Using scale-free topology to estimate critical genes from regulatory networks

Mathaeus Dejori1, Martin Stetter2, Technical University of Munich;, Siemens AG

Cellular molecular network systems result from complex interactions between proteins, DNA, RNA and other molecules. One of the main interests is to understand the operational mode of complex regulatory genetic networks and their response to intervention such as for example the response to drug treatment.
We present a method for estimating genes that play a key role in controlling the state of regulatory genetic networks by analyzing the network topology. By introducing a new topological feature we are able to estimate the effect of genes on the stability of scale-free genetic networks finding those ones that represent the Achilles Heel of a molecular interaction network. The resulting information can be helpful for understanding the quality of genetic networks obtained by microarray data or it can indicate potential candidates for new drug-targets, e.g. to suppress missguided pathways in cancer cells.