Additional file 8: Figure S6. of A transcriptome-based protein network that identifies new therapeutic targets in colorectal cancer

Topological parameters analysis on global network building from the functional association between 111 genes deregulated in CRC vs. NT. A. Network visualization of node degree and clustering coefficient parameters. The node degree, i.e. the number of edges linked to a node, was visually mapped by the node size: nodes with a low degree were smaller, in contrast to nodes with a high degree. The clustering coefficient, another computed topological parameter reflecting the tendency of neighbors of each node to interact together, was mapped by node gradient color: nodes with lowest clustering coefficient are blue and nodes with highest clustering coefficient are orange (medium clustering coefficient are yellow). As mentioned in Additional file 7: Figure S5, the thickness of edges was correlated with score confidence (large for high score), the blue line indicated physical interaction experimentally demonstrated in the source of evidence and the node shape illustrated the specific PCR array: Apoptosis: square, Cancer Pathway: hexagon, Lipoprotein signaling and cholesterol metabolism: circle, Drug metabolism: diamond and Wnt pathway: octagon. B. Scatter plot displaying the correlation between node degrees and clustering coefficients in the global network composed of 111 nodes showing transcriptome deregulation in CRC as compared to NT. Dotted lines indicated the median of node degree (value of 11) and the median of clustering coefficient (value of 0.54). Genes showing a deregulation in more than 75% of CRC were indicated by a black symbol. (PDF 300 kb)