<p>The influence of the <i>global equal width</i> discretization method on the global network inference performance (AUC-PR) for three Erdös-Rényi networks and MI estimators.</p
<p>The figure shows the area under the receiver operator characteristic (AUC ROC) and area under the...
Global assortativity GA and the median and mean standardized local assortativity for the three stat...
<p>The legend shows the used sample sizes. Gene expression data were simulated for an Erdös-Rényi ne...
<p>The influence of the <i>equal width</i> discretization method on the global network inference per...
<p>The influence of the <i>equal frequency</i> discretization method on the global network inference...
<p>Effect of network size on network reconstruction – AUC values of the ROC (A) and the PR (B) curve...
well across sizes.We provided subchallenges with networks of size 10, 50, and 100 in order to compar...
The inference of gene regulatory networks from gene expression data is a difficult problem because t...
The AUC results compared with the state-of-the-art methods on 13 real networks.</p
<p>Simulated gene expression datasets for Erdös-Rényi networks with edge density for sample sizes r...
The AUC and precision results compared with baseline methods on 13 real networks.</p
<p>The performance of structure inference, under 6 different numbers of perturbations (from 2 to 7),...
Graphical models are widely used to study complex multivariate biological systems. Network inference...
<p>(a) Residual prediction errors. For the global features, we train a linear regression model with ...
<p>Effect of perturbation data on network reconstruction performance (a and b represent AUPR and AUR...
<p>The figure shows the area under the receiver operator characteristic (AUC ROC) and area under the...
Global assortativity GA and the median and mean standardized local assortativity for the three stat...
<p>The legend shows the used sample sizes. Gene expression data were simulated for an Erdös-Rényi ne...
<p>The influence of the <i>equal width</i> discretization method on the global network inference per...
<p>The influence of the <i>equal frequency</i> discretization method on the global network inference...
<p>Effect of network size on network reconstruction – AUC values of the ROC (A) and the PR (B) curve...
well across sizes.We provided subchallenges with networks of size 10, 50, and 100 in order to compar...
The inference of gene regulatory networks from gene expression data is a difficult problem because t...
The AUC results compared with the state-of-the-art methods on 13 real networks.</p
<p>Simulated gene expression datasets for Erdös-Rényi networks with edge density for sample sizes r...
The AUC and precision results compared with baseline methods on 13 real networks.</p
<p>The performance of structure inference, under 6 different numbers of perturbations (from 2 to 7),...
Graphical models are widely used to study complex multivariate biological systems. Network inference...
<p>(a) Residual prediction errors. For the global features, we train a linear regression model with ...
<p>Effect of perturbation data on network reconstruction performance (a and b represent AUPR and AUR...
<p>The figure shows the area under the receiver operator characteristic (AUC ROC) and area under the...
Global assortativity GA and the median and mean standardized local assortativity for the three stat...
<p>The legend shows the used sample sizes. Gene expression data were simulated for an Erdös-Rényi ne...
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