Heterotrophic bacteria exhibit remarkable taxonomic and metabolic diversity. Experimental phenotyping of individual strains is often impractical due to the diversity of metabolic strategies, highlighting the need for predictive approaches based on biochemical principles. Here, we demonstrate that bacteria preferentially catabolize amino acids that are energetically inexpensive to synthesize and require shorter degradation pathways. Our results show how general biochemical constraints shape amino acid catabolism across bacterial lineages and provide a framework for integrating microbial physiology into predictive ecological theory.
The Hidden Power of Normalization: Exponential Capacity Control in Deep Neural Networks
arXiv:2511.00958v1 Announce Type: cross Abstract: Normalization methods are fundamental components of modern deep neural networks (DNNs). Empirically, they are known to stabilize optimization dynamics and
