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Compressed biological systems of tens of thousands of biochemical reactions by a hierarchical organization of pathways which speeds up the downstream analysis up to 3 times in addition to saving memory and storage space

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Quantitative Flux Coupling Analysis

Introduction

Quantitative flux coupling analysis (QFCA) is a quantitative approach to identify and remove the redundancies of the steady-state flux cone. The full description and theory of the algorithm implemented by QFCA is discussed in the associated papers. When referencing QFCA, please cite the followings:

Quick Start

The following example uses the QFCA function to compute the table of flux coupling relations and the list of blocked reactions for the core E. coli model and also returns the reduced metabolic network.

load('ecoli_core_model.mat');
[reduced_net, fctable, blocked] = QFCA(model, true, 'linprog');

The output of the above code is as follows.

Original number of:
	metabolites = 72;	reactions = 95;	nonzero elements = 360
Original number of:
	reversible reactions = 59;	irreversible reactions = 36
Identifying the blocked reactions and removing them from the network: 0.034
Reduced number of:
	metabolites = 72;	reactions = 95;	nonzero elements = 360
Finding the full coupling relations: 0.008
Reduced number of:
	metabolites = 34;	reactions = 60;	nonzero elements = 236
Correcting the reversibility types: 0.037
Finding the directional and partial coupling relations: 0.411
Inferring by the transitivity of full coupling relations: 0.000
Metabolic network reductions postprocessing: 0.001
Reduced number of:
	metabolites = 30;	reactions = 58;	nonzero elements = 224
The number of solved:
	linear programs = 54;	systems of linear equations = 8

Furthermore, the directionallyCoupled function can be utilized as a stand-alone function to find fictitious metabolite certificates.

License

QFCA is distributed under the GNU General Public License v3.0.

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Compressed biological systems of tens of thousands of biochemical reactions by a hierarchical organization of pathways which speeds up the downstream analysis up to 3 times in addition to saving memory and storage space

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