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. 2023 Mar 1;4:1057204. doi: 10.3389/fragi.2023.1057204

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Copyright © 2023 Marino, Putignano, Cappilli, Chersoni, Santuccione, Calabrese, Bischof, Vanhaelen, Zhavoronkov, Scarano, Mazzotta and Santus.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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To identify novel aging-related proteins, the full set of human proteins was extracted from the Swiss-Prot database. Already known aging related proteins listed on the GenAge database were used as instances of the aging-related class. UniProt, Gene Ontology and GeneFriends databases were used to extract 21,000 protein characteristics that were subsequently used as features to train 3 classifiers to identify proteins likely to be associated with aging.