Prior Information Properties.

<p>Prior Information Properties.</p

MSE and MSSRE in the simulations with 20% noise.

<p>Each point corresponds to the median of the MSE values (<b>Panel A</b>) and MSSRE values (<b>Panel B</b>) in 100 simulations with different noise realizations. The error bars represent the median absolute deviation. The results of the simulations with the correct network (CN) are plotted in red whereas the blue and green colors represent the solutions with 3% and 5% misconnected network structures, respectively (MN3% and MN5%).The networks which are represented by the green shapes share the same misconnections with the corresponding shapes in blue and have extra misconnections on top of these. In the upper right hand side corner of each plot, the results of the simulations with totally random networks (RN) are depicted. In <b>Panel A</b>, each errorbar is surrounded with different shapes, whereas in <b>Panel B</b>, the medians are denoted by the corresponding shapes for better readability of both graphs. (See <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0040082#pone-0040082-t001" target="_blank">Table 1</a> for the details of the prior information used).</p

Discrimination Performance.

<p>Discrimination Performance.</p

Behaviour of MSE and MSSRE with respect to changes in the connection strengths differing between the competing networks.

<p>The change in MSE (Panel A) and MSSRE (Panel B) in simulations with MN3% and MN5% relative to the simulations with CN are shown in the y-axis. In the x-axis, the total magnitude of the missing connections which existed in CN but had been ignored in the imposed network structure are plotted.</p

Values of Connection Strengths in .

<p>In this plot, each black point represents the connection strength of an element in the unrestricted connectivity matrix which was restricted to 0 previously in the imposed network structure. Each column represents one transcription factor. Red stars are the connections which were missing in the imposed network structure whereas in CN these elements have nonzero values indicating existing connections instead. The outlier elements for each transcription factor identified at a whisker length of 2 are surrounded with additional squares in blue.</p

Example network with 6 genes and 3 transcription factors (TF’s).

<p>The imposed network structure is encoded in . Existing connections are depicted as 1′s. W has 1′s at the positions where the difference between the initial estimate, and the template, is subject to minimization. These positions correspond to the 0′s in where no connections exist.</p

Example HC4N result tree.

<p>For clarity, the co-occurrence is displayed in each node. Clusters with many proteins of low co-occurrence and with large child nodes indicate interacting complexes at the highest interaction level. Complexes built of several cores have a higher co-occurrence and leafs as child nodes. Leaf nodes with a high co-occurrence symbolize complex cores. Leaf nodes with low co-occurrence mostly do not represent complex cores, and their interpretation is not always univocal.</p

Predicted Interactions in Cell Cycle Regulatory Network of Yeast.

<p>Only the ones which were supported by biological evidence from literature are shown here. <b>Bold font</b> genes belong to the new set of genes whereas the normal font genes are the model set genes.</p

Structure of the Simulations.

<p>At each noise level, 10 different regulatory networks were simulated as shown with circles in the figure. Later, each of these were manipulated to obtain different prior information as depicted in pink rectangles.</p

General view of the approach.

<p>The individual steps in the figure are explained in detail in the Methods Section.</p