Predicting age from the transcriptome of human dermal fibroblasts

Predicting age from the transcriptome of human dermal fibroblasts

Abstract Biomarkers of aging can be used to assess the health of individuals and to study aging and age-related diseases. We generate a large dataset of genome-wide RNA-seq profiles of human dermal fibroblasts from 133 people aged 1 to 94 years old to test whether signatures of aging are encoded wit...

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Bibliographic Details
Main Authors: Jason G. Fleischer, Roberta Schulte, Hsiao H. Tsai, Swati Tyagi, Arkaitz Ibarra, Maxim N. Shokhirev, Ling Huang, Martin W. Hetzer, Saket Navlakha
Format: Article
Language:English
Published: BMC 2018-12-01
Series:Genome Biology
Subjects:
Biological age
Skin fibroblasts
Machine learning
Ensemble classifiers
RNA-seq
Aging
Online Access:http://link.springer.com/article/10.1186/s13059-018-1599-6

Internet

http://link.springer.com/article/10.1186/s13059-018-1599-6

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