9 research outputs found
Bayesian approaches to reverse engineer cellular systems: a simulation study on nonlinear Gaussian networks-6
<p><b>Copyright information:</b></p><p>Taken from "Bayesian approaches to reverse engineer cellular systems: a simulation study on nonlinear Gaussian networks"</p><p>http://www.biomedcentral.com/1471-2105/8/S5/S2</p><p>BMC Bioinformatics 2007;8(Suppl 5):S2-S2.</p><p>Published online 24 May 2007</p><p>PMCID:PMC1892090.</p><p></p>model, as a function of the sampling interval (in minutes)
Bayesian approaches to reverse engineer cellular systems: a simulation study on nonlinear Gaussian networks-8
<p><b>Copyright information:</b></p><p>Taken from "Bayesian approaches to reverse engineer cellular systems: a simulation study on nonlinear Gaussian networks"</p><p>http://www.biomedcentral.com/1471-2105/8/S5/S2</p><p>BMC Bioinformatics 2007;8(Suppl 5):S2-S2.</p><p>Published online 24 May 2007</p><p>PMCID:PMC1892090.</p><p></p> function at increasingly high values of
Bayesian approaches to reverse engineer cellular systems: a simulation study on nonlinear Gaussian networks-1
<p><b>Copyright information:</b></p><p>Taken from "Bayesian approaches to reverse engineer cellular systems: a simulation study on nonlinear Gaussian networks"</p><p>http://www.biomedcentral.com/1471-2105/8/S5/S2</p><p>BMC Bioinformatics 2007;8(Suppl 5):S2-S2.</p><p>Published online 24 May 2007</p><p>PMCID:PMC1892090.</p><p></p>, obtained using the nonlinear models corresponding to = 0.6 (a) and = 2 (b). Time is expressed in minutes
Bayesian approaches to reverse engineer cellular systems: a simulation study on nonlinear Gaussian networks-0
<p><b>Copyright information:</b></p><p>Taken from "Bayesian approaches to reverse engineer cellular systems: a simulation study on nonlinear Gaussian networks"</p><p>http://www.biomedcentral.com/1471-2105/8/S5/S2</p><p>BMC Bioinformatics 2007;8(Suppl 5):S2-S2.</p><p>Published online 24 May 2007</p><p>PMCID:PMC1892090.</p><p></p> of the parameter of the hyperbolic tangent function (continuous blue curves); the dashed red curves refer to the RMSE and average number of parents for the linear regression model. The dash-dotted green curve in (b) represents the average number of parents in the differential equation model (i.e. the average number of true parents). Further analyses showed that, for β + β, the RMSE saturates at 0.247, and the average number of parents saturates at 3.4
Bayesian approaches to reverse engineer cellular systems: a simulation study on nonlinear Gaussian networks-5
<p><b>Copyright information:</b></p><p>Taken from "Bayesian approaches to reverse engineer cellular systems: a simulation study on nonlinear Gaussian networks"</p><p>http://www.biomedcentral.com/1471-2105/8/S5/S2</p><p>BMC Bioinformatics 2007;8(Suppl 5):S2-S2.</p><p>Published online 24 May 2007</p><p>PMCID:PMC1892090.</p><p></p>ar model corresponding to = 1.8, as a function of the of the noise. = 0 corresponds to the noiseless case
Bayesian approaches to reverse engineer cellular systems: a simulation study on nonlinear Gaussian networks-7
<p><b>Copyright information:</b></p><p>Taken from "Bayesian approaches to reverse engineer cellular systems: a simulation study on nonlinear Gaussian networks"</p><p>http://www.biomedcentral.com/1471-2105/8/S5/S2</p><p>BMC Bioinformatics 2007;8(Suppl 5):S2-S2.</p><p>Published online 24 May 2007</p><p>PMCID:PMC1892090.</p><p></p>ar model corresponding to = 0.8, as a function of the sampling interval (in minutes)
Bayesian approaches to reverse engineer cellular systems: a simulation study on nonlinear Gaussian networks-2
<p><b>Copyright information:</b></p><p>Taken from "Bayesian approaches to reverse engineer cellular systems: a simulation study on nonlinear Gaussian networks"</p><p>http://www.biomedcentral.com/1471-2105/8/S5/S2</p><p>BMC Bioinformatics 2007;8(Suppl 5):S2-S2.</p><p>Published online 24 May 2007</p><p>PMCID:PMC1892090.</p><p></p> of the hyperbolic tangent function (continuous blue curves). The dashed red curves refer to the recall, precision and F-measure of the linear regression model. Further analyses showed that, for β + β, recall saturates at 0.27, precision at 0.26, and the F-measure at 0.26
Bayesian approaches to reverse engineer cellular systems: a simulation study on nonlinear Gaussian networks-3
<p><b>Copyright information:</b></p><p>Taken from "Bayesian approaches to reverse engineer cellular systems: a simulation study on nonlinear Gaussian networks"</p><p>http://www.biomedcentral.com/1471-2105/8/S5/S2</p><p>BMC Bioinformatics 2007;8(Suppl 5):S2-S2.</p><p>Published online 24 May 2007</p><p>PMCID:PMC1892090.</p><p></p> to the number of parent-child relationships in the true model)
Bayesian approaches to reverse engineer cellular systems: a simulation study on nonlinear Gaussian networks-4
<p><b>Copyright information:</b></p><p>Taken from "Bayesian approaches to reverse engineer cellular systems: a simulation study on nonlinear Gaussian networks"</p><p>http://www.biomedcentral.com/1471-2105/8/S5/S2</p><p>BMC Bioinformatics 2007;8(Suppl 5):S2-S2.</p><p>Published online 24 May 2007</p><p>PMCID:PMC1892090.</p><p></p>model as a function of the of the noise. = 0 corresponds to the noiseless case