Towards AI-driven longevity research: An overview

被引：14

作者：

Marino, Nicola ^{[1
]}

Putignano, Guido ^{[1
]}

Cappilli, Simone ^{[2
,3
]}

Chersoni, Emmanuele ^{[4
]}

Santuccione, Antonella ^{[1
]}

Calabrese, Giuliana ^{[5
]}

Bischof, Evelyne ^{[6
]}

Vanhaelen, Quentin ^{[6
]}

Zhavoronkov, Alex ^{[6
]}

Scarano, Bryan ^{[5
]}

Mazzotta, Alessandro D. ^{[7
,8
]}

Santus, Enrico ^{[9
]}

机构：

[1] Womens Brain Project WBP, Gunterhausen, Switzerland

[2] Univ Cattolica Sacro Cuore, Dermatol, Rome, Italy

[3] A Gemelli Univ Hosp Fdn, IRCCS, Dept Abdominal & Endocrine Metab Med & Surg Sci, UOC Dermatol, Rome, Italy

[4] Hong Kong Polytech Univ, Dept Chinese & Bilingual Studies, Hong Kong, Peoples R China

[5] Univ Cattolica Sacro Cuore, Dept Translat Med & Surg, Rome, Italy

[6] Insil Med Hong Kong Ltd, Hong Kong, Peoples R China

[7] Inst Mutualiste Montsouris, Dept Digest Oncol & Metab Surg, Paris, France

[8] Biorobot Inst, Scuola Super Sant Anna, Pisa, Italy

[9] Bayer USA, Whippany, NJ USA

来源：

FRONTIERS IN AGING | 2023年 / 4卷

关键词：

artificial intelligence; machine learning; biomarkers; feature selection; deep aging clock; longevity medicine; STEM-CELLS; TRANSCRIPTION FACTORS; NETWORK THEORY; TELOMERE; BIOLOGY; SENESCENCE; DIFFERENTIATION; LYMPHOCYTES; EXPOSURE; ROLES;

D O I：

10.3389/fragi.2023.1057204

中图分类号：

R592 [老年病学]; C [社会科学总论];

学科分类号：

03 ; 0303 ; 100203 ;

摘要：

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.

引用

页数：15

共 126 条

[1] Usp16 contributes to somatic stem-cell defects in Down's syndrome [J].