{"id":17108,"date":"2019-09-24T19:44:53","date_gmt":"2019-09-25T09:50:28","guid":{"rendered":"https:\/\/swarma.org\/?p=17108"},"modified":"2019-09-25T17:50:32","modified_gmt":"2019-09-25T09:50:32","slug":"62b96ed617","status":"publish","type":"post","link":"https:\/\/swarma.org\/?p=17108","title":{"rendered":"\u7f51\u7edc\u79d1\u5b66\u5165\u95e8\uff1a9\u5927\u6280\u5de7\u5e26\u4f60\u4e0a\u624b\u7f51\u7edc\u6570\u636e\u5206\u6790"},"content":{"rendered":"
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<\/span><\/p>\n

\"\u96c6\u667a\"<\/section>\n
\u56fe1\uff1a\u7f51\u7edc\u8282\u70b9\u56fe<\/strong><\/span><\/section>\n<\/p>\n

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<\/strong><\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n

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\u6280\u5de7\u56db\uff1a\u8bf7\u6ce8\u610f\uff0c\u7f51\u7edc\u53ef\u89c6\u5316<\/strong><\/span><\/p>\n

\u53ef\u80fd\u5f88\u6709\u7528\uff0c\u4f46\u53ef\u80fd\u4f1a\u4ea7\u751f\u8bef\u5bfc<\/span><\/strong><\/span><\/p>\n

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\"\u96c6\u667a\"<\/section>\n

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\u6280\u5de7\u516d\uff1a\u907f\u514d\u76f2\u76ee\u4f7f\u7528\u805a<\/strong><\/span><\/p>\n

\u7c7b\u7b97\u6cd5\uff0c\u6700\u597d\u68c0\u67e5\u5b83\u4eec\u4e4b\u95f4\u7684\u5dee\u5f02<\/span><\/strong><\/span><\/p>\n

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\u968f\u673a\u533a\u5757\u6a21\u578b\uff08stochastic block model SBM\uff09\u662f\u57fa\u4e8e\u8fd9\u4e00\u5b9a\u4e49\u7684\u4e00\u79cd\u6d41\u884c\u7684\u65b9\u6cd5[31,33]\uff0c\u5b83\u5df2\u88ab\u5e94\u7528\u5728\u4e0e\u4e00\u4e9b\u751f\u7269\u7f51\u7edc\u76f8\u5173\u7684\u5206\u6790\u4e2d\uff08\u4ee5\u7a81\u51fa\u751f\u6001\u7f51\u7edc\u4e2d\u8fde\u63a5\u4f53[32]\u6216\u529f\u80fd\u7fa4\u7684\u590d\u6742\u7ed3\u6784[34]\uff09\u3002\u5176\u4e2d\u4e00\u4e2a\u91cd\u8981\u7684\u7279\u5f81\u662f\u5b83\u5141\u8bb8\u901a\u8fc7\u4e0d\u540c\u7684\u7edf\u8ba1\u5206\u5e03\u660e\u786e\u5730\u6a21\u62df\u8fb9\u7684\u65b9\u5411\u548c\u6743\u91cd[11]\u3002\u7b2c\u4e09\u79cd\u65b9\u6cd5\u8003\u8651\u5bf9\u6bcf\u4e2a\u8282\u70b9\u5173\u8054\u4e00\u4e2a\u7279\u5f81\u5411\u91cf\uff0c\u7136\u540e\u628a\u76f8\u4f3c\u7279\u5f81\u7684\u8282\u70b9\u805a\u96c6\u5728\u4e00\u8d77\u3002\u8fd9\u5305\u62ec\u57fa\u4e8e\u6a21\u5f0f\uff08motif\uff09\u7684\u65b9\u6cd5[35]\u548c\u5927\u91cf\u65b0\u9896\u7684\u8282\u70b9\u5d4c\u5165\u6280\u672f[36,37]\u3002\u8282\u70b9\u88ab\u63cf\u8ff0\u4e3a\u4e00\u4e2a\u76f8\u5bf9\u5408\u9002\u7684\u4f4e\u7ef4\u7a7a\u95f4\u4e2d\u7684\u70b9\uff0c\u8fd9\u4f7f\u5f97\u5bf9\u591a\u5143\u6570\u636e\u5e94\u7528\u73b0\u6709\u7684\u5404\u79cd\u805a\u7c7b\u65b9\u6cd5\u6210\u4e3a\u53ef\u80fd\u3002\u91cd\u8981\u7684\u662f\u8981\u8ba4\u8bc6\u5230\uff0c\u8fd9\u4e9b\u76f8\u4f3c\u6027\u6982\u5ff5\u81ea\u7136\u800c\u7136\u4f1a\u5bfc\u81f4\u4e0d\u540c\u7684\u8282\u70b9\u805a\u7c7b\u3002\u5728\u8fd9\u4e9b\u9009\u9879\u4e4b\u95f4\u7684\u6289\u62e9\u5fc5\u987b\u7531\u751f\u7269\u5b66\u95ee\u9898\u800c\u4e0d\u662f\u7531\u5b83\u4eec\u5728\u8f6f\u4ef6\u5de5\u5177\u4e2d\u7684\u53ef\u7528\u6027\u6765\u9a71\u52a8\uff08\u6280\u5de71\uff09\u3002<\/span><\/p>\n

