Here the CD79a and CD79b subunits associated with the BCR were taken together and considered as a sin gle BCR complex. Shortest path analysis of networks is generally consid ered to represent a reliable method for capturing infor mation on the transduction of signals through the various intermediate nodes. Further, our experi ments in Figure 1B had also helped to distinguish at least some of the signaling intermediates that were either significantly activated, or ignored, upon BCR sti mulation of cells. Therefore, starting from the BCR, we next traced all the possible shortest paths leading to each human ortholog of the signaling intermediate that was shown to be activated in Figure 1B. Here, we con sidered a signaling intermediate to be activated only if its phosphorylation levels were increased by at least 2 fold in response to anti IgM stimulation.

This filtration exercise short listed Raf1, ERK 1/2, MEK 1/2, p38, JNK, CAMKII, Lyn and Akt1 as the target nodes, and all the resulting shortest paths originating from the BCR to each of these intermediates were merged to create a sub network. In order to complete the above network we again employed the shortest path algorithm to next trace the various possible shortest paths from each of the acti vated signaling intermediates to the set of seven short listed TFs described in Figure 3B. These paths were then merged to yield the shortest path network from the signaling intermediates to the TFs. In the final step we merged the three sub networks comprising of the links between the BCR and the signal ing intermediates, the signaling intermediates and the TFs, and the DOR between the TFs and the target genes described in Figure 3B.

This synthesis generated an information centric network that captured the path ways mediating BCR dependent cell cycle arrest of CH1 cells. The resulting network was comprised of 163 nodes and 416 edges and is depicted in Figure 3. Here, 44 of the constituent nodes are transcription factors whereas 103 are signaling molecules. It is pertinent to note here that the network shown in Figure 3C is distinct from the more conventional protein protein interaction, or, gene regulatory networks in that it represents a hybrid of both approaches. Thus while the links from the BCR through the signaling intermediates and to the TFs essentially constitute a PPI network, the downstream component incorporating links from TFs to the target genes however describes Carfilzomib a set of protein to gene interactions.

Extracting the gene expression signature of the cellular response Our next goal then was to delineate the core pathways or modules in the network described in Figure 3C, that specifically regulated the cellular phenotypic response. To do this, however, it was first necessary to identify those BCR dependent genes described in Figure 3B, that were responsible for enforcing G1 arrest of cycling CH1 cells.