Cargando…

Towards AI-driven longevity research: An overview

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, re...

Descripción completa

Detalles Bibliográficos
Autores principales: Marino, Nicola, Putignano, Guido, Cappilli, Simone, Chersoni, Emmanuele, Santuccione, Antonella, Calabrese, Giuliana, Bischof, Evelyne, Vanhaelen, Quentin, Zhavoronkov, Alex, Scarano, Bryan, Mazzotta, Alessandro D., Santus, Enrico
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10018490/
https://www.ncbi.nlm.nih.gov/pubmed/36936271
http://dx.doi.org/10.3389/fragi.2023.1057204
Descripción
Sumario: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.