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In this paper, we propose an average-degree based cluster mining algorithm (ACM) for complexes detection in PPI networks. ACM method contains of three stages. Firstly, we make use of PPI network topology, i.e., average degree, to present a new quantitative function and then present a hierarchical algorithm to identify protein complexes. Finally, post-processing is applied to the predicted results...
PPI(Protein-protein interaction) networks decomposition is of great importance for understanding and detecting functional complexes in PPI networks. In this paper, we study spectral clustering for detecting protein complexes, focusing on two open issues in spectral clustering: (i) constructing similarity graphs; (ii) determining the number of clusters. Firstly, we study four similarity graphs to construct...
A social network consists of events and individuals, in which the events denote the activities happening in the system and the individuals denotes the peoples who are attracted into the activities. A memory feature exists in a dynamic social network which leads to the decay of the event attraction, and further influences the structure and the dynamics of the network. In the paper, an agent model for...
In this paper, we give several properties related to highly connected graph. Based on these properties, we give a redefinition of highly connected subgraph which results in an algorithm for determining whether a given graph is highly connected in linear time. Then we present a computationally efficient algorithm, called MOHCS, for mining overlapping highly connected subgraphs. We experimentally evaluate...
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