We propose several characterizations of weighted complex networks by incorporating the concept of metaweight into the clustering coefficient, degree correlation, and module decomposition. These incorporations make it possible to describe weighted networks depending on how strongly we emphasize...

In this paper, we present an alternate algorithm for detecting overlapping community structures in the complex network. Two concepts named the maximal sub-graph and the clustering coefficient between two neighboring communities are introduced. First, all the maximal sub-graphs are extracted from...

In this work, we analyze gossip spreading on weighted networks. We try to define a new metric to classify weighted complex networks using our model. The model proposed here is based on the gossip spreading model introduced by Lind et al. on unweighted networks. The new metric is based on gossip...

In this paper, we develop a general analytical method to compute clustering coefficients of growing networks. This method can be applied to any network as long as we can construct and solve the dynamic equation for the degree of any node. We also verify the accuracy of the method through simulation.

Gene co-expression networks are increasingly used to explore the system-level functionality of genes. The network construction is conceptually straightforward: nodes represent genes and nodes are connected if the corresponding genes are significantly co-expressed across appropriately chosen...