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model_reduction's Introduction

This repository contains the Matlab library corresponding to the manuscript "An automated model reduction method for 
biochemical reaction networks" published in Symmetry. The manuscript is available at https://www.mdpi.com/2073-8994/12/8/1321.

The main reduction procedure can be found in the folder "Reduction_procedure" located in the folder "scr". 
It uses the information of a given biochemical reaction network (CRN) provided by the user to automatically 
reduce the corresponding mathematical model. We have provided two examples of real-life CRNs retrieved from the BioModels database [1], namely, a model 
of neural stem cll regulation (NSCR), [2], and a model of hedgehog signaling pathway (HSP), [2]. The input files corresponding 
to each example can be found in the folder "Examples" located in the folder "scr". For each example, there are two 
input files, namely, "Inputs" and "Denominator".

The file named "Inputs" contains the following information of a given CRN
     1. The complex composition matrix.
     2. The incidence matrix.
     3. The vector of rate constants of the reactions.
     4. The vector of initial species' concentrations.
     5. The user-specified threshold value of the error integral. 
     
For our real-life examples, the treshold value of the error integral has been set to 0.15. In general, this treshold 
can be choosen depending on the desired closeness of the reduced model to the original model.
     
The file named "Denominator" is a Matlab function corresponding to the rational terms in the expressions of reaction rates.

In order to proceed with the reduction (for each example), the user needs to:
     1. Open the files "Inputs" and "Denominator" with all the files located in the folder "Reduction_procedure".
     2. Run the file "Inputs".
     3. Run the file "Main".
     
The automatic reduction procedure provides the following outputs:
     1. The mathematical model and the complex graph corresponding to the original network.
     2. The mathematical model and the complex graph corresponding to the reduced network.
     3. The final value of the error integral.
     4. Comparison of concentration profiles of the important species between the original and the reducd models. 
     
REFERENCES

[1] Le Novere, N.; Bornstein, B.; Broicher, A.; Courtot, M.; Donizelli, M.; Dharuri, H.; Li, L.; Sauro, H.; Schilstra, M.; Shapiro, B.; et al. 
    BioModels Database: A free, centralized database of curated, published, quantitative kinetic models of biochemical and cellular systems. 
    Nucleic Acids Res. 2006, 34, D689โ€“D691.

[2] Sivakumar, K.C.; Dhanesh, S.B.; Shobana, S.; James, J.; Mundayoor, S. 
    A systems biology approach to model neural stem cell regulation by notch, shh, wnt, and EGF signaling pathways. 
    Omics J. Integr. Biol. 2011, 15, 729โ€“737. 

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