Minimizing cell signalling pathway elements using lumping parameters

Abstract

Many complex cell signaling pathway models contain a large number of state variables and parameters. Such models often require computational tools and techniques of model reduction to minimize the number of elements. Techniques of model reduction play an important role in various theoretical and practical applications in systems biology. We introduce a model an approach of model reduction based on lumping of parameters. The suggested technique provides us a good step forward in minimizing model parameters for cell signaling pathways. The proposed technique is applied for the mathematical modeling of NF-κB signal transduction pathway. The number of parameters is reduced from 37 to 8. Some numerical simulations are computed for different initial values. Results provide a good agreement between the complete and the simplified model with a high degree of predictive accuracy. More interestingly, the suggested technique in this work could be used by biologists for simplifying the complexity of cell signaling pathways and identifying critical model parameters.

Keywords

• Mathematical modeling
• Lumping components
• Model reductions
• Cell signaling pathways
• Computational simulation