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This limitation could be addressed by using nonlinear cost functions.
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A nonlinear optimization problem is then formulated and solved by using nonlinear direct search techniques.
Kinetic parameters were obtained by using nonlinear regression.
The kinetic parameters were refined by using nonlinear regression.
Statistical analyses of the resulting tumor data were performed by using nonlinear Poisson and probit models.
The concentrations of agonist causing half-maximal contraction or relaxation (EC50) were calculated by using nonlinear semilogistic regression analysis.
The data were analyzed by globally fitting using nonlinear least-squares (IGOR Pro Wavemetrics).
The IC50 values were calculated by fitting the data using nonlinear regression in GraphPad Prism Software (San Diego, CA).
Vmax and Km parameters were determined using nonlinear regression analysis by plotting initial enzyme velocity (vo) versus substrate concentration ([S]).
The cost function defined in (3) is nonlinear with respect to the unknowns being suitable to be solved using nonlinear optimization techniques (Newton-Raphson [23], Levenberg-Marquardt [23]).
One might also use a nonlinear cost function such as that proposed by Dekel and Alon (2005) based on experiment.
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