refactor: FSEOF

[ae-tafur]

Main improvements in this PR:

FSEOF implementation in GECKO 2 in summary fix % of the maximum growth and forced the rest of the carbon source towards product target. Nevertheless, original implementation (https://doi.org/10.1128/AEM.00115-10), same as RAVEN have, is the opposite. A maximum theoretical product is calculated, then this value is fixed to a different % of it, to further maximize the growth. Then, here FSEOF implementation is refactored to follow same as RAVEN since the cell will always have growth as objective.

Now:

• alpha (values to fix target production) vector from the minimum production to 90% of the maximum theoretical yield, in n steps defined by the user.

• k_score (mean of fold changes) is not longer calculated, then an slope value is calculated for each reaction which always increase or decrease while enforcing the objective

• Actions are suggested for reactions and gene targets. OE (ever expression) for those reaction that always increase; KD, for those that always decrease; KO, for those that always decrease but in the las step (90% of the maximum theoretical yield) are zero.

• Transport reactions, defined as reactions involving (at least) one metabolite name in more than one compartment. are reported in a new table.

• Gene targets predicted are checked for gene essentiality while maximizing growth and product target production.

Instructions on merging this PR:

• This PR has develop as target branch, and will be resolved with a squash-merge.
• This PR has main as target branch, and will be resolved with a merge commit.

[github-actions]

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.

[ae-tafur]

as suggested by @edkerk, gene essentially now is considered if growth is < 1e-8.