Fangzhou Li

AIFS is collaborating with UC Davis to comprehensively analyze the composition of milk using various 'omics analyses, aiming to create a database that connects molecular information with research-derived data on nutritional and health benefits, facilitating a deeper understanding of the health effects of milk molecules through machine learning-derived insights.

Efforts to expand food composition information, exemplified by FoodDB, encounter challenges of manual curation and the presence of "nutritional dark matter," prompting a proposed solution involving the creation of a software package for automated curation of nutrition data from papers.