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matlab-based modelling environment 'data2dynamics  (MathWorks Inc)


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    MathWorks Inc matlab-based modelling environment 'data2dynamics
    The parameter θ m ∈ θ was varied over a broad range of values and for each fixed value of θ m , the increase in D P L ( θ m ) = min θ ˜ m - 2 log ( L ( θ ) ) was computed, with L ( θ ) the likelihood function as defined in , and θ ˜ m = { θ 1 , … , θ m - 1 , θ m + 1 , θ N } . The 99% confidence interval threshold is shown as a red dashed line. The parameter values used to generate the synthetic dataset are shown as red dots. The parameter values resulting in the minimal D = min θ - 2 log ( L ( θ ) ) are shown as grey stars. This figure has been generated using the Matlab environment <t>‘Data2Dynamics’</t> [ , ].
    Matlab Based Modelling Environment 'data2dynamics, 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/result/matlab-based modelling environment 'data2dynamics/product/MathWorks Inc
    Average 90 stars, based on 1 article reviews
    matlab-based modelling environment 'data2dynamics - by Bioz Stars, 2026-03
    90/100 stars

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    1) Product Images from "A method for the inference of cytokine interaction networks"

    Article Title: A method for the inference of cytokine interaction networks

    Journal: PLoS Computational Biology

    doi: 10.1371/journal.pcbi.1010112

    The parameter θ m ∈ θ was varied over a broad range of values and for each fixed value of θ m , the increase in D P L ( θ m ) = min θ ˜ m - 2 log ( L ( θ ) ) was computed, with L ( θ ) the likelihood function as defined in , and θ ˜ m = { θ 1 , … , θ m - 1 , θ m + 1 , θ N } . The 99% confidence interval threshold is shown as a red dashed line. The parameter values used to generate the synthetic dataset are shown as red dots. The parameter values resulting in the minimal D = min θ - 2 log ( L ( θ ) ) are shown as grey stars. This figure has been generated using the Matlab environment ‘Data2Dynamics’ [ , ].
    Figure Legend Snippet: The parameter θ m ∈ θ was varied over a broad range of values and for each fixed value of θ m , the increase in D P L ( θ m ) = min θ ˜ m - 2 log ( L ( θ ) ) was computed, with L ( θ ) the likelihood function as defined in , and θ ˜ m = { θ 1 , … , θ m - 1 , θ m + 1 , θ N } . The 99% confidence interval threshold is shown as a red dashed line. The parameter values used to generate the synthetic dataset are shown as red dots. The parameter values resulting in the minimal D = min θ - 2 log ( L ( θ ) ) are shown as grey stars. This figure has been generated using the Matlab environment ‘Data2Dynamics’ [ , ].

    Techniques Used: Generated

    The parameter θ m = s A ∈ θ was varied over a broad range of values and for each fixed value of θ m , the increase in D P L ( θ m ) = min θ ˜ m - 2 log ( L ( θ ) ) was computed, with L ( θ ) the likelihood function as defined in , and θ ˜ m = { θ 1 , … , θ m - 1 , θ m + 1 , θ N } . The 99% confidence interval threshold is shown as a red dashed line and corresponds to a two order of magnitude interval for s A . The parameter value used to generate the synthetic dataset is shown as a red dot. The parameter value resulting in the minimal D = min θ - 2 log ( L ( θ ) ) is shown as a grey star. This figure has been generated using the Matlab environment ‘Data2Dynamics’ [ , ].
    Figure Legend Snippet: The parameter θ m = s A ∈ θ was varied over a broad range of values and for each fixed value of θ m , the increase in D P L ( θ m ) = min θ ˜ m - 2 log ( L ( θ ) ) was computed, with L ( θ ) the likelihood function as defined in , and θ ˜ m = { θ 1 , … , θ m - 1 , θ m + 1 , θ N } . The 99% confidence interval threshold is shown as a red dashed line and corresponds to a two order of magnitude interval for s A . The parameter value used to generate the synthetic dataset is shown as a red dot. The parameter value resulting in the minimal D = min θ - 2 log ( L ( θ ) ) is shown as a grey star. This figure has been generated using the Matlab environment ‘Data2Dynamics’ [ , ].