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\"\u96c6\u667a\"<\/div>\n

\u56fe3\uff1a\u968f\u673a\u533a\u5757\u6a21\u578b\uff08stochastic block model SBM\uff09<\/span><\/strong><\/span><\/strong><\/span><\/p>\n

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\u6280\u5de7\u4e03\uff1a\u6a21\u62df\u7f51\u7edc\u65f6<\/strong><\/span><\/p>\n

\u4e0d\u8981\u9009\u62e9\u7b80\u5355\u7684\u65b9\u6cd5<\/span><\/strong><\/span><\/p>\n

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\u6700\u540e\uff0c\u5f53\u6240\u7814\u7a76\u7684\u7f51\u7edc\u4e0d\u662f\u76f4\u63a5\u89c2\u6d4b\u5230\u7684\uff0c\u800c\u662f\u7531\u539f\u59cb\u7684\u8d44\u6599\u89e3\u91ca\u5f97\u5230\uff0c\u6709\u5fc5\u8981\u6a21\u62df\u6574\u4e2a\u521b\u5efa\u8fc7\u7a0b\u3002\u8003\u8651\u4ece\u79fb\u52a8\u6570\u636e\u63a8\u65ad\u7684\u8054\u7cfb\u7f51\u7edc\u7684\u60c5\u51b5[23]\uff1a\u53ef\u4ee5\u6a21\u62df\u4fdd\u7559\u539f\u59cb\u6570\u636e\u67d0\u4e9b\u5c5e\u6027\u7684\u8fd0\u52a8\u8f68\u8ff9\u7f51\u7edc\uff0c\u7136\u540e\u5efa\u7acb\u8054\u7cfb\u7f51\u7edc\uff0c\u6216\u76f4\u63a5\u6a21\u62df\u201c\u73b0\u5b9e\u201d\u7684\u8054\u7cfb\u7f51\u7edc\u3002\u524d\u4e00\u79cd\u65b9\u6cd5\u4ece\u672c\u8d28\u4e0a\u8003\u8651\u4e86\u6784\u5efa\u6b65\u9aa4\u5f15\u8d77\u7684\u4e0d\u786e\u5b9a\u6027\u548c\u504f\u5dee\uff0c\u800c\u540e\u4e00\u79cd\u65b9\u6cd5\u53ef\u80fd\u4f1a\u5ffd\u7565\u8fd9\u4e9b\u4e0d\u786e\u5b9a\u6027\u548c\u504f\u5dee\u3002<\/span><\/p>\n

