Age and life expectancy clocks based on machine learning analysis of mouse frailty
The discovery of interventions that slow aging could be accelerated by employing non-invasive biometrics that predict biological age or life expectancy. Here the authors use longitudinal frailty data from naturally aging mice to develop two such tools, that are responsive to interventions.
Guardado en:
Autores principales: | , , , , , , , , , |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
Nature Portfolio
2020
|
Materias: | |
Acceso en línea: | https://doaj.org/article/3a49ccbd63f44865818e20ab50fb5065 |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
id |
oai:doaj.org-article:3a49ccbd63f44865818e20ab50fb5065 |
---|---|
record_format |
dspace |
spelling |
oai:doaj.org-article:3a49ccbd63f44865818e20ab50fb50652021-12-02T18:34:02ZAge and life expectancy clocks based on machine learning analysis of mouse frailty10.1038/s41467-020-18446-02041-1723https://doaj.org/article/3a49ccbd63f44865818e20ab50fb50652020-09-01T00:00:00Zhttps://doi.org/10.1038/s41467-020-18446-0https://doaj.org/toc/2041-1723The discovery of interventions that slow aging could be accelerated by employing non-invasive biometrics that predict biological age or life expectancy. Here the authors use longitudinal frailty data from naturally aging mice to develop two such tools, that are responsive to interventions.Michael B. SchultzAlice E. KaneSarah J. MitchellMichael R. MacArthurElisa WarnerDavid S. VogelJames R. MitchellSusan E. HowlettMichael S. BonkowskiDavid A. SinclairNature PortfolioarticleScienceQENNature Communications, Vol 11, Iss 1, Pp 1-12 (2020) |
institution |
DOAJ |
collection |
DOAJ |
language |
EN |
topic |
Science Q |
spellingShingle |
Science Q Michael B. Schultz Alice E. Kane Sarah J. Mitchell Michael R. MacArthur Elisa Warner David S. Vogel James R. Mitchell Susan E. Howlett Michael S. Bonkowski David A. Sinclair Age and life expectancy clocks based on machine learning analysis of mouse frailty |
description |
The discovery of interventions that slow aging could be accelerated by employing non-invasive biometrics that predict biological age or life expectancy. Here the authors use longitudinal frailty data from naturally aging mice to develop two such tools, that are responsive to interventions. |
format |
article |
author |
Michael B. Schultz Alice E. Kane Sarah J. Mitchell Michael R. MacArthur Elisa Warner David S. Vogel James R. Mitchell Susan E. Howlett Michael S. Bonkowski David A. Sinclair |
author_facet |
Michael B. Schultz Alice E. Kane Sarah J. Mitchell Michael R. MacArthur Elisa Warner David S. Vogel James R. Mitchell Susan E. Howlett Michael S. Bonkowski David A. Sinclair |
author_sort |
Michael B. Schultz |
title |
Age and life expectancy clocks based on machine learning analysis of mouse frailty |
title_short |
Age and life expectancy clocks based on machine learning analysis of mouse frailty |
title_full |
Age and life expectancy clocks based on machine learning analysis of mouse frailty |
title_fullStr |
Age and life expectancy clocks based on machine learning analysis of mouse frailty |
title_full_unstemmed |
Age and life expectancy clocks based on machine learning analysis of mouse frailty |
title_sort |
age and life expectancy clocks based on machine learning analysis of mouse frailty |
publisher |
Nature Portfolio |
publishDate |
2020 |
url |
https://doaj.org/article/3a49ccbd63f44865818e20ab50fb5065 |
work_keys_str_mv |
AT michaelbschultz ageandlifeexpectancyclocksbasedonmachinelearninganalysisofmousefrailty AT aliceekane ageandlifeexpectancyclocksbasedonmachinelearninganalysisofmousefrailty AT sarahjmitchell ageandlifeexpectancyclocksbasedonmachinelearninganalysisofmousefrailty AT michaelrmacarthur ageandlifeexpectancyclocksbasedonmachinelearninganalysisofmousefrailty AT elisawarner ageandlifeexpectancyclocksbasedonmachinelearninganalysisofmousefrailty AT davidsvogel ageandlifeexpectancyclocksbasedonmachinelearninganalysisofmousefrailty AT jamesrmitchell ageandlifeexpectancyclocksbasedonmachinelearninganalysisofmousefrailty AT susanehowlett ageandlifeexpectancyclocksbasedonmachinelearninganalysisofmousefrailty AT michaelsbonkowski ageandlifeexpectancyclocksbasedonmachinelearninganalysisofmousefrailty AT davidasinclair ageandlifeexpectancyclocksbasedonmachinelearninganalysisofmousefrailty |
_version_ |
1718377912985452544 |