Benchmarking ML in ADMET predictions: the practical impact of feature representations in ligand-based models

Abstract This study, focusing on predicting Absorption, Distribution, Metabolism, Excretion, and Toxicology (ADMET) properties, addresses the key challenges of ML models trained using ligand-based representations. We propose a structured approach to data feature selection, taking a step beyond the c...

Full description

Saved in:
Bibliographic Details
Main Authors: Gintautas Kamuntavičius, Tanya Paquet, Orestis Bastas, Dainius Šalkauskas, Alvaro Prat, Hisham Abdel Aty, Aurimas Pabrinkis, Povilas Norvaišas, Roy Tal
Format: Article
Language:English
Published: BMC 2025-07-01
Series:Journal of Cheminformatics
Online Access:https://doi.org/10.1186/s13321-025-01041-0
Tags: Add Tag
No Tags, Be the first to tag this record!