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\u6280\u5de7\u516b\uff1a\u91cd\u65b0\u8003\u8651<\/strong><\/span><\/p>\n

\u6570\u636e\u4ee5\u6784\u5efa\u591a\u4e2a\u7f51\u7edc\u5c42<\/span><\/strong><\/span><\/p>\n

<\/strong><\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n

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\u5f53\u4f7f\u7528\u8fde\u7eed\u8f6e\u6b21\u6570\u636e\u6536\u96c6\u7684\u65f6\u95f4\u5e8f\u5217\u7684\u7f51\u7edc\uff08\u8282\u70b9\u5217\u8868\u53ef\u80fd\u968f\u65f6\u95f4\u53d8\u5316\uff09\u5feb\u7167\u65f6\uff0c\u8be5\u7f51\u7edc\u88ab\u79f0\u4e3a\u52a8\u6001\u7f51\u7edc( Dynamic network )\u3002\u5728\u8fd9\u79cd\u60c5\u51b5\u4e0b\uff0c\u53ef\u4ee5\u8bc4\u4f30\u968f\u65f6\u95f4\u53d8\u5316\u7684\u7f51\u7edc\u7ed3\u6784\uff08\u4f8b\u5982\uff0c\u91cd\u65b0\u8fde\u63a5\u7684\u4ea4\u4e92\u4f5c\u7528\u6216\u968f\u65f6\u95f4\u53d8\u5316\u7684\u7f51\u7edc\u6307\u6807\uff09\u4ee5\u53ca\u5c06\u6280\u5de76\u4e2d\u63d0\u5230\u7684\u6982\u5ff5\u7684\u6269\u5c55\u5e94\u7528\u4e8e\u52a8\u6001\u6848\u4f8b\u4e2d[42,43]\u3002\u4f8b\u5982\uff0c\u53ef\u4ee5\u4ece\u52a8\u6001\u7f51\u7edc\u63a8\u65ad\u51fa\u52a8\u6001\u7684\u52a8\u7269\u793e\u4f1a\u7ed3\u6784\u6765\uff0c\u4ee5\u589e\u5f3a\u5bf9\u75be\u75c5\u4f20\u64ad\u7684\u7406\u89e3[44]\u3002\u53e6\u4e00\u65b9\u9762\uff0c\u5728\u4e0d\u540c\u7684\u7a7a\u95f4\u4f4d\u7f6e\u4e5f\u53ef\u4ee5\u89c2\u5bdf\u5230\u76f8\u4e92\u4f5c\u7528\u3002\u5728\u751f\u6001\u5b66\u4e2d\uff0c\u5b83\u4eec\u901a\u5e38\u805a\u5408\u6210\u4e3a\u4e00\u4e2a\u5143\u7f51\u7edc( Metanetwork )<\/span>\uff08\u6216\u539f\u7f51\u7edc( Mwtaweb ) [45]\uff09\u4e2d\uff0c\u4ee5\u7814\u7a76\u5c40\u90e8\u7f51\u7edc\u4e0e\u8fd9\u79cd\u5143\u7f51\u7edc\u7684\u4e0d\u540c\uff0c\u5e76\u7528\u73af\u5883\u56e0\u7d20\u89e3\u91ca\u8fd9\u4e9b\u53d8\u5316\u3002\u5728\u8fd9\u4e24\u79cd\u60c5\u51b5\u4e0b\uff0c\u591a\u4e2a\u7f51\u7edc\u5c42\u5141\u8bb8\u5c06\u7f51\u7edc\u63cf\u8ff0\u4e3a\u4e0d\u65ad\u6f14\u53d8\u7684\u5bf9\u8c61\uff0c\u5206\u6790\u65e8\u5728\u8bc6\u522b\u4ea4\u4e92\u65f6\u7a7a\u53d8\u5316\u56e0\u7d20\u53ca\u9a71\u52a8\u5b83\u4eec\u7684\u56e0\u7d20\u3002<\/span><\/p>\n

