PT - JOURNAL ARTICLE AU - Liu, Wei AU - Li, Dong AU - Wang, Jian AU - Xie, Hongwei AU - Zhu, Yunping AU - He, Fuchu TI - Proteome-wide Prediction of Signal Flow Direction in Protein Interaction Networks Based on Interacting Domains AID - 10.1074/mcp.M800354-MCP200 DP - 2009 Sep 01 TA - Molecular & Cellular Proteomics PG - 2063--2070 VI - 8 IP - 9 4099 - http://www.mcponline.org/content/8/9/2063.short 4100 - http://www.mcponline.org/content/8/9/2063.full SO - Mol Cell Proteomics2009 Sep 01; 8 AB - Signal flow direction is one of the most important features of the protein-protein interactions in signaling networks. However, almost all the outcomes of current high-throughout techniques for protein-protein interactions mapping are usually supposed to be non-directional. Based on the pairwise interaction domains, here we defined a novel parameter protein interaction directional score and then used it to predict the direction of signal flow between proteins in proteome-wide signaling networks. Using 5-fold cross-validation, our approach obtained a satisfied performance with the accuracy 89.79%, coverage 48.08%, and error ratio 16.91%. As an application, we established an integrated human directional protein interaction network, including 2,237 proteins and 5,530 interactions, and inferred a large amount of novel signaling pathways. Directional protein interaction network was strongly supported by the known signaling pathways literature (with the 87.5% accuracy) and further analyses on the biological annotation, subcellular localization, and network topology property. Thus, this study provided an effective method to define the upstream/downstream relations of interacting protein pairs and a powerful tool to unravel the unknown signaling pathways.© 2009 by The American Society for Biochemistry and Molecular Biology, Inc.