Guide#

The guide consists of short, task-focused pages: one job per page, three to eight functions, with MATLAB and Python side by side. Start at Getting started and continue in order, or go directly to the page for a task.

The guide ends with two older sets of material: a complete reconstruction protocol for H. polymorpha, followed from start to finish, and the legacy tutorials from the original RAVEN paper. Both are MATLAB only.

Functions from cobrapy#

Functions that come from cobrapy, not from 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 task 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 Setup section of the page.

Not executed: Reconstruction from KEGG, which downloads tens of megabytes and takes minutes, and the Human-GEM steps of Context-specific models with ftINIT, 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 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, in place of a script of function calls.

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

Reconstruction#

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

  2. Reconstruction from KEGG, a draft without a template model, and what such a draft is missing.

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

Analysis and repair#

  1. Metabolic tasks, defining what a model must be able to do, and checking that it keeps that ability.

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

  3. Gap-filling, closing the gaps in a draft model.

  4. Flux variability and alternative optima, how much each flux can vary, and which predictions the model fixes.

  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.

  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.

Protocol and legacy tutorials#

Resource

Description

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.

The task pages are for looking something up; the protocol shows a whole reconstruction in order.

Planned pages#

Compartment localisation has no page; the feature is in development and not at parity between the two toolboxes.