Usage of stoichiometric matrix and kinetic information #175
Replies: 3 comments 4 replies
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The stoichiometric matrix can be used to detect possible combinations of fluxes that can lead to steady states. from biomass import Text2Model
import sympy
model = Text2Model("test.txt")
model.convert(overwrite=True)
# transform to sympy matrix
stoichiometry = sympy.Matrix(model.stoichiometry)
# compute nullspace/kernel, returns list of matrix, transform to sympy matrix
steadystates = sympy.Matrix([stoichiometry.nullspace()])
possible_states = steadystates * sympy.ones(steadystates.shape[1], 1) # calculate row sum For the toy model:
the code above returns [1, 1, 0], indicating that A --> B and B --> A need to have equal flux, while the synthesis of A needs to be 0. I think this would be very useful information in the initial model generation. |
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I would like to change how graphs are drawn. |
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TODO:
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I opened this discussion to talk about potential uses of the stoichiometric matrix and kinetic information.
I would like to add every possible usage as a separate comment thread in this discussion.
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