Machine learning reveals genes impacting oxidative stress resistance across yeasts

Reactive oxygen species (ROS) are highly reactive molecules encountered by yeasts during routine metabolism and during interactions with other organisms, including host infection. Here, we characterized the variation in resistance to ROS across the ancient yeast subphylum Saccharomycotina and used machine learning (ML) to identify gene families whose sizes were predictive of ROS resistance.. Authors: Coon, Joshua J. [GLBRC - University of Wisconsin]. DOE Contract: SC0018409. Subjects: AI; Artificial Intelligece; Data Independent Acquisition; DatasetType:Proteomics; Kluyveromyces lactis; Machine Learning; Oxidative Stress; Proteomics; Reactive Oxygen Species; Saccharomyces cerevisiae; Yeast