GEMsembler: consensus model assembly and structural comparison of genome-scale metabolic models across tools improve functional performance.

ABSTRACT: Genome-scale metabolic models (GEMs) are widely used in systems biology to investigate metabolism and predict perturbation responses. Automatic GEM reconstruction tools generate GEMs with different properties and predictive capacities for the same organism. Since different models can excel at different tasks, combining them can increase metabolic network certainty and enhance model performance. Here, we introduce GEMsembler, a Python package designed to compare cross-tool GEMs, track the origin of model features, and build consensus models containing any subset of the input models. GEMsembler provides comprehensive analysis functionality, including identification and visualization of biosynthesis pathways, growth assessment, and an agreement-based curation workflow. GEMsembler-curated cons

SUBMITTER: Matveishina EK 

PROVIDER: S-EPMC12542698 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature