---
_id: '11064'
abstract:
- lang: eng
text: 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 within the transcriptome.
We develop an ensemble machine learning method that predicts age to a median error
of 4 years, outperforming previous methods used to predict age. The ensemble was
further validated by testing it on ten progeria patients, and our method is the
only one that predicts accelerated aging in these patients.
article_number: '221'
article_processing_charge: No
article_type: original
author:
- first_name: Jason G.
full_name: Fleischer, Jason G.
last_name: Fleischer
- first_name: Roberta
full_name: Schulte, Roberta
last_name: Schulte
- first_name: Hsiao H.
full_name: Tsai, Hsiao H.
last_name: Tsai
- first_name: Swati
full_name: Tyagi, Swati
last_name: Tyagi
- first_name: Arkaitz
full_name: Ibarra, Arkaitz
last_name: Ibarra
- first_name: Maxim N.
full_name: Shokhirev, Maxim N.
last_name: Shokhirev
- first_name: Ling
full_name: Huang, Ling
last_name: Huang
- first_name: Martin W
full_name: HETZER, Martin W
id: 86c0d31b-b4eb-11ec-ac5a-eae7b2e135ed
last_name: HETZER
orcid: 0000-0002-2111-992X
- first_name: Saket
full_name: Navlakha, Saket
last_name: Navlakha
citation:
ama: Fleischer JG, Schulte R, Tsai HH, et al. Predicting age from the transcriptome
of human dermal fibroblasts. Genome Biology. 2018;19. doi:10.1186/s13059-018-1599-6
apa: Fleischer, J. G., Schulte, R., Tsai, H. H., Tyagi, S., Ibarra, A., Shokhirev,
M. N., … Navlakha, S. (2018). Predicting age from the transcriptome of human dermal
fibroblasts. Genome Biology. BioMed Central. https://doi.org/10.1186/s13059-018-1599-6
chicago: Fleischer, Jason G., Roberta Schulte, Hsiao H. Tsai, Swati Tyagi, Arkaitz
Ibarra, Maxim N. Shokhirev, Ling Huang, Martin Hetzer, and Saket Navlakha. “Predicting
Age from the Transcriptome of Human Dermal Fibroblasts.” Genome Biology.
BioMed Central, 2018. https://doi.org/10.1186/s13059-018-1599-6.
ieee: J. G. Fleischer et al., “Predicting age from the transcriptome of human
dermal fibroblasts,” Genome Biology, vol. 19. BioMed Central, 2018.
ista: Fleischer JG, Schulte R, Tsai HH, Tyagi S, Ibarra A, Shokhirev MN, Huang L,
Hetzer M, Navlakha S. 2018. Predicting age from the transcriptome of human dermal
fibroblasts. Genome Biology. 19, 221.
mla: Fleischer, Jason G., et al. “Predicting Age from the Transcriptome of Human
Dermal Fibroblasts.” Genome Biology, vol. 19, 221, BioMed Central, 2018,
doi:10.1186/s13059-018-1599-6.
short: J.G. Fleischer, R. Schulte, H.H. Tsai, S. Tyagi, A. Ibarra, M.N. Shokhirev,
L. Huang, M. Hetzer, S. Navlakha, Genome Biology 19 (2018).
date_created: 2022-04-07T07:45:40Z
date_published: 2018-12-20T00:00:00Z
date_updated: 2022-07-18T08:32:34Z
day: '20'
doi: 10.1186/s13059-018-1599-6
extern: '1'
external_id:
pmid:
- '30567591'
intvolume: ' 19'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.1186/s13059-018-1599-6
month: '12'
oa: 1
oa_version: Published Version
pmid: 1
publication: Genome Biology
publication_identifier:
issn:
- 1474-760X
publication_status: published
publisher: BioMed Central
quality_controlled: '1'
scopus_import: '1'
status: public
title: Predicting age from the transcriptome of human dermal fibroblasts
type: journal_article
user_id: 72615eeb-f1f3-11ec-aa25-d4573ddc34fd
volume: 19
year: '2018'
...