About the examples¶
The screenshots and numbers in this documentation come from real runs of GEMs MAP, captured automatically from the running application. Nothing is mocked or edited, except that transient notifications are hidden and numbered callouts are added to some images. This page records what was used, so that every value can be reproduced and checked.
The model: E. coli iML1515¶
| Organism | Escherichia coli str. K-12 substr. MG1655 |
| Model | iML1515 (Monk et al., 2017), from BiGG Models |
| File | iML1515.json, the classic BiGG COBRA JSON export (http://bigg.ucsd.edu/static/models/iML1515.json; BiGG lists it as last updated 31 Oct 2019) |
| SHA-256 | b0f9199f048779bb08a14dfa6c09ec56d35b8750d2f99681980d0f098355fbf5 |
| Size in GEMs MAP | 2,712 reactions · 1,877 metabolites · 1,516 genes · 3 compartments · 40 subsystems |
| Objective | maximise BIOMASS_Ec_iML1515_core_75p37M (from the file) |
| Medium | from the file: 24 compounds may be taken up; D-glucose ≤ 10 mmol gDW⁻¹ h⁻¹; O₂ and the other compounds ≤ 1000 |
iML1515 is a published model by its authors; it is used here only as a well-known, openly available example.
Which iML1515 file?
The new BiGG site also offers iML1515.biggr.sbml / *.biggr.json exports. These carry fewer annotations and no subsystems, so the Subsystems views would be empty. The classic JSON used here has a subsystem on every reaction.
Software¶
| GEMs MAP | development version of 12 October 2026, just before 0.3.0b1 (the manifests record the build) |
| COBRApy | 0.32.1 |
| Solver | GLPK (COBRApy's default in the backend environment) |
| Browser | Microsoft Edge (Chromium), headless, 1600 × 900 px at 1.5× |
| Date | 10 October 2026, recaptured on 12 October 2026 |
The complete record of every capture, including the text the application displayed for the key values, is in docs/assets/images/capture-manifest.json. The capture script is tools/docs/capture_screenshots.py (see Contributing to the docs).
Values shown in the pages¶
| Run | Configuration | Displayed result |
|---|---|---|
| pFBA, aerobic | Base model (file medium and bounds), fraction of optimum 1 | Optimal; objective 0.876997 h⁻¹; Σ|flux| 769.79; 431 of 2,712 reactions active |
| pFBA, anaerobic | State Anaerobic = Base model with Anaerobic medium preset (EX_o2_e uptake 1000 → 0) |
Optimal; objective 0.15754 h⁻¹; Σ|flux| 414.634; 433 reactions active |
| Comparison | A = aerobic pFBA, B = anaerobic pFBA, zero threshold 10⁻⁹, no pseudocount | 392 changed, 24 activated from zero, 22 inactivated to zero, 13 direction reversals, 4 unchanged |
| FVA | 14 reactions of subsystem Citric Acid Cycle, fraction of optimum 1, Base model | Optimal; objective 0.876997 |
Pyruvate (pyr_c) |
aerobic pFBA | turnover 12.4614 mmol gDW⁻¹ h⁻¹; 70 reactions, 16 with flux |
Acetyl-CoA (accoa_c) |
aerobic → anaerobic | turnover 10.296 → 18.262 mmol gDW⁻¹ h⁻¹ |
| Template | Global central carbon metabolism on iML1515, before MetaNetX curation | 25 mapped, 1 to review (D-ribose 5-phosphate → r5p_c, Medium), 0 open |
| Metabolite analysis | MetaNetX + local BiGG tables, default options | 1,577 confident and curated (+4,645 cross-references), 300 to review, 0 unmapped |
Reproducibility of individual fluxes
Objective values are reproducible. Individual fluxes of FBA and pFBA solutions, and the counts derived from them, can differ between runs because of alternative optima. Two captures of the same comparison gave 391 and 392 changed reactions. Treat the per-reaction numbers as one valid solution.
The tutorial model: E. coli iJO1366¶
The quick start tutorial uses iJO1366 (Orth et al., 2011), the predecessor of iML1515, from the classic BiGG export http://bigg.ucsd.edu/static/models/iJO1366.json (SHA-256 9376a93f62ad430719f23e612154dd94c67e0d7c9545ed9d17a4d0c347672313): 2,583 reactions, 1,805 metabolites, 1,367 genes, 39 subsystems. With the medium of the file, pFBA gives 0.982372 h⁻¹ with oxygen and 0.241502 h⁻¹ with the oxygen uptake set to 0. All values displayed during the tutorial capture are in docs/assets/images/tutorials/quickstart-manifest.json.
Reference¶
Orth JD, Conrad TM, Na J, Lerman JA, Nam H, Feist AM, Palsson BØ (2011). A comprehensive genome-scale reconstruction of Escherichia coli metabolism—2011. Molecular Systems Biology 7:535. doi:10.1038/msb.2011.65
Monk JM, Lloyd CJ, Brunk E, et al. (2017). iML1515, a knowledgebase that computes Escherichia coli traits. Nature Biotechnology 35:904–908. doi:10.1038/nbt.3956
King ZA, Lu J, Dräger A, et al. (2016). BiGG Models: a platform for integrating, standardizing and sharing genome-scale models. Nucleic Acids Research 44:D515–D522. doi:10.1093/nar/gkv1049