Navigating the complex landscape of high-dimensional omics data with machine learning models presents a significant challenge. The integration of biological domain knowledge into these models has shown promise in creating more meaningful stratificati...
MOTIVATION: Classification of samples using biomedical omics data is a widely used method in biomedical research. However, these datasets often possess challenging characteristics, including high dimensionality, limited sample sizes, and inherent bia...
SUMMARY: Federated learning enables collaboration in medicine, where data is scattered across multiple centers without the need to aggregate the data in a central cloud. While, in general, machine learning models can be applied to a wide range of dat...
DNA methylation is a fundamental epigenetic modification involved in various biological processes and diseases. Analysis of DNA methylation data at a genome-wide and high-throughput level can provide insights into diseases influenced by epigenetics, ...
Deoxyribonucleic acid(DNA) N6-methyladenine plays a vital role in various biological processes, and the accurate identification of its site can provide a more comprehensive understanding of its biological effects. There are several methods for 6mA si...
Methods in molecular biology (Clifton, N.J.)
Jan 1, 2023
Genome-wide DNA methylomes have contributed greatly to tumor detection and subclassification. However, interpreting the biological impact of the DNA methylome at the individual gene level remains a challenge. MethylationToActivity (M2A) is a pipeline...
BACKGROUND: DNA methylation has a significant effect on gene expression and can be associated with various diseases. Meta-analysis of available DNA methylation datasets requires development of a specific workflow for joint data processing.
N6-methyladenine (6mA) is associated with important roles in DNA replication, DNA repair, transcription, regulation of gene expression. Several experimental methods were used to identify DNA modifications. However, these experimental methods are cost...
Transcription factors (TFs) are proteins specifically involved in gene expression regulation. It is generally accepted in epigenetics that methylated nucleotides could prevent the TFs from binding to DNA fragments. However, recent studies have confir...
Methods in molecular biology (Clifton, N.J.)
Jan 1, 2022
We introduce the CPFNN (Correlation Pre-Filtering Neural Network) for biological age prediction based on blood DNA methylation data. The model is built on 20,000 top correlated DNA methylation features and trained by 1810 healthy samples from GEO dat...