, we aimed to identify blood-based DNA methylation biomarkers that are associated with breast cancer.
Deep learning predicts DNA methylation regulatory variants in the human brain and elucidates the genetics of psychiatric disorders.
Proceedings of the National Academy of Sciences of the United States of America
Aug 15, 2022
There is growing evidence for the role of DNA methylation (DNAm) quantitative trait loci (mQTLs) in the genetics of complex traits, including psychiatric disorders. However, due to extensive linkage disequilibrium (LD) of the genome, it is challengin...
Artificial intelligence and leukocyte epigenomics: Evaluation and prediction of late-onset Alzheimer's disease.
PloS one
Mar 31, 2021
We evaluated the utility of leucocyte epigenomic-biomarkers for Alzheimer's Disease (AD) detection and elucidates its molecular pathogeneses. Genome-wide DNA methylation analysis was performed using the Infinium MethylationEPIC BeadChip array in 24 l...
Machine learning analysis of DNA methylation in a hypoxia-immune model of oral squamous cell carcinoma.
International immunopharmacology
Oct 19, 2020
BACKGROUND: Hypoxia status and immunity are related with the development and prognosis of oral squamous cell carcinoma (OSCC). Here, we constructed a hypoxia-immune model to explore its upstream mechanism and identify potential CpG sites.
Evaluation of marker selection methods and statistical models for chronological age prediction based on DNA methylation.
Legal medicine (Tokyo, Japan)
Jul 1, 2020
In forensic investigation, retrieving biological information from DNA evidence is a promising field of interest. One of the applications is on the estimation of the age of the donor based on DNA methylation. A large number of studies focused on age p...
MethylNet: an automated and modular deep learning approach for DNA methylation analysis.
BMC bioinformatics
Mar 17, 2020
BACKGROUND: DNA methylation (DNAm) is an epigenetic regulator of gene expression programs that can be altered by environmental exposures, aging, and in pathogenesis. Traditional analyses that associate DNAm alterations with phenotypes suffer from mul...
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