Towards AI-driven longevity research: An overview
Nicola Marino, Guido Putignano, Simone Cappilli, Emmanuele Chersoni, Antonella Santuccione Chadha, Giuliana Calabrese, Evelyne Bischof, Quentin Vanhaelen, Alex Zhavoronkov, Bryan Scarano, Alessandro Mazzotta, Enrico Santus
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.