ArticleBioinformatics (Oxford, England)2023
Reconstructor: a COBRApy compatible tool for automated genome-scale metabolic network reconstruction with parsimonious flux-based gap-filling.
Article in Bioinformatics (Oxford, England), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- BioEMMA: Automated Generation of Model-Specific Escher-Compatible Maps from KEGG Pathways.Biology · 2026Article
- Environmental formermSystems · 2026Article
- Genome-scale metabolic modelling identifies vaginal microbiome members as potential probiotics.Nature microbiology · 2026Article
- Selecting methods for draft GEM generation in multicellular eukaryotes: a comparative analysis.BMC bioinformatics · 2026Article
- Water kefir as a paradigm for multi-omics and genome-scale metabolic modelling in fermented food.NPJ biofilms and microbiomes · 2026Review
- Article
- Evaluation of Genome-Scale Model Reconstruction Strategies forMetabolites · 2025Article
- Genome-scale metabolic network reconstruction analysis identifies bacterial vaginosis-associated metabolic interactions.Nature communications · 2025Article
- Niche-specific metabolic phenotypes can be used to identify antimicrobial targets in pathogens.PLoS biology · 2024Article
- Spatial transcriptome-guided multi-scale framework connects P. aeruginosa metabolic states to oxidative stress biofilm microenvironment.PLoS computational biology · 2024Article
- Top-down and bottom-up microbiome engineering approaches to enable biomanufacturing from waste biomass.Journal of industrial microbiology & biotechnology · 2024Review
- State-of the-Art Constraint-Based Modeling of Microbial Metabolism: From Basics to Context-Specific Models with a Focus on Methanotrophs.Microorganisms · 2023Review
- Metabolic Network Models of themSystems · 2023Article
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Authors and funding
3 authors.
Funding
Abstract
motivationGenome-scale metabolic network reconstructions (GENREs) are valuable for understanding cellular metabolism in silico. Several tools exist for automatic GENRE generation. However, these tools frequently (i) do not readily integrate with some of the widely-used suites of packaged methods available for network analysis, (ii) lack effective network curation tools, (iii) are not sufficiently user-friendly, and (iv) often produce low-quality draft reconstructions.
resultsHere, we present Reconstructor, a user-friendly, COBRApy-compatible tool that produces high-quality draft reconstructions with reaction and metabolite naming conventions that are consistent with the ModelSEED biochemistry database and includes a gap-filling technique based on the principles of parsimony. Reconstructor can generate SBML GENREs from three input types: annotated protein .fasta sequences (Type 1 input), a BLASTp output (Type 2), or an existing SBML GENRE that can be further gap-filled (Type 3). While Reconstructor can be used to create GENREs of any species, we demonstrate the utility of Reconstructor with bacterial reconstructions. We demonstrate how Reconstructor readily generates high-quality GENRES that capture strain, species, and higher taxonomic differences in functional metabolism of bacteria and are useful for further biological discovery. AVAILABILITY AND IMPLEMENTATION: The Reconstructor Python package is freely available for download. Complete installation and usage instructions and benchmarking data are available at http://github.com/emmamglass/reconstructor.
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