Identifying network communities with a high resolution

Physical Review E - Statistical, Nonlinear, and Soft Matter Physics

Volumn 77, Issue 1, 2008, Pages

  Ruan, Jianhua ^a,c   Zhang, Weixiong ^a,b  

^a WASHINGTON UNIVERSITY IN ST LOUIS   (United States)

^b WASHINGTON UNIVERSITY SCHOOL OF MEDICINE   (United States)

^c NONE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COMPLEX NETWORKS; MODULARITY FUNCTIONS;

COMPUTATIONAL COMPLEXITY; COMPUTER SCIENCE; HEURISTIC ALGORITHMS; OPTIMIZATION; PROBLEM SOLVING;

LARGE SCALE SYSTEMS;

EID: 38349191347     PISSN: 15393755     EISSN: 15502376     Source Type: Journal    
DOI: 10.1103/PhysRevE.77.016104     Document Type: Article

References (41)

1. M. E. J. Newman, Proc. Natl. Acad. Sci. U.S.A. PNASA6 0027-8424 10.1073/pnas.0307545100 101, 5200 (2004).
2. G. D. Bader and C. W. Hogue, Nat. Biotechnol. NABIF9 1087-0156 10.1038/nbt1002-991 20, 991 (2002).
3. J. Kleinberg and S. Lawrence, Science SCIEAS 0036-8075 10.1126/science.1067014 294, 1849 (2001).
4. R. Albert and A. L. Barabasi, Rev. Mod. Phys. RMPHAT 0034-6861 10.1103/RevModPhys.74.47 74, 47 (2002).
5. M. E. J. Newman, SIAM Rev. SIREAD 0036-1445 10.1137/S003614450342480 45, 167 (2003).
6. M. E. J. Newman, Proc. Natl. Acad. Sci. U.S.A. PNASA6 0027-8424 10.1073/pnas.0601602103 103, 8577 (2006).
7. M. E. J. Newman, Phys. Rev. E PLEEE8 1063-651X 10.1103/PhysRevE.74.036104 74, 036104 (2006).
8. J. B. Pereira-Leal, A. J. Enright, and C. A. Ouzounis, Proteins 18PLAF 0887-3585 10.1002/prot.10505 54, 49 (2004).
9. V. Spirin and L. A. Mirny, Proc. Natl. Acad. Sci. U.S.A. PNASA6 0027-8424 10.1073/pnas.2032324100 100, 12123 (2003).
10. D. M. Wilkinson and B. A. Huberman, Proc. Natl. Acad. Sci. U.S.A. PNASA6 0027-8424 10.1073/pnas.0307740100 101, 5241 (2004).
11. P. O. Fjällström, Linköping Electronic Articles in Computer and Information Science 3, 10 (1998).
12. G. W. Flake, S. Lawrence, C. L. Giles, and F. Coetzee, IEEE Trans. Comput. ITCOB4 0018-9340 35, 66 (2002).
13. F. Radicchi, C. Castellano, F. Cecconi, V. Loreto, and D. Parisi, Proc. Natl. Acad. Sci. U.S.A. PNASA6 0027-8424 10.1073/pnas.0400054101 101, 2658 (2004).
14. M. E. J. Newman, Eur. Phys. J. B EPJBFY 1434-6028 10.1140/epjb/e2004- 00124-y 38, 321 (2004).
15. M. E. J. Newman and M. Girvan, Phys. Rev. E PLEEE8 1063-651X 10.1103/PhysRevE.69.026113 69, 026113 (2004).
16. J. Ruan and W. Zhang, Proceedings of the 21st National Conference on Artificial Intelligence, edited by, Y. Gil, and, R. Mooney, (AAAI, Menio Park, CA, 2006), pp. 470-475.
17. S. White and P. Smyth, Proceedings of the 5th SIAM International Conference on Data Mining, edited by, H. Kargupta, J. Srivastava, C. Kamath, and, A. Goodman, (Society for Industrial and Applied Mathematics, Philadelphia, PA, 2005), pp. 274-284.
18. R. Guimera and L. A. Nunes Amaral, Nature (London) NATUAS 0028-0836 10.1038/nature03288 433, 895 (2005).
