<p><b>(a)</b> Results versus the numbers of incoming links. A total of 300 BA random networks with different network sizes (|V| = 10,20,…,100) were used as target networks, and 16,500 nodes in those networks were classified according to the number of incoming links. <b>(b)</b> Results versus the network sizes. For each different number of nodes, 30 BA random networks were examined. Error-bars mean the standard deviations. In each figure, the maximum time step was set to |V| + 10 in generating artificial gene expression data.</p
Abstract: The complexity of biological systems is encoded in gene regulatory networks. Unravelling t...
The inference of biological networks is an active research area in the field of systems biology. The...
Numerous methods have been developed for inferring gene regulatory networks from expression data, ho...
<p>Results of <b>(a)</b> precision, <b>(b)</b> recall, and <b>(c)</b> structural accuracy, respectiv...
<p>Predicted networks were evaluated on the basis of two scoring metrics, (<b>a</b>) area under the ...
<p>For each of the twelve combinations of size and experimental setting, 300 random reference networ...
Motivation: Inferring a gene regulatory network exclusively from microarray expression profiles is a...
<p><b>A.</b> Comparison based on fold enrichment of true edges in the inferred network. The cartoon ...
<p>Properties of the TALE-gene network are compared to average values from 100 randomized controls (...
<p>Number of unique phenotypes <i>U</i> accessed for different numbers of gene expression states <i>...
<p>(<i>a</i>) A human PPI network with <i>n</i> = 11,524 nodes and average degree of 9.0. The dashed...
MOTIVATION: Network-based gene function inference methods have proliferated in recent years, but mea...
National audienceIntegrative and systems biology is a very promising tool for deciphering the biolog...
<p>Number of unique phenotypes <i>U</i> accessed for different numbers of gene expression states <i>...
<p>Number of unique phenotypes <i>U</i> accessed for different sampling sizes <i>λ</i> and varying d...
Abstract: The complexity of biological systems is encoded in gene regulatory networks. Unravelling t...
The inference of biological networks is an active research area in the field of systems biology. The...
Numerous methods have been developed for inferring gene regulatory networks from expression data, ho...
<p>Results of <b>(a)</b> precision, <b>(b)</b> recall, and <b>(c)</b> structural accuracy, respectiv...
<p>Predicted networks were evaluated on the basis of two scoring metrics, (<b>a</b>) area under the ...
<p>For each of the twelve combinations of size and experimental setting, 300 random reference networ...
Motivation: Inferring a gene regulatory network exclusively from microarray expression profiles is a...
<p><b>A.</b> Comparison based on fold enrichment of true edges in the inferred network. The cartoon ...
<p>Properties of the TALE-gene network are compared to average values from 100 randomized controls (...
<p>Number of unique phenotypes <i>U</i> accessed for different numbers of gene expression states <i>...
<p>(<i>a</i>) A human PPI network with <i>n</i> = 11,524 nodes and average degree of 9.0. The dashed...
MOTIVATION: Network-based gene function inference methods have proliferated in recent years, but mea...
National audienceIntegrative and systems biology is a very promising tool for deciphering the biolog...
<p>Number of unique phenotypes <i>U</i> accessed for different numbers of gene expression states <i>...
<p>Number of unique phenotypes <i>U</i> accessed for different sampling sizes <i>λ</i> and varying d...
Abstract: The complexity of biological systems is encoded in gene regulatory networks. Unravelling t...
The inference of biological networks is an active research area in the field of systems biology. The...
Numerous methods have been developed for inferring gene regulatory networks from expression data, ho...