J. E. Goldford

This paper predicts microbial dioxygen utilization from genome sequences without gene annotation, achieving >70% accuracy and demonstrating environmental correlations.

The paper models metabolic evolution and finds that Mo-dependent biochemistry emerged after oxygen rise, supported by genomic and machine learning analyses.

This study shows that available energy fluxes drive a transition in microbial community diversity, stability, and function, shifting from resource-limited to preference-driven regimes.

The paper shows that microbial communities re-assemble into predictable, stable communities through non-specific metabolic cross-feeding, even when grown in minimal environments.