Module identification in bipartite networks with applications to directed networks Export

@misc{citeulike:1434949, abstract = {Modularity is one of the most prominent properties of real-world complexnetworks. Here, we address the issue of module identification in an importantclass of networks known as bipartite networks. Nodes in bipartite networks aredivided into two non-overlapping sets, and the links must have one end nodefrom each set. We suggest a novel approach especially suited for moduledetection in bipartite networks, and define a set of random networks thatpermit the evaluation of the accuracy of the new approach. Finally, we discusshow our approach can also be used to accurately identify modules in directedunipartite networks.}, archivePrefix = {arXiv}, author = {Guimera, R. and Sales-Pardo, M. and Amaral, L. A. N.}, citeulike-article-id = {1434949}, citeulike-linkout-0 = {http://arxiv.org/abs/physics/0701151}, citeulike-linkout-1 = {http://arxiv.org/pdf/physics/0701151}, day = {12}, eprint = {physics/0701151}, journal = {Physical Review E (Statistical, Nonlinear, and Soft Matter Physics)}, keywords = {bipartite, community-detection, community-finding, complexnetwork, modularity, networks, physics, u24}, month = {Jan}, number = {3}, pages = {036102+}, posted-at = {2009-06-10 01:29:28}, priority = {2}, title = {Module identification in bipartite networks with applications to directed networks}, url = {http://arxiv.org/abs/physics/0701151}, volume = {76}, year = {2007} }

TY - ELEC ID - citeulike:1434949 L3 - citeulike-article-id:1434949 N2 - Modularity is one of the most prominent properties of real-world complexnetworks. Here, we address the issue of module identification in an importantclass of networks known as bipartite networks. Nodes in bipartite networks aredivided into two non-overlapping sets, and the links must have one end nodefrom each set. We suggest a novel approach especially suited for moduledetection in bipartite networks, and define a set of random networks thatpermit the evaluation of the accuracy of the new approach. Finally, we discusshow our approach can also be used to accurately identify modules in directedunipartite networks. IS - 3 JF - Physical Review E (Statistical, Nonlinear, and Soft Matter Physics) TI - Module identification in bipartite networks with applications to directed networks VL - 76 SP - 036102 KW - bipartite KW - community-detection KW - community-finding KW - complexnetwork KW - modularity KW - networks KW - physics KW - u24 AU - Guimera, R AU - Sales-Pardo, M AU - Amaral, LAN PY - 2007/Jan/12/ UR - http://arxiv.org/abs/physics/0701151 ER -