Zachary A. King

The paper introduces an automated system called Lila to design and optimize microbial strains for producing small molecules, achieving high titers for naringenin and creating strains for 242 molecules.

ImmCellFie infers cell metabolic capabilities from transcriptomic or proteomic data using genome-scale models and provides interactive analysis tools.

This paper introduces a visualization method for time-course metabolomics data integrated into metabolic network maps, demonstrating its utility in analyzing platelet and erythrocyte storage.

Memote, open-source Python software, runs a community-maintained, partly scored test suite (consistency, biomass, annotations, optional experimental data) on SBML-encoded genome-scale metabolic models, once or through continuous integration.

The paper decomposes the Escherichia coli transcriptome into 70 independent regulatory signals, showing that 50 correspond to known transcriptional regulators and revealing a principle of signal summation in prokaryotic gene regulation.

This paper designs and evolves synthetic syntrophic E. coli pairs using a novel algorithm, revealing metabolic changes that enhance community fitness and guide co-culture optimization.

The paper identifies 34% of Escherichia coli genes with no experimental evidence of function, termed the y-ome, and characterizes their properties.

COBRAme is a software framework for building and simulating ME-models, enabling efficient reconstruction and analysis of genome-scale models of metabolism and gene expression.

This study shows that enzyme promiscuity enables E. coli to adapt to novel substrates through computational modeling and lab evolution experiments.

BOFdat generates biomass objective function stoichiometric coefficients from omic data and calculates maintenance costs.