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Towards AI-driven longevity research: An overview

Authors :
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
Source :
Frontiers in Aging, Vol 4 (2023)
Publication Year :
2023
Publisher :
Frontiers Media S.A., 2023.

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.

Details

Language :
English
ISSN :
26736217
Volume :
4
Database :
Directory of Open Access Journals
Journal :
Frontiers in Aging
Publication Type :
Academic Journal
Accession number :
edsdoj.7bf248a7ed541c0b5364cadb1ab9e02
Document Type :
article
Full Text :
https://doi.org/10.3389/fragi.2023.1057204