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Image Search Results
Journal: Bioinformatics
Article Title: Optimization and profile calculation of ODE models using second order adjoint sensitivity analysis
doi: 10.1093/bioinformatics/bty230
Figure Lengend Snippet: Performance measures of different local optimization methods [ lsqnonlin with TR algorithm and fmincon with TR and IP algorithm, using either Hessians (H), FIM, or the BFGS scheme]. The multi-start optimization was carried out multiple times using different starting points for the local optimizations. Mean and standard deviation for ( A ) the ratio of computation time over converged optimization starts and ( B ) the number of converged starts are shown. ( C ) Median and standard deviation of the number of optimization steps over all optimization runs
Article Snippet: Common least-squares algorithms such as the
Techniques: Standard Deviation
Journal: Bioinformatics
Article Title: Optimization and profile calculation of ODE models using second order adjoint sensitivity analysis
doi: 10.1093/bioinformatics/bty230
Figure Lengend Snippet: Profile likelihood computation using either the optimization-based method ( lsqnonlin or fmincon with TR or IP algorithm and Hessian or BFGS approximation), or the hybrid method with either FIM or Hessian. ( A ) Total computation time for all profiles of the considered models. Three methods failed to compute profiles for the RAF/MEK/ERK model. Thus, their computation times are not depicted. ( B ) A profile of the RAF/MEK/ERK model, the three remaining methods in good agreement with each other, with confidence intervals to a confidence level of 95% depicted below. ( C ) A profile of the RAF/MEK/ERK model, for which lsqnonlin failed to compute the profile, with confidence intervals to a confidence level of 95% depicted below
Article Snippet: Common least-squares algorithms such as the
Techniques: