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Computational tools for geroscience

The rapid progress of the past three decades has led the geroscience field near a point where human interventions in aging are plausible. Advances across scientific areas, such as high throughput “-omics” approaches, have led to an exponentially increasing quantity of data available for biogerontolo...

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Detalles Bibliográficos
Autores principales: Kruempel, Joseph C.P., Howington, Marshall B., Leiser, Scott F.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7685266/
https://www.ncbi.nlm.nih.gov/pubmed/33241167
http://dx.doi.org/10.1016/j.tma.2019.11.004
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author Kruempel, Joseph C.P.
Howington, Marshall B.
Leiser, Scott F.
author_facet Kruempel, Joseph C.P.
Howington, Marshall B.
Leiser, Scott F.
author_sort Kruempel, Joseph C.P.
collection PubMed
description The rapid progress of the past three decades has led the geroscience field near a point where human interventions in aging are plausible. Advances across scientific areas, such as high throughput “-omics” approaches, have led to an exponentially increasing quantity of data available for biogerontologists. To best translate the lifespan and healthspan extending interventions discovered by basic scientists into preventative medicine, it is imperative that the current data are comprehensively utilized to generate testable hypotheses about translational interventions. Building a translational pipeline for geroscience will require both systematic efforts to identify interventions that extend healthspan across taxa and diagnostics that can identify patients who may benefit from interventions prior to the onset of an age-related morbidity. Databases and computational tools that organize and analyze both the wealth of information available on basic biogerontology research and clinical data on aging populations will be critical in developing such a pipeline. Here, we review the current landscape of databases and computational resources available for translational aging research. We discuss key platforms and tools available for aging research, with a focus on how each tool can be used in concert with hypothesis driven experiments to move closer to human interventions in aging.
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spelling pubmed-76852662020-11-24 Computational tools for geroscience Kruempel, Joseph C.P. Howington, Marshall B. Leiser, Scott F. Transl Med Aging Article The rapid progress of the past three decades has led the geroscience field near a point where human interventions in aging are plausible. Advances across scientific areas, such as high throughput “-omics” approaches, have led to an exponentially increasing quantity of data available for biogerontologists. To best translate the lifespan and healthspan extending interventions discovered by basic scientists into preventative medicine, it is imperative that the current data are comprehensively utilized to generate testable hypotheses about translational interventions. Building a translational pipeline for geroscience will require both systematic efforts to identify interventions that extend healthspan across taxa and diagnostics that can identify patients who may benefit from interventions prior to the onset of an age-related morbidity. Databases and computational tools that organize and analyze both the wealth of information available on basic biogerontology research and clinical data on aging populations will be critical in developing such a pipeline. Here, we review the current landscape of databases and computational resources available for translational aging research. We discuss key platforms and tools available for aging research, with a focus on how each tool can be used in concert with hypothesis driven experiments to move closer to human interventions in aging. 2019-11-14 2019 /pmc/articles/PMC7685266/ /pubmed/33241167 http://dx.doi.org/10.1016/j.tma.2019.11.004 Text en This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Article
Kruempel, Joseph C.P.
Howington, Marshall B.
Leiser, Scott F.
Computational tools for geroscience
title Computational tools for geroscience
title_full Computational tools for geroscience
title_fullStr Computational tools for geroscience
title_full_unstemmed Computational tools for geroscience
title_short Computational tools for geroscience
title_sort computational tools for geroscience
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7685266/
https://www.ncbi.nlm.nih.gov/pubmed/33241167
http://dx.doi.org/10.1016/j.tma.2019.11.004
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