Gregory L. Medlock

Comparative analyses of parasites with a comprehensive database of genome-scale metabolic models

The paper presents a comparative analysis of 192 protozoan parasite genomes using a metabolic network reconstruction pipeline to identify species-specific metabolic differences and improve experimental system selection.

Medusa: software to build and analyze ensembles of genome-scale metabolic network reconstructions

Medusa is a Python package that generates and analyzes ensembles of genome-scale metabolic network reconstructions, enabling ensemble simulations and machine learning-guided curation.

Memote: A community-driven effort towards a standardized genome-scale metabolic model test suite

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.

Guiding the Refinement of Biochemical Knowledgebases with Ensembles of Metabolic Networks and Machine Learning

The paper develops a machine learning approach to guide curation of metabolic models by identifying structural variants that improve predictiveness across bacterial species.

Functional Anabolic Network Analysis of Human-associated Lactobacillus Strains

This study introduces PROTEAN, a method to analyze metabolic capabilities of Lactobacillus strains, revealing site-specific differences in predicted metabolic production.