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The MAPK/ERK pathway is a major signal transduction systemwhich regulates many fundamental cellular processes including thegrowth control and the cell death. As a result of these roles, it hasa crucial importance in cancer as well as normal developmental processes. Therefore, it has been intensively studied resulting in a wealthof knowledge about its activation. It is also well documented thatthe activation kinetics of the pathway is crucial to determine the natureof the biological response. However, while individual biochemicalsteps are well characterized, it is still difficult to predict or even understandhow the activation kinetics works. The aim of this paper is toestimate the stochastic rate constants of the MAPK/ERK network dynamics. Accordingly, taking a Bayesian approach, we combined underlyingqualitative biological knowledge in several competing dynamicmodels via sets of quasireactions and estimated the stochastic rate constantsof these reactions. Comparing the resulting estimates via theBIC and DIC criteria, we chose a biological model which includesEGFR degradation—Raf-MEK-ERK cascade without the involvementof RKIPs.

Estimating Network Kinetics of the MAPK/ERK Pathway Using Biochemical Data