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Introduced preprocessing wrapper function
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jchitpin committed Nov 12, 2024
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{"documenter":{"julia_version":"1.10.4","generation_timestamp":"2024-11-12T11:05:44","documenter_version":"1.7.0"}}
{"documenter":{"julia_version":"1.10.4","generation_timestamp":"2024-11-12T14:39:50","documenter_version":"1.7.0"}}
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"tutorials/chmc-standard-metabolic-networks.md",
"tutorials/chmc-standard-ion-channels.md",
"tutorials/chmc-atomic-glucose.md",
"tutorials/chmc-atomic-glucose-under-the-hood.md",
"tutorials/boilerplate-for-bigg-gems.md",
],
"Library" => Any[#
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# Boilerplate code for ACHMC analysis of BiGG models

The following code is provided to quickly construct ACHMC models of BiGG
metabolic models and others stored in the SBML file format. Each code
block is designed to be standalone with calculations saved to file and
re-loaded in a subsequent code block. Unfortunately, BiGG does not store
SMILES strings so these will need to be manually compiled by the user.
The following code is provided to construct ACHMC models of BiGG metabolic
models (and others) stored in the SBML file format. Each code block is
designed to be standalone with calculations saved to file and re-loaded in
a subsequent code block. Since metabolic models can be quite complex,
individual pre-processesing functions are used rather than the wrapper
function `preprocess_all_for_atomic_chmc`. Unfortunately, BiGG does not
store SMILES strings so these will need to be manually compiled by the
user.

Note we recommend starting with relatively small networks (<500
metabolites and reactions in the original metabolic model) for
computational feasibility.
metabolites and reactions in the original metabolic model) for computational
feasibility before scaling to larger ones.

## Inputs (from BiGG)

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