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eNauka >  Results >  Machine Learning-Guided Design of Rhenium Tricarbonyl Complexes for Next-Generation Antibiotics
Title: Machine Learning-Guided Design of Rhenium Tricarbonyl Complexes for Next-Generation Antibiotics
Authors: Nedyalkova, Miroslava; Demirci, Gozde; Cortat, Youri; Schindler, Kevin; Rahmani, Fatlinda; Horner, Justine; Vasighi, Mahdi; Crochet, Aurelien; Pavic, Aleksandar B  ; Mamula, Olimpia;
Zobi, Fabio; Lattuada, Marco;
Issue Date: 2025
Publication: ACS BIO & MED CHEM AU
ISSN: 2694-2437 ACS BIO & MED CHEM AU Search Idenfier
Type: Article
DOI: 10.1021/acsbiomedchemau.5c00125
WoS-ID: 001565531600001
Scopus-ID: 2-s2.0-105018776426
URI: https://imagine.imgge.bg.ac.rs/handle/123456789/3184
https://enauka.gov.rs/handle/123456789/999544
Project: NCCR-BioInspired Materials and the University of Fribourg
Metadata source: (Preuzeto iz Nasi u WoS)
M-category: 
21M21

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