Zachary A. Holmes

This paper develops a foundation model for microbial growth dynamics using self-supervised learning on diverse datasets, enabling accurate reconstruction and prediction of growth patterns and antibiotic responses.

The paper shows that microbial community dynamics can be represented by low-dimensional latent variables, with the critical dimension scaling linearly with observables.

The paper identifies Pseudomonas stutzeri as a plastic-degrading species by analyzing microbial enzyme sequences and structures, and validates its ability to degrade synthetic polymers.