MATLAB vs Python#
GECKO ships as a MATLAB toolbox and as the Python package geckopy. This page is generated from the source of both toolboxes at build time. Pairs are found automatically where the names match, completed from a curated list where they do not, and marked with a cobrapy badge where cobrapy covers the function instead of geckopy. Every name is verified to exist.
Paired functions#
79 GECKO functions listed: 70 matched automatically, 9 from a curated list, 0 covered by cobrapy instead of geckopy.
GECKO (MATLAB) |
geckopy (Python) |
Summary |
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KEY_CLASSNAME Template ModelAdapter to copy and adapt per organism. |
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Add new reactions to an enzyme-constrained model. |
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Apply complex subunit stoichiometry to an ecModel. |
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Apply user-defined kcats to an ecModel. |
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Apply kcat-derived enzyme constraints to an ecModel. |
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Assign kcats from the kcat source files and apply them. |
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Select one kcat value per reaction and write to model.ec. |
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The fewest-changes point whose RMSE is within |
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Compute the f factor for an ecModel. |
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Calculate the molecular weight of a protein. |
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Tune kcats against experimental data with CMA-ES. |
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Decide one kcat per reaction from the kcat source files. |
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Constrain enzyme usages by their concentration. |
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Constrain ecModel fluxes to provided flux data. |
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Convert data/customKcats.tsv into data/kcats/custom.tsv. |
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Download a KEGG organism's gene data and write a CSV. |
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Download UniProt protein data for an organism and write a TSV. |
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Run Flux-Scanning with Enforced Objective Function for a target. |
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Run flux variability analysis on an ecModel. |
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Summarise loadBRENDAdata's output per EC number, for |
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The enzyme-substrate pairs of an ecModel's reactions. |
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Download (once) GECKO's BRENDA files and return their folder. |
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Fetch and parse an OpenKineticsPredictor job. |
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Populate model.ec.concs from proteome data. |
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Look up EC numbers for a reaction's gene set in a UniProt or KEGG index. |
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Query PubChem by metabolite names to obtain SMILES. |
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Flexibilize enzyme concentrations of an ecModel. |
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Match model EC numbers and substrates to BRENDA kcats. |
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Download curated complex stochiometries from Complex Portal. |
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Calculate control coefficients of protein usage. |
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Populate model.ec.eccodes from UniProt and KEGG databases. |
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Populate model.ec.eccodes from the model.eccodes field. |
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Top-N enzymes limiting the current objective. |
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Fill missing kcats from isozymes of the same reaction. |
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Get all reactions annotated to a particular enzyme. |
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Assign standard kcat and MW to reactions without enzymes. |
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Generate a context-specific ecModel from a general one. |
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Index of the parameter each isozyme copy follows. |
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The kcat assignment settings of a model adapter. |
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Gather kcats from BRENDA and keep them as a source file. |
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Gather kcats from DLKcat and keep them as a source file. |
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Estimate kcats from the EC tree and keep them as a source file. |
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Estimate kcats from measured homologs and keep them as a source file. |
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Gather kcats from OpenKineticsPredictor and keep them as a source file. |
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Load kcat and specific activity data from BRENDA files. |
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Load the BRENDA measurement table. |
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Load the conventional GEM (non-ecModel). |
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Load the ecModel that matches the modelAdapter. |
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Load experimental data for evotune (CMA-ES) kcat tuning. |
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Load total protein measurements and exchange flux data. |
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Read a kcat source file and map its rows to an ecModel. |
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Load absolute proteomics data and average over replicates. |
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Expand a conventional GEM into a basic ecModel. |
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Map ecModel fluxes back to the conventional starting model. |
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Merge DLKcat and BRENDA fuzzy matching results. |
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Merge any number of kcatLists, keeping the highest-priority |
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Abstract base class for species-specific model adapters. |
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Resolve and cache the active ModelAdapter. |
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How many kcats differ from their prior by more than relTol. |
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Score kcat with progressively more of it reverted to |
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Read the DLKcat output file into a kcatList structure. |
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Greedy shadow-price-ordered relaxation of proteomics |
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Remove the standard pseudoenzyme and standard kcats. |
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Summarize the results from getEnzymeUsage. |
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Run DLKcat to predict kcat values from a Docker image. |
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Save an ecModel in YAML and/or SBML format. |
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Write a kcatList to a kcat source file of the project. |
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Report which kcats the data can actually speak to. |
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Build a tunableMask from a screenKcatLeverage report. |
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Relax the most limiting kcats to reach a growth rate. |
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Change the kcat value for selected reactions. |
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Set the limit of the total protein usage in the model. |
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Fit the average enzyme saturation factor of an ecModel. |
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Submit a kcat prediction job to OpenKineticsPredictor. |
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Round values in selected columns to six significant digits. |
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Sweep priorPenaltyWeight and report the |
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Gather the kcat sources that the configuration needs. |
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Bring an ecModel made with GECKO 3 to the GECKO 4 format. |
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Prepare and write the input file for DLKcat. |
Deliberately not ported#
GECKO (MATLAB) |
Why not |
|---|---|
Plots an ecFVA flux range directly from the result; geckopy returns the ec_fva DataFrame and leaves plotting to matplotlib or seaborn directly. |
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Parses a downloaded OpenKineticsPredictor result file. geckopy replaced the file round-trip with a REST client (submit_open_kinetics_predictor / fetch_open_kinetics_predictor); the equivalent parsing is internal to that client. |
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Obsolete since GECKO 3.2.0; setProtPoolSize (geckopy set_prot_pool_size) supersedes it. |
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Builds an OpenKineticsPredictor request file. geckopy replaced the file round-trip with a REST client; the equivalent request-building is internal to that client. |
Not yet mapped#
23 GECKO functions are not yet recorded here.
applyECcodes, buildGECKOdoc, convertAdapterToToml, createGECKOproject, ecTreeEstimate, evotuneScore,
fillCarbonNum, findGECKOroot, getEcRxnKeys, getECstring, getEnzymeUsage, getPfbaEnzymes,
loadAdapterParams, loadDatabases, parseGECKOargs, readAdapterToml, resolveKcatAggregation, resolveOkpApiKey,
resolveTunableContext, reviewKcatAssignment, TomlAdapter, upgradeGECKOproject, writeAdapterToml