Deriving mechanistic relations between genes and proteins is a crucial part of large-scale genomic data analysis.Genes and proteins in the cell do not function as stand alone units but rather through intricate networks.Normal regulation of cellular function is dependent on coherent functioning of the cellular networks.Genomic and proteomic methods generate large amounts of data and most current methods of analysis attempt to identify most significant genes without regard to their network connectivity thereby treating each gene or protein as an individual entity.We have analyzed the same data sets based on their network connectivity to determine coherently regulated networks that may play a causal role in driving different phenotypes.Identifying these networks is possible by analyzing functional interactions between genes within the given biological context highlighted by the dat& Novel network algorithms we have developed integrate experimental data from gene expression, phopho-proteomics and siRNA screens to enable us to derive pathway and network dependent analysis of large data sets.