model.medium it only changes the importing direction's bound and doesn't modify the other bound. So that will stay as it was. So if the bounds of EX_glc_e were 0; 1000 and you set it to 10, the new bounds will be -10; 1000. No flux is enforced unless you do so yourself.
5 replies
Hey guys, I spotted sth in my model. when I set the light and organic compound uptake reactions to zero, my model still produces biomass is it coz my model is not energetically balanced?
it is only phosphate uptake that leads to zero biomass when it's blocked.
I also successively set the bounds of phosphate consuming and producing reactions to zero, and it's only phosphate producing reactions that result in zero biomass. How can I find the reason behind that? shall I check if the producing reactions also produce biomass precursors?
2 replies
Metabolite Reaction Flux Range C-Number C-Flux
arg_L[e] EX_arg_L[e] 0.0001106 [0.000105; 0.0001483] 6 1.37%
asn_L[e] EX_asn_L[e] 8.6E-05 [-756.8; 0.0001873] 4 0.71%
Metabolite Reaction Flux Range C-Number C-Flux
C02712[c] DM_C02712[c] 0 [-0.0001237; 0] 7 0.00%
adprbp[c] DM_adprbp[c] 0 [-284.2; 0] 15 0.00%
Hello, I was wondering if anyone has a "simple trick" to discover alternatives in minimal media with a statistical or algorithmic approach, rather than by-hand.
What I mean is, for my model I can generate many minimal media using cobra.medium.minimal_medium.
Often, it is obvious when I examine the resulting dataframe when there are two "choices" for one need. For example, I might see that the minimal media all have EX_LalaDgluMdapDala_e OR EX_LalaDgluMdap_e, but never both, and always one or the other.
But then there are more complicated cases, where there are >2 alternatives for the underlying need, and maybe some cases where in one minimal medium two underlying needs are met with one uptake, but in other minimal media two different uptakes perform these actions.
It feels like there should be some simple correlational "trick" to figure out these relationships. Any insight is appreciated, thanks for reading!
cobra supports Python 3.9 and 3.10 even though we have it in setup.cfg. Any ideas to get this corrected?
[Announcement] COBRApy community meeting 2022
Dear COBRApy community,
It is time for another community meeting. As always, feel especially welcome if you have not previously attended any of the calls. We will talk about future directions for the project and look forward to hearing from new users, as well as long term supporters.
If you want to participate, please choose a time slot here (you can adjust the timezone on the upper right):
We will also post a recording of the meeting on YouTube afterwards.
We have heard your feedback that the last meeting was a bit heavy on the organizational aspects of the project (management, funding, etc.). So, I propose to split the meeting into a development and organizational part of 30 minutes each. Let us know if you have any topics you would like to see on the Agenda. Some tentative agenda points follow below.
Best regards,
Christian on behalf of the COBRApy project
Agenda
Development
- Refactoring of the test/CICD suite
- What to address before or after the stable release of COBRApy X.0
- What is the community using COBRApy for and what are big unmet needs in the community that COBRApy should address?
- Omics data integration (some updates on DRIVEN)
Organization
- COBRApy manuscript updates
- Improve DEI in the project
- Mentoring for new contributors
- Implementation of the COC is completed
- A tutorial on contributing
2 replies
1) cobra.Model() with no name given makes name be None instead of empty string? Is there a good reason or I can change it for consistency with SBML behavior?
2) When saving to matlab, should subsystems be populated with group.id or group.name (assuming both exist)? MATLAB format files don't have groups, so some data will be lost either way.
2b) When reading, should the subsystems be checked for compliance with SBML IDs or should I leave it up to SBML for writing? I think leave it up to SBML, but I'm not sure.
Thank you
Dear COBRApy community
Thank you everybody for responding to the scheduling poll. Based on the responses, I have now fixed the meeting for Thursday, May 12th 2022 16:00 UTC / 9:00 PDT / 18:00 CEST. You can find the Zoom link and dial-in numbers below.
Unfortunately, this date did not work for everybody, but I will record it and upload it. You are also very much invited to send us additional agenda or talking points by adding them to the discussion on Github Discussions. The Meeting Notes can be found here.
Lastly, we would like to stress that this meeting is open to all members of the community, whether you have responded to the poll or not. So please feel free to join the meeting.
Best regards,
Christian on behalf of the COBRApy project
How to join?
Thursday, May 12th 2022 16:00 UTC / 9:00 PDT / 18:00 CEST
Zoom Meeting
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Meeting ID: 856 2814 8241
Passcode: 872494
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Tentative Agenda
Development
- Refactoring of the test/CICD suite
- What to address before or after the stable release of COBRApy X.0
- What is the community using COBRApy for and what are big unmet needs in the community that COBRApy should address?
- Omics data integration (some updates on DRIVEN)
Organization
- COBRApy manuscript updates
- Improve DEI in the project
- Mentoring for new contributors
- Implementation of the COC is completed
- A tutorial on contributing
4 replies
I'm trying to replicate the definition of metabolic tasks used in Richelle et al. 2019 in Python: "a model successfully passes a task if the associated LP problem is still solvable when the sole exchange reactions allowed carrying flux in the model are temporary sink reactions associated with each of the inputs and outputs listed in the task". The algorithm I've implemented is:
- set bounds of all boundary reactions to (0,0)
- add sink reactions for each of the inputs and outputs with the specified bounds
- set the sink reaction of the first output metabolite as the objective
- run slim_optimize()
However, the results I'm receiving are that the model is infeasible for every task, which is not consistent with what is seen when running similar tests using RAVEN Toolbox. Is there something obvious I'm doing wrong here?