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7.9.0.529 (r2009b) 32-bit  (MathWorks Inc)


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    MathWorks Inc 7.9.0.529 (r2009b) 32-bit
    Convergence curves. Representative results of parameter estimation runs of the six benchmarks, carried out with the eSS method. The curves plot the (logarithmic) objective function value as a function of the (logarithmic) computation time. For ease of visualization, the values in the curves have been divided by the final value reached by each of them, i.e. the y axis plots J / J f . Note that, since the benchmarks have different number of variables and data points, and different noise levels, the objective function values are not equivalent for different models. Results obtained on a computer with Intel Xeon Quadcore processor, 2.50 GHz, using Matlab 7.9.0.529 <t>(R2009b)</t> 32-bit.
    7.9.0.529 (R2009b) 32 Bit, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/7%2E9%2E0%2E529+(r2009b)+32-bit/pmc04342829-290-13-13
    Average 90 stars, based on 1 article reviews
    7.9.0.529 (r2009b) 32-bit - by Bioz Stars, 2026-09
    90/100 stars

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    1) Product Images from "BioPreDyn-bench: a suite of benchmark problems for dynamic modelling in systems biology"

    Article Title: BioPreDyn-bench: a suite of benchmark problems for dynamic modelling in systems biology

    Journal: BMC Systems Biology

    doi: 10.1186/s12918-015-0144-4

    Convergence curves. Representative results of parameter estimation runs of the six benchmarks, carried out with the eSS method. The curves plot the (logarithmic) objective function value as a function of the (logarithmic) computation time. For ease of visualization, the values in the curves have been divided by the final value reached by each of them, i.e. the y axis plots J / J f . Note that, since the benchmarks have different number of variables and data points, and different noise levels, the objective function values are not equivalent for different models. Results obtained on a computer with Intel Xeon Quadcore processor, 2.50 GHz, using Matlab 7.9.0.529 (R2009b) 32-bit.
    Figure Legend Snippet: Convergence curves. Representative results of parameter estimation runs of the six benchmarks, carried out with the eSS method. The curves plot the (logarithmic) objective function value as a function of the (logarithmic) computation time. For ease of visualization, the values in the curves have been divided by the final value reached by each of them, i.e. the y axis plots J / J f . Note that, since the benchmarks have different number of variables and data points, and different noise levels, the objective function values are not equivalent for different models. Results obtained on a computer with Intel Xeon Quadcore processor, 2.50 GHz, using Matlab 7.9.0.529 (R2009b) 32-bit.

    Techniques Used:

    Dispersion of convergence curves. Results of 20 parameter estimation runs of the B4 benchmark (CHO cells) with the eSS method. The figures plot the objective function value as a function of the computation time (in log-log scale). Results obtained on a computer with Intel Xeon Quadcore processor, 2.50 GHz, using Matlab 7.9.0.529 (R2009b) 32-bit.
    Figure Legend Snippet: Dispersion of convergence curves. Results of 20 parameter estimation runs of the B4 benchmark (CHO cells) with the eSS method. The figures plot the objective function value as a function of the computation time (in log-log scale). Results obtained on a computer with Intel Xeon Quadcore processor, 2.50 GHz, using Matlab 7.9.0.529 (R2009b) 32-bit.

    Techniques Used: Dispersion



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    7.9.0.529 (r2009b) 32-bit  (MathWorks Inc)
    90
    MathWorks Inc 7.9.0.529 (r2009b) 32-bit
    Convergence curves. Representative results of parameter estimation runs of the six benchmarks, carried out with the eSS method. The curves plot the (logarithmic) objective function value as a function of the (logarithmic) computation time. For ease of visualization, the values in the curves have been divided by the final value reached by each of them, i.e. the y axis plots J / J f . Note that, since the benchmarks have different number of variables and data points, and different noise levels, the objective function values are not equivalent for different models. Results obtained on a computer with Intel Xeon Quadcore processor, 2.50 GHz, using Matlab 7.9.0.529 <t>(R2009b)</t> 32-bit.
    7.9.0.529 (R2009b) 32 Bit, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/7%2E9%2E0%2E529+(r2009b)+32-bit/pmc04342829-290-13-13
    Average 90 stars, based on 1 article reviews
    7.9.0.529 (r2009b) 32-bit - by Bioz Stars, 2026-09
    90/100 stars
    		  Buy from Supplier

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    Convergence curves. Representative results of parameter estimation runs of the six benchmarks, carried out with the eSS method. The curves plot the (logarithmic) objective function value as a function of the (logarithmic) computation time. For ease of visualization, the values in the curves have been divided by the final value reached by each of them, i.e. the y axis plots J / J f . Note that, since the benchmarks have different number of variables and data points, and different noise levels, the objective function values are not equivalent for different models. Results obtained on a computer with Intel Xeon Quadcore processor, 2.50 GHz, using Matlab 7.9.0.529 (R2009b) 32-bit.

    Journal: BMC Systems Biology

    Article Title: BioPreDyn-bench: a suite of benchmark problems for dynamic modelling in systems biology

    doi: 10.1186/s12918-015-0144-4

    Figure Lengend Snippet: Convergence curves. Representative results of parameter estimation runs of the six benchmarks, carried out with the eSS method. The curves plot the (logarithmic) objective function value as a function of the (logarithmic) computation time. For ease of visualization, the values in the curves have been divided by the final value reached by each of them, i.e. the y axis plots J / J f . Note that, since the benchmarks have different number of variables and data points, and different noise levels, the objective function values are not equivalent for different models. Results obtained on a computer with Intel Xeon Quadcore processor, 2.50 GHz, using Matlab 7.9.0.529 (R2009b) 32-bit.

    Article Snippet: Results obtained on a computer with Intel Xeon Quadcore processor, 2.50 GHz, using Matlab 7.9.0.529 (R2009b) 32-bit.

    Techniques:

    Dispersion of convergence curves. Results of 20 parameter estimation runs of the B4 benchmark (CHO cells) with the eSS method. The figures plot the objective function value as a function of the computation time (in log-log scale). Results obtained on a computer with Intel Xeon Quadcore processor, 2.50 GHz, using Matlab 7.9.0.529 (R2009b) 32-bit.

    Journal: BMC Systems Biology

    Article Title: BioPreDyn-bench: a suite of benchmark problems for dynamic modelling in systems biology

    doi: 10.1186/s12918-015-0144-4

    Figure Lengend Snippet: Dispersion of convergence curves. Results of 20 parameter estimation runs of the B4 benchmark (CHO cells) with the eSS method. The figures plot the objective function value as a function of the computation time (in log-log scale). Results obtained on a computer with Intel Xeon Quadcore processor, 2.50 GHz, using Matlab 7.9.0.529 (R2009b) 32-bit.

    Article Snippet: Results obtained on a computer with Intel Xeon Quadcore processor, 2.50 GHz, using Matlab 7.9.0.529 (R2009b) 32-bit.

    Techniques: Dispersion