We suggest a fast method for finding possibly overlapping network communities of a desired size and link density. Our method is a natural generalization of the finite-T superparamagnetic Potts clustering introduced by Blatt et al (1996 Phys. Rev. Lett.76 3251) and the annealing of the Potts model with a global antiferromagnetic term recently suggested by Reichard and Bornholdt (2004 Phys. Rev. Lett.93 21870). Like in both cited works, the proposed generalization is based on ordering of the ferromagnetic Potts model; the novelty of the proposed approach lies in the adjustable dependence of the antiferromagnetic term on the population of each Potts state, which interpolates between the two previously considered cases. This adjustability allows one to empirically tune the algorithm to detect the maximum number of communities of the given size and link density. We illustrate the method by detecting protein complexes in high-throughput protein binding networks.

中文翻译：

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在稀疏网络中寻找介观社区


我们建议一种快速方法来查找具有所需大小和链接密度的可能重叠的网络社区。我们的方法是 Blatt 等人 (1996 Phys. Rev. Lett.76 3251) 引入的有限 T 超顺磁 Potts 聚类的自然推广，以及 Reichard 和 Bornholdt 最近提出的具有全局反铁磁项的 Potts 模型退火 (2004物理学Rev.Lett.93 21870）。与两篇引用的著作一样，所提出的概括是基于铁磁 Potts 模型的排序；所提出方法的新颖性在于反铁磁项对每个波茨态的总体的可调整依赖性，其在先前考虑的两种情况之间进行插值。这种可调整性允许人们凭经验调整算法来检测给定大小和链接密度的社区的最大数量。我们通过检测高通量蛋白质结合网络中的蛋白质复合物来说明该方法。