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eNauka >  Results >  Prediction of progesterone receptor binding potency, agonism and antagonism using machine learning models
Title: Prediction of progesterone receptor binding potency, agonism and antagonism using machine learning models
Authors: Milošević Nemanja  ; Sukur Nataša  ; Fa Svetlana  ; Stanić Bojana  ; Andrić Nebojša  
Issue Date: 2025
Publication: Computational Toxicology
ISSN: 2468-1113 COMPUTATIONAL TOXICOLOGY Search Idenfier
2468-1113 COMPUTATIONAL TOXICOLOGY Search Idenfier
Type: Article
Collation: vol. 34 br. 100351 str. 100351-100351
DOI: 10.1016/j.comtox.2025.100351
WoS-ID: 001497485700001
Scopus-ID: 2-s2.0-105004883377
URI: https://www.cris.uns.ac.rs/record.jsf?recordId=140553&source=eNauka&language=en
https://cris.uns.ac.rs/en/scientific-results/journal-publication/46889
https://enauka.gov.rs/handle/123456789/982380
Project: Provincial Secretariat for Higher Education and Scientific Research of the Autonomous Province of Vojvodina [003088437 2024 09418 003 000 000 001/2]
M-category: 
21M21

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