Edge-based scoring and searching method for identifying condition-responsive protein-protein interaction sub-network.
BACKGROUND
Current high-throughput protein-protein interaction (PPI) data do not provide information about the condition(s) under which the interactions occur. Thus, the identification of condition-responsive PPI sub-networks is of great importance for investigating how a living cell adapts to changing environments.


RESULTS
In this article, we propose a novel edge-based scoring and searching approach to extract a PPI sub-network responsive to conditions related to some investigated gene expression profiles. Using this approach, what we constructed is a sub-network connected by the selected edges (interactions), instead of only a set of vertices (proteins) as in previous works. Furthermore, we suggest a systematic approach to evaluate the biological relevance of the identified responsive sub-network by its ability of capturing condition-relevant functional modules. We apply the proposed method to analyze a human prostate cancer dataset and a yeast cell cycle dataset. The results demonstrate that the edge-based method is able to efficiently capture relevant protein interaction behaviors under the investigated conditions.


BACKGROUND
Supplementary data are available at Bioinformatics online.
Guo
Zheng
Z
Department of Bioinformatics, Bio-pharmaceutical Key Laboratory of Heilongjiang Province-Incubator of State Key Laboratory, Harbin Medical University, Harbin 150086, China. guoz@ems.hrbmu.edu.cn
Wang
Lei
L
Li
Yongjin
Y
Gong
Xue
X
Yao
Chen
C
Ma
Wencai
W
Wang
Dong
D
Li
Yanhui
Y
Zhu
Jing
J
Zhang
Min
M
Yang
Da
D
Rao
Shaoqi
S
Wang
Jing
J
D000465:Algorithms; D003198:Computer Simulation; D008954:Models, Biological; D025941:Protein Interaction Mapping / Q000379:methods*; D020543:Proteome / Q000378:metabolism*; D015398:Signal Transduction / Q000502:physiology*
D020543:Proteome