Pathways on demand: automated reconstruction of human signaling networks

An algorithm that predicts molecular signaling pathways in humans provides a powerful way to 'join the dots' within protein networks. An important goal for systems biology is to identify the chains of reactions that carry cellular signals from receptors to the transcriptional regulators (TRs) that orchestrate gene activity. T. M. Murali, Anna Ritz, Shiv Kale and co-workers at Virginia Tech developed a method called PATHLINKER that computes the most likely paths between receptors and TRs using a large network of known human protein interactions. The researchers proved the effectiveness of PATHLINKER by correctly reconstructing 47 known signaling pathways. Most promisingly, PATHLINKER suggested a previously unknown component in the Wnt signaling pathway, which the researchers verified by experiment. PATHLINKER will be a valuable tool for choosing which proteins and interactions to study in the lab.