ChromAgeNet
Biomarker1 paper1 finding
- Cells1
Associations
1Biological age
upin silico1
1 study
Biological age
upin silico1
ChromAgeNet predicts biological age in silico (AUROC of 0.77 ± 0.03).
“We trained our algorithm on 3D microscope images of DAPI-stained HSC nuclei to discriminate between young and aged murine HSCs, achieving an AUROC of 0.77 ± 0.03.”
In silico3D microscope images of DAPI-stained HSC nucleihematopoietic stem cell
Deep learning predicts mouse hematopoietic stem cell aging from chromatin architecture · Aging cell · 28 Sep 2026
Latest
1CellsAging clocks
Deep learning predicts mouse hematopoietic stem cell aging from chromatin architecture
A convolutional neural network named ChromAgeNet distinguished young from aged mouse stem cells using three-dimensional nuclear images and identified key structural markers of aging.