Geometric deep learning as a potential tool for antimicrobial peptide prediction. - Fabiano C. Fernandes; Marlon H. Cardoso; Abel Gil-Ley; Lívia V. Luchi; Maria G. L. da Silva; Maria L. R. Macedo; Cesar de la Fuente-Nunez; Octávio L. Franco (Frontiers Bioinform., 2023)

Editorial: Machine learning approaches to antimicrobials: discovery and resistance. - Shira L. Broschat; Shirley W. I. Siu; Cesar de la Fuente-Nunez (Frontiers Bioinform., 2024)

AI in biomaterials discovery: generating self-assembling peptides with resource-efficient deep learning. - Tianang Leng; Cesar de la Fuente-Nunez (Nat. Mac. Intell., 2024)

From Data to Decisions: Leveraging Artificial Intelligence and Machine Learning in Combating Antimicrobial Resistance - a Comprehensive Review. - José M. Pérez de la Lastra; Samuel J. T. Wardell; Tarun Pal; Cesar de la Fuente-Nunez; Daniel Pletzer (J. Medical Syst., 2024)

Covering Multiple Objectives with a Small Set of Solutions Using Bayesian Optimization. - Natalie Maus; Kyurae Kim; Yimeng Zeng; Haydn Thomas Jones; Fangping Wan; Marcelo Der Torossian Torres; Cesar de la Fuente-Nunez; Jacob R. Gardner (CoRR, 2025)

Large Scale Multi-Task Bayesian Optimization with Large Language Models. - Yimeng Zeng; Natalie Maus; Haydn Thomas Jones; Jeffrey Tao; Fangping Wan; Marcelo Der Torossian Torres; Cesar de la Fuente-Nunez; Ryan Marcus; Osbert Bastani; Jacob R. Gardner (CoRR, 2025)

Predicting and generating antibiotics against future pathogens with ApexOracle. - Tianang Leng; Fangping Wan; Marcelo Der Torossian Torres; Cesar de la Fuente-Nunez (CoRR, 2025)

A Dataset for Distilling Knowledge Priors from Literature for Therapeutic Design. - Haydn Thomas Jones; Natalie Maus; Josh Magnus Ludan; Maggie Ziyu Huan; Jiaming Liang; Marcelo Der Torossian Torres; Jiatao Liang; Zachary G. Ives; Yoseph Barash; Cesar de la Fuente-Nunez; Jacob R. Gardner; Mark Yatskar (CoRR, 2025)