Machine learning can guide experimental approaches for protein digestibility estimations. (arXiv:2211.00625v1 [q-bio.QM])

Food protein digestibility and bioavailability are critical aspects in
addressing human nutritional demands, particularly when seeking sustainable
alternatives to animal-based proteins. In this study, we propose a machine
learning approach to predict the true ileal digestibility coefficient of food
items. The model makes use of a unique curated dataset that combines
nutritional information from different foods with FASTA sequences of some of
their protein families. We extracted the biochemical properties of the proteins
and combined these properties with embeddings from …

arxiv bio estimations experimental machine machine learning protein