Guimin Qin

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The majority of recent graph mining approaches have focused on analyzing static interaction networks, neglecting the fact that most real-world networks are dynamic in nature. In this paper, we define a framework to find evolution patterns which are regular in dynamic networks. These patterns can be used to characterize the local properties of dynamic(More)
Despite several algorithms for searching subgraphs in motif detection presented in the literature, no effort has been done for characterizing their performance till now. This paper presents a methodology to evaluate the performance of three algorithms: edge sampling algorithm (ESA), enumerate subgraphs (ESU) and randomly enumerate subgraphs (RAND-ESU). A(More)
The disease biomarkers can help make accurate diagnosis and therefore give appropriate interventions. In the past years, the accumulation of various kinds of 'omics' data, e.g. genomics and transcriptomics, makes it possible to identify disease biomarkers in a more efficient way. In particular, the molecular networks that describe the functional(More)
With the development in research, teaching and literature work in traditional Chinese medicine and pharmacology (TCMP) by means of computers, it has been found that the existing Chinese character operative systems cannot meet the need of carrying out information processing and software development in this field, since these systems do not include many of(More)
Many complex networks in the real world demonstrate similar patterns, including the scale-free property and strong community structure. In this paper, we present a novel parameter-free community detection algorithm based on the scale-free property of networks, named ScaleFreeCDA. The basic idea behind it is two mechanisms, i.e., node growth and preferential(More)