Created by Ming Wu, 07/30/2012

I suggest reading *Protocol [Novel approach to reconstruct context dependent metabolic network] before this protocol*, because the pipeline is built based on the novel approach that I developed.

A matrix is needed to provide: each row is a miRNA, for each miRNA, its targets (Entrez gene ID) in the metabolic system are listed as a vector.

An example variable is shown in here:

Refer to our paper and protocol for reconstruct context dependent network to know GIMME.

our code for the pipeline is here:

*TissueS_miRNA_biomass.m*

[MetaGeneTable,F0,vF1,diFF]=TissueS_miRNA_biomass(expressionData,miRNA_target, model);

gene expression data (MATLAB structure variable), miRNA_target matrix, and the context dependent model to start from (e.g. a tissue specific cancer model).

MetaGeneTable extracts metabolic gene targets from miRNA_target matrix.

F0 is the max value of objective function for the unperturbed model.

vF1 is a vector in which each element is the max value of objective function for the corresponding miRNA (overexpression/delivery of the miRNA)

Refer to our paper to know the theory of the approach.

our code for the pipeline is here:

*predictMIRNA_FC_single_flux.m**UB_update_withFC.m*

[diFF,flux00,fluxAll,diffF]=predictMIRNA_FC_single_flux(Model,expressionData, miRNA_target, ParsedGPR, Prxn);

flux00 is a vector representing the flux distribution for each reactions for the unperturbed model.

fluxAll are vectors representing flux distributions for every of the perturbed model corresponding to each miRNA. Each column is a flux vector for a miRNA perturbation.

diffF is the differences between each vector in fluxAll and flux00.

For further analysis, the pipeline can also be applied to identify essential metabolic enzymes for a given system. Similar to application in miRNA:

[diFF_metaEnzymes]=predictMIRNA_FC_single_flux(Model,expressionData, List_of_metaEnzyme, ParsedGPR, Prxn);

The only differences is the miRNA-target matrix is changed to a vector list of metabolic enzymes. This pipeline then can identify the essential metabolic enzyme whose downregulation will reduce biomass production rate.