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\"\u96c6\u667a\"<\/section>\n

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\u6280\u5de7\u4e5d\uff1a\u8de8\u8d8a\u4f60\u7684\u5b66\u79d1\uff0c<\/strong><\/span><\/p>\n

\u7814\u8bfb\u7f51\u7edc\u79d1\u5b66\u6587\u732e<\/span><\/strong><\/span><\/p>\n

<\/strong><\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n

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\u7ed3\u8bba<\/span><\/strong><\/span><\/p>\n

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\u8fd9\u91cc\u4ecb\u7ecd\u76849\u4e2a\u6280\u5de7\u63d0\u4f9b\u4e86\u6570\u636e\u5206\u6790\u8005\u5165\u95e8\u7f51\u7edc\u6570\u636e\u5206\u6790\u7684\u4e00\u79cd\u65b9\u5f0f\u3002\u8fd9\u4e9b\u6280\u5de7\u5e76\u4e0d\u662f\u552f\u4e00\u7684\uff0c\u6211\u4eec\u77e5\u9053\u5176\u4ed6\u4e00\u4e9b\u57fa\u4e8e\u7f51\u7edc\u7684\u95ee\u9898\u4f8b\u5982\u7f51\u7edc\u4e2d\u4fe1\u606f\u7684\u4f20\u64ad\u4e5f\u503c\u5f97\u7279\u522b\u5173\u6ce8\u3002\u5c3d\u7ba1\u5982\u6b64\uff0c\u975e\u4e13\u4e1a\u7f51\u7edc\u5206\u6790\u4eba\u5458\u5fc5\u987b\u5bf9\u81ea\u5df1\u9010\u6b65\u5b66\u4e60\u7f51\u7edc\u6982\u5ff5\u548c\u65b9\u6cd5\u7684\u80fd\u529b\u5145\u6ee1\u4fe1\u5fc3\uff0c\u7f51\u7edc\u7684\u6982\u5ff5\u548c\u65b9\u6cd5\u4f1a\u5bf9\u4ed6\u4eec\u7684\u79d1\u5b66\u7814\u7a76\u4ea7\u751f\u6b63\u9762\u7684\u5f71\u54cd\u3002<\/span><\/p>\n

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2. M. Zitnik, R. Sosi, and J. Leskovec, \u201cPrioritizing network communities,\u201d NatCommun, vol. 9, no. 1, p. 2544, 2018.<\/span><\/p>\n

3. B. Wang, A. Pourshafeie, M. Zitnik, J. Zhu, C. D. Bustamante, S. Batzoglou, andJ. Leskovec, \u201cNetwork enhancement as a general method to denoise weightedbiological networks,\u201d Nat Commun, vol. 9, no. 1, p. 3108, 2018.<\/span><\/p>\n

4. R. E. Kass, B. S. Caffo, M. Davidian, X.-L. Meng, B. Yu, and N. Reid, \u201cTensimple rules for effective statistical practice,\u201d 2016.<\/span><\/p>\n

5. R. Diestel, \u201cGraph theory.\u201d http:\/\/diestel-graph-theory.com, 2016.<\/span><\/p>\n

6. A. Barrat, M. Barthelemy, R. Pastor-Satorras, and A. Vespignani, \u201cThearchitecture of complex weighted networks,\u201d Proceedings of the national academyof sciences, vol. 101, no. 11, pp. 3747\u20133752, 2004.<\/span><\/p>\n

7. P. P. Staniczenko, J. C. Kopp, and S. Allesina, \u201cThe ghost of nestedness inecological networks,\u201d Nature communications, vol. 4, p. 1391, 2013.<\/span><\/p>\n

8. G. A. Pavlopoulos, P. I. Kontou, A. Pavlopoulou, C. Bouyioukos, E. Markou, andP. G. Bagos, \u201cBipartite graphs in systems biology and medicine: a survey ofmethods and applications,\u201d GigaScience, vol. 7, no. 4, p. giy014, 2018.<\/span><\/p>\n