19. A. Clauset, M. E. J. Newman, and C. Moore, Phys. Rev. E PLEEE8 1063-651X 10.1103/PhysRevE.70.066111 70, 066111 (2004).
20. U. Brandes, D. Delling, M. Gaertler, R. Goerke, M. Hoefer, Z. Nikoloski, and D. Wagner, e-print arXiv:physics/0608255.
21. L. Danon, J. Duch, A. Diaz-Guilera, and A. Arenas, J. Stat. Mech.: Theory Exp. ZZZZZZ 1742-5468 (2005) P09008.
22. S. Fortunato and M. Barthelemy, Proc. Natl. Acad. Sci. U.S.A. PNASA6 0027-8424 10.1073/pnas.0605965104 104, 36 (2007).
23. S. Muff, F. Rao, and A. Caflisch, Phys. Rev. E PLEEE8 1063-651X 10.1103/PhysRevE.72.056107 72, 056107 (2005).
24. R. Guimerà, M. Sales-Pardo, and L. A. Nunes Amaral, Phys. Rev. E PLEEE8 1063-651X 10.1103/PhysRevE.70.025101 70, 025101 (R) (2004).
25. J. Ruan and W. Zhang, Proceedings of the IEEE International Conference on Data Mining, edited by, N. Ramakrishnan, O. R. Zaïane, Y. Shi, C. W. Clifton, and, X. Wu, (IEEE Computer Society, Washington, D.C., 2007), pp. 643-648.
26. J. Shi and J. Malik, IEEE Trans. Pattern Anal. Mach. Intell. ITPIDJ 0162-8828 10.1109/34.868688 22, 888 (2000).
27. A. Y. Ng, M. I. Jordan, and Y. Weiss, Advances in Neural Information Processing System, edited by, T. G. Dietterich, S. Becker, and, Z. Ghahramani, (MIT Press, Cambridge, MA, 2001), pp. 849-856.
28. C. Elkan, Proceedings of the 20th International Conference on Machine Learning, edited by, T. Fawcett, and, N. Mishra, (AAAI, Menlo Park, CA, 2003), pp. 147-153.
29. http://cic.cs.wustl.edu/qcut/supplemental.pdf
30. R. Milo, N. Kashtan, S. Itzkovitz, M. E. J. Newman, and U. Alon, e-print arXiv:cond-mat/0312028.
31. J. Duch and A. Arenas, Phys. Rev. E PLEEE8 1063-651X 10.1103/PhysRevE.72. 027104 72, 027104 (2005).
32. D. Hand, H. Mannila, and P. Smyth, Principles of Data Mining (Adaptive Computation and Machine Learning) (MIT, Cambridge, MA, 2001).
33. L. Danon, A. Diaz-Guilera, and A. Arenas, J. Stat. Mech.: Theory Exp. ZZZZZZ 1742-5468 (2006) P11010.
34. A. Arenas, A. Diaz-Guilera, and C. Perez-Vicente, Phys. Rev. Lett. PRLTAO 0031-9007 10.1103/PhysRevLett.96.114102 96, 114102 (2006).
35. G. Palla, I. Derenyi, I. Farkas, and T. Vicsek, Nature (London) NATUAS 0028-0836 10.1038/nature03607 435, 814 (2005).
36. J. Reichardt and S. Bornholdt, Phys. Rev. Lett. PRLTAO 0031-9007 10.1103/PhysRevLett.93.218701 93, 218701 (2004).
37. P. N. Tan, M. Steinbach, and V. Kumar, Introduction to Data Mining (Addison-Wesley, Reading, MA, 2005).
38. E. B. Fowlkes and C. L. Mallows, J. Am. Stat. Assoc. JSTNAL 0162-1459 10.2307/2288117 78, 553 (1983).
39. M. Meila, J. Multivariate Anal. 98, 873 (2007). 0047-259X
40. N. J. Krogan, G. Cagney, H. Yu, G. Zhong, X. Guo, A. Ignatchenko, J. Li, S. Pu, and A. P. Datta, Nature (London) NATUAS 0028-0836 10.1038/nature04670 440, 637 (2006).
41. H. W. Mewes, D. Frishman, K. F. Mayer, M. Munsterkotter, O. Noubibou, P. Pagel, T. Rattei, M. Oesterheld, A. Ruepp, and V. Stumpflen, Nucleic Acids Res. NARHAD 0305-1048 10.1093/nar/gkj148 34, D169 (2006).