Nuclear morphometrics coupled with machine learning identifies dynamic states of senescence across age
S
Sahil A. Mapkar
S
Sarah A. Bliss
E
Edgar E. Perez Carbajal
S
Sean H. Murray
Z
Zhiru Li
A
Anna K. Wilson
V
Vikrant Piprode
Y
You Jin Lee
T
Thorsten Kirsch
K
Katerina S. Petroff
F
Fengyuan Liu
M
Michael N. Wosczyna
Article Details
Journal
Nature Communications
Volume / Issue
Vol. 16, Issue 1
Published
July 07, 2025
ISSN
2041-1723
Publisher
Nature Portfolio
Authors (12)
S
Sahil A. Mapkar
S
Sarah A. Bliss
E
Edgar E. Perez Carbajal
S
Sean H. Murray
Z
Zhiru Li
A
Anna K. Wilson
V
Vikrant Piprode
Y
You Jin Lee
T
Thorsten Kirsch
K
Katerina S. Petroff
F
Fengyuan Liu
M
Michael N. Wosczyna
Related Articles from this Journal
Synthesis of adaptive 15N-nitrosyl-Co7 nanocluster for electrocatalytic C–H functionalization
Chao Wu, Xu Zhang et al.
Aug 2026
10.1038/s41467-026-76516-1
Pan-Ebolavirus nanoparticle vaccine provides protection in rodents from lethal infection by Zaire and Sudan viruses
Connor Weidle, Natalie Brunette et al.
Aug 2026
10.1038/s41467-026-76114-1
Multi-population GWAS meta-analysis identifies bladder cancer susceptibility loci and highlights genetic regulation of smoking-related risk
Ludmila Prokunina-Olsson, Oscar Florez-Vargas et al.
Aug 2026
10.1038/s41467-026-76157-4
Genome-wide annotation of human multi-nucleotide variants reveals widespread functional differences from single nucleotide variants
Weiwei Jin, Wen Cao et al.
Aug 2026
10.1038/s41467-026-76470-y
Allele-specific chromatin architecture shapes imprinted domains and coordinates a distal enhancer and antisense transcription at the mouse Mest-Copg2 domain
Bongmin Bae, Katherine Gu et al.
Aug 2026
10.1038/s41467-026-76506-3