Inferring domain-domain interactions from protein-protein interactions in the complex network conformation

doi:10.1186/1752-0509-6-S1-S7

CORC > 数学与系统科学研究院 > 中国科学院数学与系统科学研究院 > 应用数学研究所

	Inferring domain-domain interactions from protein-protein interactions in the complex network conformation
	Chen,Chen 1; Zhao,Jun-Fei 1; Huang,Qiang 1; Wang,Rui-Sheng 2; Zhang,Xiang-Sun1,3
刊名	BMC Systems Biology
	2012-07-16
卷号	6 期号:Suppl 1
ISSN号	1752-0509
DOI	10.1186/1752-0509-6-S1-S7
英文摘要	AbstractBackgroundAs protein domains are functional and structural units of proteins, a large proportion of protein-protein interactions (PPIs) are achieved by domain-domain interactions (DDIs), many computational efforts have been made to identify DDIs from experimental PPIs since high throughput technologies have produced a large number of PPIs for different species. These methods can be separated into two categories: deterministic and probabilistic. In deterministic methods, parsimony assumption has been utilized. Parsimony principle has been widely used in computational biology as the evolution of the nature is considered as a continuous optimization process. In the context of identifying DDIs, parsimony methods try to find a minimal set of DDIs that can explain the observed PPIs. This category of methods are promising since they can be formulated and solved easily. Besides, researches have shown that they can detect specific DDIs, which is often hard for many probabilistic methods. We notice that existing methods just view PPI networks as simply assembled by single interactions, but there is now ample evidence that PPI networks should be considered in a global (systematic) point of view for it exhibits general properties of complex networks, such as 'scale-free' and 'small-world'.ResultsIn this work, we integrate this global point of view into the parsimony-based model. Particularly, prior knowledge is extracted from these global properties by plausible reasoning and then taken as input. We investigate the role of the added information extensively through numerical experiments. Results show that the proposed method has improved performance, which confirms the biological meanings of the extracted prior knowledge.ConclusionsThis work provides us some clues for using these properties of complex networks in computational models and to some extent reveals the biological meanings underlying these general network properties.
语种	英语
出版者	BioMed Central
WOS记录号	BMC:10.1186/1752-0509-6-S1-S7
内容类型	期刊论文
源URL	[http://ir.amss.ac.cn/handle/2S8OKBNM/260]
专题	应用数学研究所
通讯作者	Zhang,Xiang-Sun
作者单位	1.Chinese Academy of Sciences; Academy of Mathematics and Systems Science 2.Pennsylvania State University; Department of Physics 3.Chinese Academy of Sciences; National Center for Mathematics and Interdisciplinary Sciences
推荐引用方式 GB/T 7714	Chen,Chen,Zhao,Jun-Fei,Huang,Qiang,et al. Inferring domain-domain interactions from protein-protein interactions in the complex network conformation[J]. BMC Systems Biology,2012,6(Suppl 1).
APA	Chen,Chen,Zhao,Jun-Fei,Huang,Qiang,Wang,Rui-Sheng,&Zhang,Xiang-Sun.(2012).Inferring domain-domain interactions from protein-protein interactions in the complex network conformation.BMC Systems Biology,6(Suppl 1).
MLA	Chen,Chen,et al."Inferring domain-domain interactions from protein-protein interactions in the complex network conformation".BMC Systems Biology 6.Suppl 1(2012).