MIKANA (Method to Infer Kinetics And Network Architecture) is a novel computational method to infer reaction mechanisms and estimate the kinetic parameters of biochemical pathways from time course data.  We developed MIKANA in collaboration with Dr. Edmund Crampin (University of Melbourne) and Dr. Patrick McSharry (University of Oxford).


MIKANA is implemented in MATLAB (MATrix LABoratory). You can download the source code in this link: MIKANA Source Code.



Graphic User Interface


We have created a standalone Graphic User Interface (GUI) of MIKANA.  You do not need MATLAB to run the standalone version.  However, you need to have the MATLAB Compiler Runtime (MCR) installed in your system:


For Windows:


MIKANA GUI - This standalone version was compiled using Matlab R14, 2008b.


For Mac OS X:


MIKANA GUI - The standalone version was compiled using the MATLAB Compiler 4.6 (R2007a).



Installation, quick guide and examples


Please consult our Quick Guide to install and learn how to use MIKANA GUI. You can replicate the results of our papers using our three example data files:


Example 1. The single enzyme, single substrate Michaelis–Menten reaction mechanism

Example 2. The reconstituted mixture of three chemical species in the muscle cell pathway

Example 3. The Lactococcus lactis glycolytic pathway (7 chemical species).


If you have any comments, questions, or would like to report a problem, please send us an email. We greatly appreciate your feedback.



How to cite MIKANA


J. Srividhya, E. J. Crampin, P. E. McSharry and S. Schnell (2007). Reconstructing biochemical pathways from time course data. Proteomics 7, 828-838. DOI: 10.1002/pmic.200600428


M. A. Mourão, J. Srividhya, P. E. McSharry, E. J. Crampin and S. Schnell (2011). A graphical user interface for a method to infer kinetics and network architecture (MIKANA). PLoS ONE 6, e27534. DOI: 10.1371/journal.pone.0027534





MIKANA was partially supported by the National Science Foundation (Awards IIS-0513701 and IIS-0852743).

The Schnell Lab, University of Michigan Medical School

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