Thermoqp

driver_testThermoQP[source]

Driver script that exercises thermoQP on the E. coli core model, setting up the objective and stoichiometric-consistency information before solving.

thermoFlux2QNty(model, solution, param)[source]

Given a steady state thermodynamically feasible flux vector, v, such that

S*v = b

l <= v <= u

Compute q and g = N’*y such that

N*diag(q)*g = b - B*w

where the stoichiometric matrix and flux vector are split into internal and external components: S = [N B] and v = [z; w],

USAGE:

[q, g, solutionQP] = thermoFlux2QNty (model, solution, param)

INPUTS:

  • model – COBRA model with fields:

    • .S - m x n stoichiometric matrix

    • .K - matrix whose transpose is used to construct the thermodynamic QP

    • .SConsistentMetBool - m x 1 boolean, stoichiometrically consistent metabolites

    • .SConsistentRxnBool - n x 1 boolean, stoichiometrically consistent reactions

    • .SIntMetBool - m x 1 boolean, true for internal metabolites

    • .SIntRxnBool - n x 1 boolean, true for internal reactions

  • solution – a solution structure providing the steady-state flux vector (.v)

OPTIONAL INPUT:

param – a structure containing the parameters for the function:

  • .SConsistentMethod - method used to identify the stoichiometrically consistent subset if not already present (‘findSExRxnInd’ or ‘findStoichConsistentSubset’)

  • .printLevel - verbose level controlling printed output

  • .bigNum - large positive number used as a bound in the QP (Default: 1)

OUTPUTS:

  • q – n x 1 vector of thermodynamic quantities per reaction

  • g – n x 1 vector g = N’*y satisfying N*diag(q)*g = b - B*w

  • solutionQP – the QP solution structure returned by solveCobraQP

thermoQP(model, q, param)[source]

Compute an approximately thermodynamically feasible flux by minimising the Euclidean norm, weighted by the conductances provided in q.

USAGE:

sol = thermoQP (model, q, param)

INPUTS:

  • model – COBRA model with the following required fields (others can be supplied):

    • .S - m x n stoichiometric matrix

    • .c - n x 1 linear objective coefficients

    • .lb - n x 1 lower bounds

    • .ub - n x 1 upper bounds

    • .b - m x 1 accumulation (right hand side of S*v = b)

    • .osense - objective sense as a number (-1 maximise, +1 minimise)

    • .osenseStr - objective sense as a string (‘max’ or ‘min’; default ‘max’)

    • .SConsistentRxnBool - n x 1 boolean, stoichiometrically consistent reactions

    • .SIntRxnBool - n x 1 boolean, true for internal reactions

  • q – n x 1 vector of reaction conductances

OPTIONAL INPUTS:

  • model – the following optional fields are also used:

    • .dxdt - m x 1 change in concentration with time

    • .csense - m x 1 character array with entries in {L,E,G} (backward compatible with an m + k x 1 csense vector, where k is the number of coupling constraints)

    • .C - k x n left hand side of C*v <= d

    • .d - k x 1 right hand side of C*v <= d

    • .dsense - k x 1 character array with entries in {L,E,G}

  • param – a structure containing the parameters for the function:

    • .printLevel - verbose level controlling printed output

    • .fbaOptimal - if true, first solve an FBA to define the external flux

    • .param - nested parameter sub-structure read by the function (e.g. .param.printLevel)

OUTPUT:

sol – solution object with fields:

  • .f - objective value

  • .v - reaction rates (optimal primal variable, legacy FBAsolution.x)

  • .y - dual variables

  • .w - reduced costs

  • .s - slacks

  • .stat - solver status in standardized form