The group found that by making combinatorial knockdowns of Rho network components, their computational method was able to accurately infer Rho-signaling network interactions more precisely than when using only data from single knockdowns. Berger noted that this finding highlights the importance of combinatorial experiments for inferring complex networks, necessary to overcome natural redundancy in signaling pathways. As perturbation of the Rho pathway in humans has been implicated in cancer and other diseases, the authors believe that these predicted interactions will be excellent candidates for future study.

Berger expects that in combination with other sources of data, imaging as a new source of high-throughput data should appreciably increase the accuracy of known signaling networks. "This work provides a glimpse into the future," added Berger, "where looking under the microscope manually at cells one-by-one is replaced with automated high-throughput processing of many cellular images."

Scientists from the Massachusetts Institute of Technology (Cambridge, MA) and Harvard Medical School (Boston, MA) contributed to this study.

Source: Cold Spring Harbor Laboratory