Matthew Schertler

Enabling predictive modeling of molecular connections between fermented foods and human inflammation through a paired dataset of cell-based models and multi-omics approaches

The paper creates a paired dataset of fermented foods and human cell responses to enable predictive models of their anti-inflammatory effects through multi-omics approaches.

Leveraging publicly available datasets and machine learning approaches for predicting the health benefits of fermented foods

The paper uses machine learning on fermented food datasets to predict bioactive peptides and their health benefits, providing publicly available tools and resources for further research.