Guide#

Short, task-focused pages: one job per page, three to eight functions, in MATLAB and Python side by side. Start at Getting started and read on, or jump to whichever task you are working on.

Two older sets of material appear at the end of this section: a complete reconstruction protocol for H. polymorpha, followed start to finish, and the legacy tutorials from the original RAVEN paper. Both are MATLAB only.

cobrapy

Functions that come from cobrapy rather than raven-toolbox carry a cobrapy badge, their import line shows where they live (from cobra.io import read_sbml_model), and the badge links to the cobrapy documentation. The function mapping lists every such function.

Executed examples

The code on the numbered pages is run, MATLAB and Python separately, by the Guide examples workflow whenever a guide page, the example data or the runner changes, and once a week against the latest RAVEN and raven-toolbox. A run fails when a block errors or prints something other than the output shown beneath it. The blocks on a page run in order in one session, so later blocks use what earlier ones made: start from the page's Setup.

Not executed: 13. Reconstruction from KEGG, which downloads tens of megabytes and takes minutes, and the Human-GEM steps of 14. Context-specific models, which take hours. A few other blocks are marked on their page as not run, with the reason. Both pages quote the run their numbers came from. The protocol and the legacy tutorials at the end of this section are MATLAB-only and are not executed.

Example data#

File

What it is

smallYeast.yml

central carbon metabolism in yeast; the default example

smallYeastBad.yml

the same model with deliberate errors, for the curation pages

empty.xml

an empty model with compartments, for building one from scratch

yeast-GEM.yml

yeast-GEM v9.1.0, the consensus S. cerevisiae model, for pages that need a genome-scale one

yeast-GEM.xml

the same model as SBML

anaerobic.yml

a condition file: yeast-GEM under anaerobic conditions

Pages#

Foundations

  1. Getting started, load a model and inspect it.

  2. Model structure and identifiers, how the RAVEN struct and cobra.Model correspond, field by field.

  3. Reading and writing models, SBML, RAVEN YAML, Excel, text, and the layout a model repository expects.

Simulation

  1. Simulating growth with FBA, objective, bounds, solve, read the fluxes.

  2. Growth media and conditions, define a medium, keep a condition as data.

  3. Solvers and configuration, which solver, and how to read what it returns.

Building and curating

  1. Building a model from scratch, metabolites, reactions, genes, exchanges.

  2. Editing an existing model, stoichiometry, GPRs, bounds, deletions.

  3. Quality control, structure, mass balance, blocked reactions, mass from nothing.

  4. Table-driven curation, applying curation as reviewable tables rather than a script of function calls.

  5. Biomass composition and annotation, what the cell is made of, rescaling it, and the annotation that stays useful after the solve.

Reconstruction

  1. Reconstruction from homology, BLAST a proteome against a template model's genes, and what the cut-offs decide for you.

  2. Reconstruction from KEGG, a draft with no template model at all, and what such a draft is missing.

  3. Context-specific models (ftINIT), omics integration and extracting a cell-line model from Human-GEM and RNA-seq, end to end.

Analysis and repair

  1. Metabolic tasks, saying what a model must be able to do, and checking that it still can.

  2. Deletions and essentiality, knockouts, essential genes and reactions, MOMA.

  3. Gap-filling, closing the holes a draft model has.

  4. Flux variability, how much each flux can still move, and which predictions the model has no choice about.

  5. Random sampling, the distribution behind those ranges, and how to condition it on a particular state.

Comparing and engineering

  1. Combining and simplifying models, merging models on metabolite names, and taking one apart again.

  2. Comparing models, what changed between two models, and what effect that difference has.

  3. Engineering targets, FSEOF for over-production targets and reporter metabolites for the metabolites a transcriptional response surrounds.

Also in this section#

GEM reconstruction protocol, H. polymorpha

homology-based reconstruction of hanpo-GEM, end to end, from template models to a growing methylotrophic draft. A published pipeline followed from start to finish. MATLAB only, not executed here.

Legacy tutorials

five exercises from the original RAVEN paper (Agren et al., 2013), updated to run with current RAVEN but otherwise unchanged. MATLAB only.

Use the numbered pages to look something up; use the protocol to see a whole reconstruction in order.

Not yet written: compartment localisation, which is still in development and not yet at parity between the two toolboxes.