9. V. Miele, F. Picard, and S. Dray, \u201cSpatially constrained clustering of ecologicalnetworks,\u201d Methods in Ecology and Evolution, vol. 5, no. 8, pp. 771\u2013779, 2014.<\/span><\/p>\n

10. P. Expert, T. S. Evans, V. D. Blondel, and R. Lambiotte, \u201cUncoveringspace-independent communities in spatial networks,\u201d Proceedings of the NationalAcademy of Sciences, vol. 108, no. 19, pp. 7663\u20137668, 2011.<\/span><\/p>\n

11. M. Mariadassou, S. Robin, C. Vacher, et al., \u201cUncovering latent structure invalued graphs: a variational approach,\u201d The Annals of Applied Statistics, vol. 4,no. 2, pp. 715\u2013742, 2010.<\/span><\/p>\n

12. M. A. Fortuna, R. G. Albaladejo, L. Fern\u00b4andez, A. Aparicio, and J. Bascompte,\u201cNetworks of spatial genetic variation across species,\u201d Proceedings of the NationalAcademy of Sciences, vol. 106, no. 45, pp. 19044\u201319049, 2009.<\/span><\/p>\n

13. D. Hric, R. K. Darst, and S. Fortunato, \u201cCommunity detection in networks:Structural communities versus ground truth,\u201d Physical Review E, vol. 90, no. 6,p. 062805, 2014.<\/span><\/p>\n

14. R. Rossi and N. Ahmed, \u201cThe network data repository with interactive graphanalytics and visualization,\u201d in Twenty-Ninth AAAI Conference on ArtificialIntelligence, 2015.<\/span><\/p>\n

15. G. K. Sandve, A. Nekrutenko, J. Taylor, and E. Hovig, \u201cTen simple rules forreproducible computational research,\u201d PLoS Comput. Biol., vol. 9, no. 10,p. e1003285, 2013.<\/span><\/p>\n

16. M. A. Carey and J. A. Papin, \u201cTen simple rules for biologists learning toprogram,\u201d PLoS Comput. Biol., vol. 14, no. 1, p. e1005871, 2018.<\/span><\/p>\n

17. J. W. Tukey, Exploratory data analysis. Reading: Addison-Wesley, 1977.<\/span><\/p>\n

18. M. Krzywinski, I. Birol, S. J. Jones, and M. A. Marra, \u201cHive plots\u2014rationalapproach to visualizing networks,\u201d Briefings in Bioinformatics, vol. 13, no. 5,pp. 627\u2013644, 2011.<\/span><\/p>\n

19. M. Rubinov and O. Sporns, \u201cComplex network measures of brain connectivity:uses and interpretations,\u201d Neuroimage, vol. 52, no. 3, pp. 1059\u20131069, 2010.<\/span><\/p>\n

20. J. Bascompte, P. Jordano, C. J. Meli\u00b4an, and J. M. Olesen, \u201cThe nested assemblyof plant\u2013animal mutualistic networks,\u201d Proceedings of the National Academy ofSciences, vol. 100, no. 16, pp. 9383\u20139387, 2003.<\/span><\/p>\n

21. R. E. Van Dijk, J. C. Kaden, A. Arg\u00a8uelles-Tic\u00b4o, D. A. Dawson, T. Burke, andB. J. Hatchwell, \u201cCooperative investment in public goods is kin directed incommunal nests of social birds,\u201d Ecology letters, vol. 17, no. 9, pp. 1141\u20131148,2014.<\/span><\/p>\n

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23. D. R. Farine and H. Whitehead, \u201cConstructing, conducting and interpretinganimal social network analysis,\u201d J Anim Ecol, vol. 84, no. 5, pp. 1144\u20131163, 2015.<\/span><\/p>\n

