Towards AI-driven longevity research: An overview.

IF 3.3 Q2 GERIATRICS & GERONTOLOGY
Frontiers in aging Pub Date : 2023-03-01 eCollection Date: 2023-01-01 DOI:10.3389/fragi.2023.1057204
Nicola Marino, Guido Putignano, Simone Cappilli, Emmanuele Chersoni, Antonella Santuccione, Giuliana Calabrese, Evelyne Bischof, Quentin Vanhaelen, Alex Zhavoronkov, Bryan Scarano, Alessandro D Mazzotta, Enrico Santus
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引用次数: 0

Abstract

While in the past technology has mostly been utilized to store information about the structural configuration of proteins and molecules for research and medical purposes, Artificial Intelligence is nowadays able to learn from the existing data how to predict and model properties and interactions, revealing important knowledge about complex biological processes, such as aging. Modern technologies, moreover, can rely on a broader set of information, including those derived from the next-generation sequencing (e.g., proteomics, lipidomics, and other omics), to understand the interactions between human body and the external environment. This is especially relevant as external factors have been shown to have a key role in aging. As the field of computational systems biology keeps improving and new biomarkers of aging are being developed, artificial intelligence promises to become a major ally of aging research.

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迈向人工智能驱动的长寿研究:综述。
过去,技术主要用于存储蛋白质和分子结构配置信息,以用于研究和医疗目的,而如今,人工智能能够从现有数据中学习如何预测和模拟特性和相互作用,从而揭示有关衰老等复杂生物过程的重要知识。此外,现代技术还可以依靠更广泛的信息,包括从下一代测序(如蛋白质组学、脂质组学和其他 omics)中获得的信息,来了解人体与外部环境之间的相互作用。这一点尤为重要,因为外部因素已被证明在衰老中起着关键作用。随着计算系统生物学领域的不断进步和新的衰老生物标志物的开发,人工智能有望成为衰老研究的主要盟友。
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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