    Techniques Used: Generated



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    matlab-based modelling environment 'data2dynamics  (MathWorks Inc)
    90
    MathWorks Inc matlab-based modelling environment 'data2dynamics
    The parameter θ m ∈ θ was varied over a broad range of values and for each fixed value of θ m , the increase in D P L ( θ m ) = min θ ˜ m - 2 log ( L ( θ ) ) was computed, with L ( θ ) the likelihood function as defined in , and θ ˜ m = { θ 1 , … , θ m - 1 , θ m + 1 , θ N } . The 99% confidence interval threshold is shown as a red dashed line. The parameter values used to generate the synthetic dataset are shown as red dots. The parameter values resulting in the minimal D = min θ - 2 log ( L ( θ ) ) are shown as grey stars. This figure has been generated using the Matlab environment <t>‘Data2Dynamics’</t> [ , ].
    Matlab Based Modelling Environment 'data2dynamics, 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/result/matlab-based modelling environment 'data2dynamics/product/MathWorks Inc
    Average 90 stars, based on 1 article reviews
    matlab-based modelling environment 'data2dynamics - by Bioz Stars, 2026-03
    90/100 stars
    		  Buy from Supplier
    matlab-based data2dynamics modeling environment  (MathWorks Inc)
    90
    MathWorks Inc matlab-based data2dynamics modeling environment
    The parameter θ m ∈ θ was varied over a broad range of values and for each fixed value of θ m , the increase in D P L ( θ m ) = min θ ˜ m - 2 log ( L ( θ ) ) was computed, with L ( θ ) the likelihood function as defined in , and θ ˜ m = { θ 1 , … , θ m - 1 , θ m + 1 , θ N } . The 99% confidence interval threshold is shown as a red dashed line. The parameter values used to generate the synthetic dataset are shown as red dots. The parameter values resulting in the minimal D = min θ - 2 log ( L ( θ ) ) are shown as grey stars. This figure has been generated using the Matlab environment <t>‘Data2Dynamics’</t> [ , ].
    Matlab Based Data2dynamics Modeling Environment, 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/result/matlab-based data2dynamics modeling environment/product/MathWorks Inc
    Average 90 stars, based on 1 article reviews
    matlab-based data2dynamics modeling environment - by Bioz Stars, 2026-03
    90/100 stars
    		  Buy from Supplier

    Image Search Results


    The parameter θ m ∈ θ was varied over a broad range of values and for each fixed value of θ m , the increase in D P L ( θ m ) = min θ ˜ m - 2 log ( L ( θ ) ) was computed, with L ( θ ) the likelihood function as defined in , and θ ˜ m = { θ 1 , … , θ m - 1 , θ m + 1 , θ N } . The 99% confidence interval threshold is shown as a red dashed line. The parameter values used to generate the synthetic dataset are shown as red dots. The parameter values resulting in the minimal D = min θ - 2 log ( L ( θ ) ) are shown as grey stars. This figure has been generated using the Matlab environment ‘Data2Dynamics’ [ , ].

    Journal: PLoS Computational Biology

    Article Title: A method for the inference of cytokine interaction networks

    doi: 10.1371/journal.pcbi.1010112

    Figure Lengend Snippet: The parameter θ m ∈ θ was varied over a broad range of values and for each fixed value of θ m , the increase in D P L ( θ m ) = min θ ˜ m - 2 log ( L ( θ ) ) was computed, with L ( θ ) the likelihood function as defined in , and θ ˜ m = { θ 1 , … , θ m - 1 , θ m + 1 , θ N } . The 99% confidence interval threshold is shown as a red dashed line. The parameter values used to generate the synthetic dataset are shown as red dots. The parameter values resulting in the minimal D = min θ - 2 log ( L ( θ ) ) are shown as grey stars. This figure has been generated using the Matlab environment ‘Data2Dynamics’ [ , ].

    Article Snippet: Our method depends on the global minimization of a log-likelihood function and a deterministic trust-region approach was used combined with a multi-start strategy, as implemented in the Matlab-based modelling environment ‘Data2Dynamics’ [ ].

    Techniques: Generated

    The parameter θ m = s A ∈ θ was varied over a broad range of values and for each fixed value of θ m , the increase in D P L ( θ m ) = min θ ˜ m - 2 log ( L ( θ ) ) was computed, with L ( θ ) the likelihood function as defined in , and θ ˜ m = { θ 1 , … , θ m - 1 , θ m + 1 , θ N } . The 99% confidence interval threshold is shown as a red dashed line and corresponds to a two order of magnitude interval for s A . The parameter value used to generate the synthetic dataset is shown as a red dot. The parameter value resulting in the minimal D = min θ - 2 log ( L ( θ ) ) is shown as a grey star. This figure has been generated using the Matlab environment ‘Data2Dynamics’ [ , ].

    Journal: PLoS Computational Biology

    Article Title: A method for the inference of cytokine interaction networks

    doi: 10.1371/journal.pcbi.1010112

    Figure Lengend Snippet: The parameter θ m = s A ∈ θ was varied over a broad range of values and for each fixed value of θ m , the increase in D P L ( θ m ) = min θ ˜ m - 2 log ( L ( θ ) ) was computed, with L ( θ ) the likelihood function as defined in , and θ ˜ m = { θ 1 , … , θ m - 1 , θ m + 1 , θ N } . The 99% confidence interval threshold is shown as a red dashed line and corresponds to a two order of magnitude interval for s A . The parameter value used to generate the synthetic dataset is shown as a red dot. The parameter value resulting in the minimal D = min θ - 2 log ( L ( θ ) ) is shown as a grey star. This figure has been generated using the Matlab environment ‘Data2Dynamics’ [ , ].

    Article Snippet: Our method depends on the global minimization of a log-likelihood function and a deterministic trust-region approach was used combined with a multi-start strategy, as implemented in the Matlab-based modelling environment ‘Data2Dynamics’ [ ].

    Techniques: Generated