NE histogram.

<p>Mean and median NE values were 1.47 and 0.38 respectively.</p

Workflow representing the 3 steps of the method.

<p>(1) Boolean inference of tables from single-stimulus/inhibitor experimental data, (2) network inference from the tables and (3) linear combination of single-stimulus/inhibitor data to predict protein activity level in multi-stimulus/inhibitor conditions, based on network structure.</p

Links in the network ranked according to the upper limit value of parameter k allowing the presence of the link.

<p>Links in the network ranked according to the upper limit value of parameter k allowing the presence of the link.</p

Influence of the parameter k on the number of links.

<p>Influence of the parameter k on the number of links.</p

Boolean inference.

<p>Three examples are shown: A. stimulus IGF1 does not affect protein Ikb, B. stimulus TNFa affects protein Ikb but the presence of MEK inhibitor does not change the protein level, C. stimulus TNFa affects protein Ikb and the presence of IKK inhibitor decreases the protein level.</p

Additional file 1: of A rule-based model of insulin signalling pathway

Model_details. Tables listing: (1) model inputs; (2) constant parameters; (3) the initial concentration of different chemical species; (4) the rules and functions used in the model, in BioNetGen syntax; (5) the model parameters. (DOCX 32 kb

Additional file 2: of A rule-based model of insulin signalling pathway

Protein_data. Experimental data of pAKT-S473, pmTORC1-S2448 and ppERK1/2-Y202,Y204 at time 2, 5, 10, 30 and 60 min following insulin plus amino acids, i.e. leucine, stimulation [41]. Data are available in three bioplogical replicates (A, B and C in the file). To correct for the antibody efficiency, all band densities for each protein are expressed relative to the baseline time 0′. Moreover, to allow for comparison among different membranes, the ratios between phosphorylated and total proteins are calculated. (XLSX 9 kb

Significance analysis of microarray transcript levels in time series experiments-0

<p><b>Copyright information:</b></p><p>Taken from "Significance analysis of microarray transcript levels in time series experiments"</p><p>http://www.biomedcentral.com/1471-2105/8/S1/S10</p><p>BMC Bioinformatics 2007;8(Suppl 1):S10-S10.</p><p>Published online 8 Mar 2007</p><p>PMCID:PMC1885839.</p><p></p>ene expression studies. Samples are collected from an insulin treated and a control culture. The expression level measured in treated and control culture for a single probe-set (corresponding to "Early growth response 1" gene) is shown in the lower part of the Figure. The area A bounded by the two expression profiles T and C is coloured in gray

Significance analysis of microarray transcript levels in time series experiments-2

<p><b>Copyright information:</b></p><p>Taken from "Significance analysis of microarray transcript levels in time series experiments"</p><p>http://www.biomedcentral.com/1471-2105/8/S1/S10</p><p>BMC Bioinformatics 2007;8(Suppl 1):S10-S10.</p><p>Published online 8 Mar 2007</p><p>PMCID:PMC1885839.</p><p></p>se positives divided by the number of selected genes for different number of selected genes (right panels) obtained on 100 simulated data sets, using methods 1, 2 and 3 on time series of 10 (upper left panel), 30 (upper right panel), and 50 (lower left panel) samples. AUCs are also reported for Precision vs Recall curves

Per cent improvement in Precision obtained ranking genes and considering increasing percentage of them as belonging to identified modules

<p><b>Copyright information:</b></p><p>Taken from "A quantization method based on threshold optimization for microarray short time series"</p><p></p><p>BMC Bioinformatics 2005;6(Suppl 4):S11-S11.</p><p>Published online 1 Dec 2005</p><p>PMCID:PMC1866397.</p><p></p