ConnectedAlign: a PPI network alignment method for identifying conserved protein complexes across multiple species

被引:4
|
作者
Gao, Jianliang [1 ]
Song, Bo [2 ]
Hu, Xiaohua [2 ]
Yan, Fengxia [3 ]
Wang, Jianxin [1 ]
机构
[1] Cent S Univ, Sch Informat Sci & Engn, Changsha 410083, Hunan, Peoples R China
[2] Drexel Univ, Coll Comp & Informat, Philadelphia, PA 19104 USA
[3] Natl Univ Def Technol, Coll Liberal Arts & Sci, Changsha 410073, Hunan, Peoples R China
来源
BMC BIOINFORMATICS | 2018年 / 19卷
基金
中国国家自然科学基金;
关键词
Network alignment; Big data; Graph data analysis; INFORMATION;
D O I
10.1186/s12859-018-2271-6
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Background: In bioinformatics, network alignment algorithms have been applied to protein-protein interaction (PPI) networks to discover evolutionary conserved substructures at the system level. However, most previous methods aim to maximize the similarity of aligned proteins in pairwise networks, while concerning little about the feature of connectivity in these substructures, such as the protein complexes. Results: In this paper, we identify the problem of finding conserved protein complexes, which requires the aligned proteins in a PPI network to form a connected subnetwork. By taking the feature of connectivity into consideration, we propose ConnectedAlign, an efficient method to find conserved protein complexes from multiple PPI networks. The proposed method improves the coverage significantly without compromising of the consistency in the aligned results. In this way, the knowledge of protein complexes in well-studied species can be extended to that of poor-studied species. Conclusions: We conducted extensive experiments on real PPI networks of four species, including human, yeast, fruit fly and worm. The experimental results demonstrate dominant benefits of the proposed method in finding protein complexes across multiple species.
引用
收藏
页数:7
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