24. A. Costa, A. M. M. Gonzalez, K. Guizien, A. M. Doglioli, J. M. Gomez,A. Petrenko, and S. Allesina, \u201cEcological networks: Pursuing the shortest path,however narrow and crooked,\u201d bioRxiv, p. 475715, 2018.<\/span><\/p>\n

25. B. C. Van Wijk, C. J. Stam, and A. Daffertshofer, \u201cComparing brain networks ofdifferent size and connectivity density using graph theory,\u201d PloS one, vol. 5,no. 10, p. e13701, 2010.<\/span><\/p>\n

26. L. Pellissier, C. Albouy, J. Bascompte, N. Farwig, C. Graham, M. Loreau, M. A.Maglianesi, C. J. Meli\u00b4an, C. Pitteloud, T. Roslin, et al., \u201cComparing speciesinteraction networks along environmental gradients,\u201d Biological Reviews, vol. 93,no. 2, pp. 785\u2013800, 2018.<\/span><\/p>\n

27. S. Fortunato and M. Barthelemy, \u201cResolution limit in community detection,\u201dProceedings of the National Academy of Sciences, vol. 104, no. 1, pp. 36\u201341, 2007.<\/span><\/p>\n

28. S. Kortsch, R. Primicerio, M. Aschan, S. Lind, A. V. Dolgov, and B. Planque,\u201cFood-web structure varies along environmental gradients in a high-latitudemarine ecosystem,\u201d Ecography, vol. 42, no. 2, pp. 295\u2013308, 2019.<\/span><\/p>\n

29. H. K. Norton, D. J. Emerson, H. Huang, J. Kim, K. R. Titus, S. Gu, D. S.Bassett, and J. E. Phillips-Cremins, \u201cDetecting hierarchical genome folding withnetwork modularity,\u201d Nature methods, vol. 15, no. 2, p. 119, 2018.<\/span><\/p>\n

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33. J.-J. Daudin, F. Picard, and S. Robin, \u201cA mixture model for random graphs,\u201dStatistics and computing, vol. 18, no. 2, pp. 173\u2013183, 2008.<\/span><\/p>\n

34. S. K\u00b4efi, V. Miele, E. A. Wieters, S. A. Navarrete, and E. L. Berlow, \u201cHowStructured Is the Entangled Bank? The Surprisingly Simple Organization ofMultiplex Ecological Networks Leads to Increased Persistence and Resilience,\u201dPLoS Biol., vol. 14, no. 8, p. e1002527, 2016.<\/span><\/p>\n

35. D. B. Stouffer, M. Sales-Pardo, M. I. Sirer, and J. Bascompte, \u201cEvolutionaryconservation of species\u2019 roles in food webs,\u201d Science, vol. 335, no. 6075,pp. 1489\u20131492, 2012.<\/span><\/p>\n

36. B. Perozzi, R. Al-Rfou, and S. Skiena, \u201cDeepwalk: Online learning of socialrepresentations,\u201d in Proceedings of the 20th ACM SIGKDD InternationalConference on Knowledge Discovery and Data Mining, KDD \u201914, (New York, NY,USA), pp. 701\u2013710, ACM, 2014.<\/span><\/p>\n

37. A. Grover and J. Leskovec, \u201cnode2vec: Scalable feature learning for networks,\u201d inProceedings of the 22nd ACM SIGKDD international conference on Knowledgediscovery and data mining, pp. 855\u2013864, ACM, 2016.<\/span><\/p>\n

38. U. Brose, T. Jonsson, E. L. Berlow, P. Warren, C. Banasek-Richter, L.-F. Bersier,J. L. Blanchard, T. Brey, S. R. Carpenter, M.-F. C. Blandenier, et al.,\u201cConsumer\u2013resource body-size relationships in natural food webs,\u201d Ecology,vol. 87, no. 10, pp. 2411\u20132417, 2006.<\/span><\/p>\n

