SysBioChalmers / GECKO

Toolbox for including enzyme constraints on a genome-scale model.
http://sysbiochalmers.github.io/GECKO/
MIT License
64 stars 46 forks source link

docs: futher polishing #335

Closed mihai-sysbio closed 1 year ago

mihai-sysbio commented 1 year ago

Main improvements in this PR:

This PR is used to highlight a few places where the tutorials can be further improved/simplified. Please feel free to push commits to this branch.

I hereby confirm that I have:

github-actions[bot] commented 1 year ago

This PR has been automatically tested with GH Actions. Here is the output of the tests:

 
Running geckoCoreFunctionTests
Done geckoCoreFunctionTests
__________

Note: In the case of multiple test runs, this post will be edited.

mihai-sysbio commented 1 year ago

It takes less than 10 min to run the light tutorial now, great job 🌟 (I know it's using a lot of pre-computed values in the TSV files, but we do provide ways to reproduce them directly in the tutorial)

mihai-sysbio commented 1 year ago

The order of installing GECKO and checking the RAVEN installation is different in the 2 tutorials. Any insight into which is preferred?

mihai-sysbio commented 1 year ago

In STEP 22 of the full tutorial

sol = solveLP(ecModel)

prints a growth rate of 0.0887, which very close to 0.0889 but still different. Any reactions?

mihai-sysbio commented 1 year ago

I've ran both tutorials several times in less than 1 hour in total, very convenient 🤩

edkerk commented 1 year ago

The order of installing GECKO and checking the RAVEN installation is different in the 2 tutorials. Any insight into which is preferred?

Best to have RAVEN first, as GECKO will do a check that RAVEN can be found, I'll swap it.

In STEP 22 of the full tutorial

sol = solveLP(ecModel)

prints a growth rate of 0.0887, which very close to 0.0889 but still different. Any reactions?

I'll slightly rephrase it to avoid mentioning precise numbers.