A graphical user interface for a method to infer kinetics and network architecture (MIKANA).

Area of Science:

• Systems Biology
• Computational Biology
• Biochemistry

Background:

• Determining biochemical reaction mechanisms is crucial for understanding cellular processes.
• Existing methods often focus on static protein interactions, lacking dynamic modeling capabilities.
• Systems biologists need realistic models of reactant, intermediate, and product dynamics.

Purpose of the Study:

• To present MIKANA (Method to Infer Kinetics And Network Architecture), a computational tool for inferring biochemical pathway mechanisms and kinetics.
• To introduce a Graphical User Interface (GUI) for MIKANA to enhance accessibility and usability for the scientific community.
• To improve MIKANA's performance by adding a feature to exclude known reactions from inference.

Main Methods:

• MIKANA infers reaction mechanisms and estimates kinetic parameters from time-course data.
• The developed GUI validates input data, displays inferred reactions, and generates differential equations.
• The GUI visualizes predicted pathway behavior against experimental data and allows exclusion of known reactions.

Main Results:

• The MIKANA GUI successfully illustrates pathway inference for Michaelis-Menten, muscle glycolysis, and Lactococcus lactis glycolysis.
• The addition of a priori reaction exclusion feature demonstrably improves MIKANA's performance.
• The open-source MIKANA software is available for academic and non-academic use.

Conclusions:

• MIKANA provides a robust computational framework for elucidating biochemical pathway dynamics.
• The user-friendly GUI facilitates the application of MIKANA for systems biology research.
• The method's open-source nature promotes further development and reproducibility in the field.