39. S. Boccaletti, G. Bianconi, R. Criado, C. I. Del Genio, J. G\u00b4omez-Gardenes,M. Romance, I. Sendina-Nadal, Z. Wang, and M. Zanin, \u201cThe structure anddynamics of multilayer networks,\u201d Physics Reports, vol. 544, no. 1, pp. 1\u2013122,2014.<\/span><\/p>\n

40. S. Pilosof, M. A. Porter, M. Pascual, and S. K\u00b4efi, \u201cThe multilayer nature ofecological networks,\u201d Nature Ecology & Evolution, vol. 1, no. 4, p. 0101, 2017.<\/span><\/p>\n

41. G. Bianconi, Multilayer Networks: Structure and Function. Oxford universitypress, 2018.<\/span><\/p>\n

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43. G. Rossetti and R. Cazabet, \u201cCommunity discovery in dynamic networks: asurvey,\u201d ACM Computing Surveys (CSUR), vol. 51, no. 2, p. 35, 2018.<\/span><\/p>\n

44. D. Farine, \u201cThe dynamics of transmission and thedynamics of networks,\u201dJournal of Animal Ecology, vol. 86, no. 3, pp. 415\u2013418, 2017.<\/span><\/p>\n

45. M. Ohlmann, V. Miele, S. Dray, L. Chalmandrier, L. O\u2019Connor, and W. Thuiller,\u201cDiversity indices for ecological networks: a unifying framework using Hillnumbers,\u201d Ecology letters, 2019.<\/span><\/p>\n

46. M. Zitnik and J. Leskovec, \u201cPredicting multicellular function through multi-layertissue networks,\u201d Bioinformatics, vol. 33, no. 14, pp. i190\u2013i198, 2017.<\/span><\/p>\n

47. B. Bentley, R. Branicky, C. L. Barnes, Y. L. Chew, E. Yemini, E. T. Bullmore,P. E. V\u00b4ertes, and W. R. Schafer, \u201cThe multilayer connectome of caenorhabditiselegans,\u201d PLoS computational biology, vol. 12, no. 12, p. e1005283, 2016.<\/span><\/p>\n

48. A. J. Berenstein, M. P. Magari\u02dcnos, A. Chernomoretz, and F. Ag\u00a8uero, \u201cAmultilayer network approach for guiding drug repositioning in neglected diseases,\u201dPLoS neglected tropical diseases, vol.10, no. 1, p. e0004300, 2016.<\/span><\/p>\n

49. A.-L. Barab\u00b4asi, \u201cNetwork science.\u201d http:\/\/networksciencebook.com, 2019.<\/span><\/p>\n

50. M. Newman, Networks. Oxford university press, 2018.<\/span><\/p>\n

51. P. Goyal and E. Ferrara, \u201cGraph embedding techniques, applications, andperformance: A survey,\u201d Knowledge-Based Systems, vol. 151, pp. 78\u201394, 2018.<\/span><\/p>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n

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<\/span>Vincent Miele , St\u00e9phane Dray ,<\/span>Catherine Matias , St\u00e9phane Robin<\/p>\n

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Nature\u4eba\u7c7b\u884c\u4e3a\uff1a<\/span><\/strong><\/span><\/strong>\u5982\u4f55\u4f18\u5316\u7f51\u7edc\u7ed3\u6784\uff0c\u6700\u5927\u7a0b\u5ea6\u53d1\u6325\u795e\u7ecf\u7f51\u7edc\u7684\u8ba4\u77e5\u6f5c\u529b\uff1f<\/span><\/strong><\/a><\/p>\n

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\u5546\u52a1\u5408\u4f5c\u53ca\u6295\u7a3f\u8f6c\u8f7d\uff5cswarma@swarma.org<\/span><\/strong><\/p>\n

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\u25c6<\/span>\u25c6<\/span>\u25c6<\/span><\/span><\/strong><\/strong><\/h1>\n<\/section>\n

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\u8ba9\u82f9\u679c\u7838\u5f97\u66f4\u731b\u70c8\u4e9b\u5427\uff01<\/span><\/p>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n

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