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Title: ConnectedAlign: a PPI network alignment method for identifying conserved protein complexes across multiple species
Abstract 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.  more » « less
Award ID(s):
1744661
PAR ID:
10109600
Author(s) / Creator(s):
Date Published:
Journal Name:
BMC bioinformatics
Volume:
supple 9
ISSN:
1471-2105
Page Range / eLocation ID:
45-51
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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