ArticleGenome biology2019
A systematic assessment of current genome-scale metabolic reconstruction tools.
Article in Genome biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 120 papers, 2 of them syntheses that pooled it.
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Who cites it
120 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- A human gut metagenome-assembled genome catalogue spanning 41 countries supports genome-scale metabolic models.Nature microbiology · 2026Pooled it
- Leveraging genome-scale metabolic models to understand aerobic methanotrophs.The ISME journal · 2024Pooled it
- BioEMMA: Automated Generation of Model-Specific Escher-Compatible Maps from KEGG Pathways.Biology · 2026Article
- AlphaGEM enables precise genome-scale metabolic modelling by integrating protein structure alignment with deep-learning-based dark metabolism mining.Nature communications · 2026Article
- Nutrient control enables metabolic reconstruction ofbioRxiv : the preprint server for biology · 2026Article
- Selecting methods for draft GEM generation in multicellular eukaryotes: a comparative analysis.BMC bioinformatics · 2026Article
- NAViFluX: a visualization‑centric platform for interactive analysis, refinement and design of genome‑scale metabolic networks.Bioinformatics (Oxford, England) · 2026Article
- Defining metabolic niches for marine microbial heterotrophs.Science advances · 2026Article
- High-throughput generation and comparison of genome-scale metabolic models reveal strain-specific metabolic diversity in 439mSystems · 2026Article
- Water kefir as a paradigm for multi-omics and genome-scale metabolic modelling in fermented food.NPJ biofilms and microbiomes · 2026Review
- Screening of exogenous nutrients for pathogenic bacteria and development of highly active bactericides.mSystems · 2026Article
- Basic Microbiome Analysis: Analytical Steps from Sampling to Sequencing.Microorganisms · 2026Review
- Substrate utilization and cross-feeding synergistically determine microbiome resistance to pathogen invasion.Nature ecology & evolution · 2026Article
- Virtual Colon: spatiotemporal modeling of metabolic interactions in a computational colonic environment.mSystems · 2026Article
- Gempipe: a tool for drafting, curating, and analyzing pan and multi-strain genome-scale metabolic models.mSystems · 2026Article
- Advances in natural product discovery: strategies, technologies, and insights.Natural products and bioprospecting · 2026Review
- Precision nutrition through diet-gut microbiome interactions: Emerging insights driven by artificial intelligence, microbiome health metrics, and mechanistic modeling.Gut microbes reports · 2026Review
- From Genome to Function: Metabolism-Wide Models of Lifecycle Stages of Parasites.Methods in molecular biology (Clifton, N.J.) · 2026Article
- Evaluating Metabolic Support in Pairwise Microbial Communities Using MetQuest.Methods in molecular biology (Clifton, N.J.) · 2026Article
- Evaluation of Genome-Scale Model Reconstruction Strategies forMetabolites · 2025Article
60 more citing papers are in PubMed but not listed here.
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4 authors.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundSeveral genome-scale metabolic reconstruction software platforms have been developed and are being continuously updated. These tools have been widely applied to reconstruct metabolic models for hundreds of microorganisms ranging from important human pathogens to species of industrial relevance. However, these platforms, as yet, have not been systematically evaluated with respect to software quality, best potential uses and intrinsic capacity to generate high-quality, genome-scale metabolic models. It is therefore unclear for potential users which tool best fits the purpose of their research.
resultsIn this work, we perform a systematic assessment of current genome-scale reconstruction software platforms. To meet our goal, we first define a list of features for assessing software quality related to genome-scale reconstruction. Subsequently, we use the feature list to evaluate the performance of each tool. To assess the similarity of the draft reconstructions to high-quality models, we compare each tool's output networks with that of the high-quality, manually curated, models of Lactobacillus plantarum and Bordetella pertussis, representatives of gram-positive and gram-negative bacteria, respectively. We additionally compare draft reconstructions with a model of Pseudomonas putida to further confirm our findings. We show that none of the tools outperforms the others in all the defined features.
conclusionsModel builders should carefully choose a tool (or combinations of tools) depending on the intended use of the metabolic model. They can use this benchmark study as a guide to select the best tool for their research. Finally, developers can also benefit from this evaluation by getting feedback to improve their software.
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