Back to search

Article

Cross Tissue DNAm Biomarker Prediction using Transfer Learning

2024-06-03

Abstract excerpt

DNA methylation (DNAm) is an epigenetic mechanism vital for regulating gene expression and influencing disease states. Developing accurate DNAm biomarkers often requires data from specific tissues, which are sometimes difficult to access. This study explores the use of Transfer Learning (TL) to predict blood DNAm biomarkers using saliva DNAm data, aiming to overcome limitations posed by sample size and tissue acce...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work
dced2ed6-e1e1-52d1-a75e-4f27a4ca360c
DOI
10.1101/2024.06.01.596949
Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest
Interactive article relationship graphSelect a related publication card to move it into the centre and load its closest explainable connections. Solid lines are source-backed structured connections. Dashed lines are semantic discovery signals and are not scientific evidence.
Cross Tissue DNAm Biomarker Prediction using Transfer LearningDOI 10.1101/2024.06.01.596949
Select a neighboring publication to make it the new centre.