Cargando…
MethylNet: an automated and modular deep learning approach for DNA methylation analysis
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 multiple hypothesis testing and multi-collinearity du...
Autores principales: | Levy, Joshua J., Titus, Alexander J., Petersen, Curtis L., Chen, Youdinghuan, Salas, Lucas A., Christensen, Brock C. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7076991/ https://www.ncbi.nlm.nih.gov/pubmed/32183722 http://dx.doi.org/10.1186/s12859-020-3443-8 |
Ejemplares similares
-
MethylSPWNet and MethylCapsNet: Biologically Motivated Organization of DNAm Neural Networks, Inspired by Capsule Networks
por: Levy, Joshua J., et al.
Publicado: (2021) -
Calculating detection limits and uncertainty of reference-based deconvolution of whole-blood DNA methylation data
por: Bell-Glenn, Shelby, et al.
Publicado: (2023) -
Altered immune phenotype and DNA methylation in panic disorder
por: Petersen, Curtis L., et al.
Publicado: (2020) -
HiTIMED: hierarchical tumor immune microenvironment epigenetic deconvolution for accurate cell type resolution in the tumor microenvironment using tumor-type-specific DNA methylation data
por: Zhang, Ze, et al.
Publicado: (2022) -
DNA 5-hydroxymethylcytosine in pediatric central nervous system tumors may impact tumor classification and is a positive prognostic marker
por: Azizgolshani, Nasim, et al.
Publicado: (2021)