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.