Topology

• Extremerays
  • Optimalrays
  • Lrs
    • Lrsinterface
• Conservedmoieties
  • Old
• Graphhypergraphconversion
• Fr

connectedComponents(model, type, figures, files)

Assuming two reactions are connected if they share metabolites, calculates the connected components in the stoichiometric matrix, that is, the sets of reactions that share a set of metabolites

USAGE

[groups, orphans, R, C] = connectedComponents (model, type, figures)

INPUT

model

OPTIONAL INPUTS

• type – {(‘allComponents’), ‘largestComponent’}

• figures – Will generate plots of the grouping algorithm as it creates block diagonal groups in from top left to bottom right in W.

• files – Indicator, whether several files containing indicator matrices are generated.

OUTPUTS

• groups – a structure array (the number of distinct groups is length(groups)) with fields:

  • groups(i).num_els - number of reactions in group i.

  • groups(i).block - sub-block identity of group i.

  • groups(i).elements - reactions of W that are in group i.

  • groups(i).degrees - degrees of connection for each reaction in group i.

• orphans – elements of W that were not in any group, becasue they did not meet the constraints.

• R – reaction adjacency

• C – compound adjacency

All components require: Connected Component Analysis on an Undirected Graph by Tristan Ursell http://www.mathworks.com/matlabcentral/fileexchange/35442-connected-component-analysis-on-an-undirected-graph.

Largest component requires: gaimc : Graph Algorithms In Matlab Code by David Gleich http://www.mathworks.com/matlabcentral/fileexchange/24134-gaimc-graph-algorithms-in-matlab-code.

findCyclicRxns(model, printLevel)

Computes the reactions that are part of one or more stoichiometrically balanced cycles in the network

USAGE

[cyclicRxnBool, rankS] = findCyclicRxns (model, printLevel)

INPUT

• model – model structure

• printLevel – verbose level

OUTPUTS

• cyclicRxnBool – boolean value

• rankS – scalar giving rank of S

getCorrespondingCols(S, rowBool, colBool, mode)

Returns a boolean vector that is true for a subset of the true cols in colBool according to whether the cols ‘exclusive’, ‘inclusive’, or ‘partial’ -ly correspond to true entries in rowBool

USAGE

restrictedColBool = getCorrespondingCols (S, rowBool, colBool, mode)

INPUTS

• S – m x n stoichiometric matrix

• rowBool – m x 1 boolean vector

• colBool – n x 1 boolean vector

• mode – ‘exclusive’ or ‘inclusive’ or ‘partial’

OUTPUT

restrictedColBool – n x 1 boolean vector

Example

S =

-1

0 0 0 0 2 -3 0 0 0 0 4 -5 0 0 0 0 6 -7 0 0 0 0 0 0

rowBool = [1; 1; 1; 0; 0]; colBool = [1; 1; 1; 1; 1];

%Therefore, the subset of rows and columns considered for inclusion are % -1 0 0 0 0 % 2 -3 0 0 0 % 0 4 -5 0 0

%If mode = ‘exclusive’ then restrictedColBool corresponds to this subset % -1 0 % 2 -3 % 0 4 %i.e. subset of colBool reactions exclusively involving rowBool metabolites

%If mode = ‘inclusive’ then restrictedColBool corresponds to this subset % -1 0 0 % 2 -3 0 % 0 4 -5 %i.e. subset of colBool reactions involving at least one rowBool metabolite

%If mode =’partial’ then restrictedColBool corresponds to the extra cols %with inclusive that are not present with exclusive.

getCorrespondingRows(S, rowBool, colBool, mode)

Returns a boolean vector that is true for a subset of the true rows in rowBool according to whether the rows ‘exclusive’, ‘inclusive’, or ‘partial’ -ly correspond to true entries in colBool

USAGE

restricedRowBool = getCorrespondingRows (S, rowBool, colBool, mode)

INPUTS

• S – m x n stoichiometric matrix

• rowBool – m x 1 boolean vector

• colBool – n x 1 boolean vector

• mode – ‘exclusive’ , ‘inclusive’ or ‘partial’

OUTPUT

restrictedRowBool – m x 1 boolean vector

Example

S =

-1

0 0 0 0 2 -3 0 0 0 0 4 -5 0 0 0 0 6 -7 0 0 0 0 0 0

rowBool = [1; 1; 1; 1; 1]; colBool = [1; 1; 1; 0; 0];

% Therefore, the subset of rows and columns considered for inclusion are % -1 0 0 % 2 -3 0 % 0 4 -5 % 0 0 6 % 0 0 0

% If mode = ‘exclusive’ then restrictedRowBool corresponds to this subset % -1 0 0 % 2 -3 0 % 0 4 -5 % i.e subset of rowBool metabolites exclusively involved in the colBool % reactions

% If mode = ‘inclusive’ then restrictedRowBool corresponds to this subset % -1 0 0 % 2 -3 0 % 0 4 -5 % 0 0 6 % i.e subset of rowBool metabolites involved in colBool reactions

% If mode =’partial’ then restrictedRowBool corresponds to the extra rows % with inclusive that are not present with exclusive.

integerizeS(model, printLevel, internalRxnsOnly)

convert an S matrix with some non integer coefficients into an S matrix with all integer coefficients assumes that there are a maximum of six significant digits in the biomass reaction

INPUT

S stoichiometric matrix

OPTIONAL INPUT

internalRxnsOnly (1),0. 1 = integerise internal reactions only

OUTPUT

S stoichiometric matrix with internal reactions integers, unless internalRxnsOnly =0, whence all reactions will be integerised g scaling vector such that modelIn.S*diag(g)=modelOut.S;

matrixCoherence(A)

Computes the coherence of a matrix A, that is the maximum absolute value of the cross correlations between the columns of A

USAGE

[mu, Q] = matrixCoherence (A)

INPUT

A – Matrix

OUTPUTS

• mu – coherence

• Q – matrix used by mu

testForTypeIIIPathways(model, ListExch, filename)

Sets up the model to run extreme pathway analysis (expa) for identifying loops in the model (Type III pathways) and runs expa.

USAGE

testForTypeIIIPathways (model, ListExch, filename)

INPUTS

• model – COBRA model structure

• ListExch – List of position of exchange reactions in S matrix

• filename – name of the file