---
_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. <i>Genome Biology</i>. 2018;19. doi:<a href="https://doi.org/10.1186/s13059-018-1599-6">10.1186/s13059-018-1599-6</a>
  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. <i>Genome Biology</i>. BioMed Central. <a href="https://doi.org/10.1186/s13059-018-1599-6">https://doi.org/10.1186/s13059-018-1599-6</a>
  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.” <i>Genome Biology</i>.
    BioMed Central, 2018. <a href="https://doi.org/10.1186/s13059-018-1599-6">https://doi.org/10.1186/s13059-018-1599-6</a>.
  ieee: J. G. Fleischer <i>et al.</i>, “Predicting age from the transcriptome of human
    dermal fibroblasts,” <i>Genome Biology</i>, 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.” <i>Genome Biology</i>, vol. 19, 221, BioMed Central, 2018,
    doi:<a href="https://doi.org/10.1186/s13059-018-1599-6">10.1186/s13059-018-1599-6</a>.
  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: 2024-10-14T11:20:00Z
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: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 19
year: '2018'
...