--- _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' ...