Integrating ensemble machine learning and multi-omics approaches to identify Dp44mT as a novel anti-Candida albicans agent targeting cellular iron homeostasis

This study presents a practical approach for predicting the antifungal activity of com-pounds using machine learning models and provides new insights into the development of antifungal compounds by disrupting iron homeostasis in <i>C. albicans</i>.