Title :
Communities analysis in protein-protein interaction networks
Author :
Kan Li ; Yin Pang
Author_Institution :
Sch. of Comput. Sci. Technol., Beijing Inst. of Technol., Beijing, China
Abstract :
No common definition of community has been agreed upon till now. One topology can be of different types, uni-partite or bipartite/multipartite. Most of the former literatures are proposed for one type of community. As the understanding of the community definition is different, the grouping results always applicable to the specified network. If the definition changes, the grouping result will no longer be "good". To do the community detection in mixed protein-protein interaction (PPI) networks, we propose a community detection method with two steps. Firstly, group vertices "must be" in the same community by properties; secondly, find overlapping vertices by functions. We apply the energy model to find community structure in PPI networks. The results show that our method is applicable to PPI network, unipartite, bipartite or mixed. It groups vertices with similar property/roles in the same community and finds overlapping vertices in the network.
Keywords :
complex networks; graph theory; molecular biophysics; network topology; proteins; bipartite network topology; community analysis; community detection method; mixed protein-protein interaction networks; multipartite network topology; unipartite network topology; Communities; Computer science; Educational institutions; Electronic mail; Network topology; Proteins; Topology; PPI networks; community detection; energy model; overlapping communities;
Conference_Titel :
Bioinformatics and Biomedicine (BIBM), 2013 IEEE International Conference on
Conference_Location :
Shanghai
DOI :
10.1109/BIBM.2013.6732757