Planning identification experiments for NFKB signaling pathway - A gradient approach

Mathematical modeling of cell signaling pathways becomes very important and challenging problem in recent years. The importance comes from possible application of obtained models. It may help us to understand phenomena appearing in single cell and in cell populations on molecular level. Furthermore, it may help us with discovering new drug therapies. Mathematical models of cell signaling pathways takes different forms. The most popular way of mathematical modeling is to use a set of nonlinear ordinary differential equations (ODEs). It is very difficult to obtain proper model. There are many hypotheses about the structure of the model (set of variables and set of phenomenons) that should be verified. The next step, fitting of the parameters of the model, is also very complicated because of the nature of measurements. The blotting technique usually gives only semi-quantitative observations which are very noisy and they are collected only at limited number of time moments. The accuracy of parameter estimation may be significantly improved by proper experiment planing. Recently, we proposed a gradient-based algorithm for optimization of sampling schedule. In this paper we use the algorithm in order to optimize a sampling schedule for identification of the mathematical model of NFkB regulatory module, previously published in related literature.