Computational tools for geroscience

Q2 Medicine
Joseph C.P. Kruempel , Marshall B. Howington , Scott F. Leiser
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引用次数: 0

Abstract

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.

Abstract Image

地质科学的计算工具
过去三十年的快速发展使老年科学领域接近一个人类干预衰老是合理的点。科学领域的进步,如高通量“组学”方法,导致生物老年学家可获得的数据量呈指数级增长。为了最好地将基础科学家发现的延长寿命和健康寿命的干预措施转化为预防医学,必须全面利用现有数据来产生关于转化干预措施的可测试假设。建立一个老年科学的转化管道,既需要系统的努力,以确定延长不同分类群健康跨度的干预措施,也需要能够在年龄相关疾病发病之前确定可能受益于干预措施的患者的诊断方法。数据库和计算工具,组织和分析基础生物老年学研究和老年人口临床数据的丰富信息,将是开发这样一个管道的关键。在这里,我们回顾了目前可用于翻译老化研究的数据库和计算资源。我们讨论了衰老研究的关键平台和工具,重点是如何将每个工具与假设驱动的实验相结合,以更接近人类对衰老的干预。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Translational Medicine of Aging
Translational Medicine of Aging Medicine-Geriatrics and Gerontology
CiteScore
5.30
自引率
0.00%
发文量
2
审稿时长
103 days
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