Reconstruction of signaling network from protein interactions based on function annotations.
The directionality of protein interactions is the prerequisite of forming various signaling networks, and the construction of signaling networks is a critical issue in the discovering the mechanism of the life process. In this paper, we proposed a novel method to infer the directionality in protein-protein interaction networks and furthermore construct signaling networks. Based on the functional annotations of proteins, we proposed a novel parameter GODS and established the prediction model. This method shows high sensitivity and specificity to predict the directionality of protein interactions, evaluated by fivefold cross validation. By taking the threshold value of GODS as 2, we achieved accuracy 95.56 percent and coverage 74.69 percent in the human test set. Also, this method was successfully applied to reconstruct the classical signaling pathways in human. This study not only provided an effective method to unravel the unknown signaling pathways, but also the deeper understanding for the signaling networks, from the aspect of protein function.
Teaching and Research Office, Department of Automatic Control, College of Mechanical & Electronic Engineering and Automatization, National University of Defense Technology, Kaifu District, Changsha 410073, Hunan, China.
Wei
W
Liu
Dong
D
Li
Yunping
Y
Zhu
Hongwei
H
Xie
Fuchu
F
He
D000818:Animals; D019295:Computational Biology / Q000379:methods*; D030562:Databases, Protein; D004175:Diptera; D006801:Humans; D051379:Mice; D008954:Models, Biological; D060066:Protein Interaction Maps; D011506:Proteins / Q000235:genetics* / Q000378:metabolism*; D051381:Rats; D015203:Reproducibility of Results; D015398:Signal Transduction; D015003:Yeasts
D011506:Proteins