biogacop / enhancing_gMCS

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How can I make a context-specific model ? #2

Open kavousisiavash opened 3 months ago

kavousisiavash commented 3 months ago

Hi , I am reading and running the codes of your article. But I have a question, for example, from a generic model like Human_1_17.mat, how did you make tissue-specific models like blood, kidney, heart, etc. models. As a rule, part of this work is related to the removal of some genes, reactions, and metabolites, but I don't think this work can be done individually.For example, if I have the Omics data for a part of the intestine, how can I create a context-specific model for the intestine with Cobrapy from Human_1_17.mat? In fact, I need a code written with Cobrapy package and help me for this. Best regards.

PacoAlgebra2 commented 3 months ago

Hi,

if you're interested in creating your own context-specific models, you will need Matlab. You can find a guide for doing so at https://sysbiochalmers.github.io/Human-GEM-guide/. As far as I know, there is no code for this task written in Cobrapy.

Best regards,

Francisco Gui


De: kavousisiavash @.> Enviado: martes, 13 de agosto de 2024 9:26 Para: biogacop/enhancing_gMCS @.> Cc: Subscribed @.***> Asunto: [biogacop/enhancing_gMCS] How can I make a context-specific model ? (Issue #2)

Hi , I am reading and running the codes of your article. But I have a question, for example, from a generic model like Human_1_17.mat, how did you make tissue-specific models like blood, kidney, heart, etc. models. As a rule, part of this work is related to the removal of some genes, reactions, and metabolites, but I don't think this work can be done individually.For example, if I have the Omics data for a part of the intestine, how can I create a context-specific model for the intestine with Cobrapy from Human_1_17.mat? In fact, I need a code written with Cobrapy package and help me for this. Best regards.

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kavousisiavash commented 3 months ago

Hello It is strange how a package based on Python does not provide such a possibility... Thank you very much for your guidance.