This site is under development. For the current active site, go to bcbhub.csic.es.

Orcid Publication

Detalle de: Deep-learning dive into the antimicrobial potential of Archaea

Title Deep-learning dive into the antimicrobial potential of Archaea
Abstract

The global burden of antimicrobial resistance demands the urgent development of new antibiotics. To face this threat, Torres et al. leveraged deep-learning models to identify archaeal encrypted peptides (termed 'archaeasins') with potential antimicrobial activity. This work highlights Archaea as an underexplored but potentially rich source of antibiotics.

Apa Reference Rodríguez-Gijón, A. & Laso-Pérez, R. (2026). Deep-learning dive into the antimicrobial potential of Archaea. Trends in Microbiology, 34(2), 123-125. 10.1016/j.tim.2025.12.004
Doi 10.1016/j.tim.2025.12.004
Publication Date Feb 2026
Publication Type Article
Researcher Alejandro Rodríguez Gijón
Ontology Drug resistance
Research Groups
Tools

Suggest changes

Publications are synced automatically from ORCID, so they can't be edited here directly. Spotted something wrong? Let us know below and we'll take care of it.

← Return to Home