AIMC Topic: DNA Methylation

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MethylNet: an automated and modular deep learning approach for DNA methylation analysis.

BMC bioinformatics
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...

Collective effects of long-range DNA methylations predict gene expressions and estimate phenotypes in cancer.

Scientific reports
DNA methylation of various genomic regions has been found to be associated with gene expression in diverse biological contexts. However, most genome-wide studies have focused on the effect of (1) methylation in cis, not in trans and (2) a single CpG,...

Invited Review: DNA methylation-based classification of paediatric brain tumours.

Neuropathology and applied neurobiology
DNA methylation-based machine learning algorithms represent powerful diagnostic tools that are currently emerging for several fields of tumour classification. For various reasons, paediatric brain tumours have been the main driving forces behind this...

Predicted Prognosis of Patients with Pancreatic Cancer by Machine Learning.

Clinical cancer research : an official journal of the American Association for Cancer Research
PURPOSE: Pancreatic cancer remains a disease of high mortality despite advanced diagnostic techniques. Mucins (MUC) play crucial roles in carcinogenesis and tumor invasion in pancreatic cancers. MUC1 and MUC4 expression are related to the aggressive ...

Machine Learning and Network Analyses Reveal Disease Subtypes of Pancreatic Cancer and their Molecular Characteristics.

Scientific reports
Given that the biological processes governing the oncogenesis of pancreatic cancers could present useful therapeutic targets, there is a pressing need to molecularly distinguish between different clinically relevant pancreatic cancer subtypes. To add...

Machine learning workflows to estimate class probabilities for precision cancer diagnostics on DNA methylation microarray data.

Nature protocols
DNA methylation data-based precision cancer diagnostics is emerging as the state of the art for molecular tumor classification. Standards for choosing statistical methods with regard to well-calibrated probability estimates for these typically highly...

Identification of aberrantly methylated‑differentially expressed genes and gene ontology in prostate cancer.

Molecular medicine reports
Prostate cancer (PCa) is the most frequent urological malignancy in men worldwide. DNA methylation has an essential role in the etiology and pathogenesis of PCa. The purpose of the present study was to identify the aberrantly methylated‑differentiall...

D-GPM: A Deep Learning Method for Gene Promoter Methylation Inference.

Genes
Whole-genome bisulfite sequencing generates a comprehensive profiling of the gene methylation levels, but is limited by a high cost. Recent studies have partitioned the genes into landmark genes and target genes and suggested that the landmark gene e...