HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS		QUICK SEARCH:   [advanced] Author: Keyword(s): Year:  Vol:  Page:

This Article Full Text Full Text (PDF) Supplemental Data All Versions of this Article: M800354-MCP200v1 8/9/2063    most recent Submit a response Alert me when this article is cited Alert me when eLetters are posted Alert me if a correction is posted Citation Map Services Email this article to a friend Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Request Permissions Glossary Google Scholar Articles by Liu, W. Articles by He, F. PubMed PubMed Citation Articles by Liu, W. Articles by He, F. Social Bookmarking                      What's this?

Molecular & Cellular Proteomics 8:2063-2070, 2009.
© 2009 by The American Society for Biochemistry and Molecular Biology, Inc.

---

Research

Proteome-wide Prediction of Signal Flow Direction in Protein Interaction Networks Based on Interacting Domains^*,

Wei Liu, Dong Li, Jian Wang, Hongwei Xie, Yunping Zhu and Fuchu He^¶

From the State Key Laboratory of Proteomics, Beijing Proteome Research Center, Beijing Institute of Radiation Medicine, College of Mechanical & Electronic Engineering and Automatization, National University of Defense Technology, Institutes of Biomedical Sciences, Fudan University, 100850 Beijing, China

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.

¶ To whom correspondence may be addressed. Tel.:86-10-68171208; Fax:86-10-68214653; E-mail: hefc{at}nic.bmi.ac.cn.

CiteULike    Complore    Connotea    Del.icio.us    Digg    Reddit    Technorati    What's this?