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原文連結
論文資訊
- 類型：已發表論文
- 日期：2014-06-25
摘要
Background: Community structure is ubiquitous in 生物 網絡s. There has been an increased interest in unraveling the community structure of 生物 systems as it may provide important insights into a system's functional components and the impact of local structures on dynamics at a global scale. Choosing an appropriate community detection algorithm to identify the community structure in an empirical 網絡 can be difficult, however, as the many algorithms available are based on a variety of cost functions and are difficult to validate. Even when community structure is identified in an empirical system, disentangling the effect of community structure from other 網絡 properties such as clustering coefficient and assortativity can be a challenge. Results: Here, we develop a generative model to produce undire
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