AIMC Topic: CpG Islands
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AI-driven feature selection and epigenetic pattern analysis: A screening strategy of CpGs validated by pyrosequencing for body fluid identification.
Forensic science international
Dec 6, 2024
Identification of body fluid stain at crime scene is one of the important tasks of forensic evidence analysis. Currently, body fluid-specific CpGs detected by DNA methylation microarray screening, have been widely studied for forensic body fluid iden...
A machine learning-based method for feature reduction of methylation data for the classification of cancer tissue origin.
International journal of clinical oncology
Sep 18, 2024
BACKGROUND: Genome DNA methylation profiling is a promising yet costly method for cancer classification, involving substantial data. We developed an ensemble learning model to identify cancer types using methylation profiles from a limited number of ...
Diagnostic classification based on DNA methylation profiles using sequential machine learning approaches.
PloS one
Sep 6, 2024
Aberrant methylation patterns in human DNA have great potential for the discovery of novel diagnostic and disease progression biomarkers. In this paper we used machine learning algorithms to identify promising methylation sites for diagnosing cancero...
Phenotype prediction using biologically interpretable neural networks on multi-cohort multi-omics data.
NPJ systems biology and applications
Aug 2, 2024
Integrating multi-omics data into predictive models has the potential to enhance accuracy, which is essential for precision medicine. In this study, we developed interpretable predictive models for multi-omics data by employing neural networks inform...
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...
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