Z. Aidong, Protein interaction networks: Computational analysis, 2009.

B. Boden, S. Günnemann, H. Ho?mann, and T. Seidl, Mining coherent subgraphs in multi-layer graphs with edge labels, Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp.1258-1266, 2012.

F. Bonchi, A. Gionis, F. Gullo, and A. Ukkonen, Distance oracles in edge-labeled graphs, pp.547-558, 2014.

B. Bringmann and S. Nijssen, What Is Frequent in a Single Graph?, Pacific-Asia Conference on Knowledge Discovery and Data Mining, pp.858-863, 2008.
DOI : 10.1007/978-3-540-68125-0_84

A. Cardillo, J. Gómez-gardenes, M. Zanin, M. Romance, D. Papo et al., Emergence of network features from multiplexity, preprint arXiv, pp.1212-2153

M. Elseidy, E. Abdelhamid, S. Skiadopoulos, and P. Kalnis, GraMi, Proceedings of VLDB, pp.517-528, 2014.
DOI : 10.14778/2732286.2732289

M. Fiedler and C. Borgelt, Subgraph Support in a Single Large Graph, Seventh IEEE International Conference on Data Mining Workshops (ICDMW 2007), pp.399-404, 2007.
DOI : 10.1109/ICDMW.2007.74

J. Gonzalez, I. Jonyer, L. Holder, and D. Cook, Ecient mining of graph-based data, Proceedings of the AAAI Workshop on Learning Statistical Models from Relational Data, pp.21-28, 2000.

L. Holder, D. Cook, and S. Djoko, Substucture discovery in the SUBDUE system, KDD workshop, pp.169-180, 1994.

V. Ingalalli, D. Ienco, and P. Poncelet, SuMGra: Querying Multigraphs via Efficient Indexing, International Conference on Database and Expert Systems Applications, pp.387-401, 2016.
DOI : 10.1007/s00778-013-0306-1
URL : https://hal.archives-ouvertes.fr/lirmm-01362431

A. Inokuchi, T. Washio, and H. Motoda, An Apriori-Based Algorithm for Mining Frequent Substructures from Graph Data, European Conference on Principles of Data Mining and Knowledge Discovery, pp.13-23, 2000.
DOI : 10.1007/3-540-45372-5_2

J. Kim and J. Lee, Community Detection in Multi-Layer Graphs, ACM SIGMOD Record, vol.44, issue.3, pp.37-48, 2015.
DOI : 10.14778/1687627.1687709

M. Kuramochi and G. Karypis, Frequent subgraph discovery, Proceedings 2001 IEEE International Conference on Data Mining, pp.313-320, 2001.
DOI : 10.1109/ICDM.2001.989534
URL : http://www-users.itlabs.umn.edu/~karypis/publications/Papers/Postscript/fsg.ps

M. Kuramochi and G. Karypis, Finding Frequent Patterns in a Large Sparse Graph*, Data Mining and Knowledge Discovery, vol.4, issue.1, pp.243-271, 2005.
DOI : 10.1007/s10618-005-0003-9

J. Lee, W. Han, R. Kasperovics, and J. Lee, An in-depth comparison of subgraph isomorphism algorithms in graph databases, Proceedings of the VLDB Endowment, vol.6, issue.2, pp.133-144, 2012.
DOI : 10.14778/2535568.2448946

Y. Li and J. Li, Disease gene identification by random walk on multigraphs merging heterogeneous genomic and phenotype data, BMC Genomics, vol.13, issue.Suppl 7
DOI : 10.1111/j.1365-2265.2008.03175.x

L. Libkin, J. Reutter, and D. Vrgo?, Trial for RDF, Proceedings of the 32nd symposium on Principles of database systems, PODS '13, pp.201-212, 2013.
DOI : 10.1145/2463664.2465226

N. Talukder and M. Zaki, A distributed approach for graph mining in massive networks, Data Mining and Knowledge Discovery, vol.5, issue.9, pp.1-29, 2016.
DOI : 10.1145/1014052.1014091

L. Thomas, S. Valluri, and K. Karlapalem, MARGIN, ACM Transactions on Knowledge Discovery from Data, vol.4, issue.3, 2010.
DOI : 10.1145/1839490.1839491
URL : https://hal.archives-ouvertes.fr/hal-00118047

Y. Wang, J. Ramon, and T. Fannes, An efficiently computable subgraph pattern support measure: counting independent observations, Data Mining and Knowledge Discovery, vol.13, issue.2, pp.444-477, 2013.
DOI : 10.1007/s10618-006-0044-8

X. Yan, H. Cheng, J. Han, and P. Yu, Mining significant graph patterns by leap search, Proceedings of the 2008 ACM SIGMOD international conference on Management of data , SIGMOD '08, pp.433-444, 2008.
DOI : 10.1145/1376616.1376662
URL : http://www.cs.uiuc.edu/homes/hanj/pdf/sigmod08_xifengyan.pdf

X. Yan and J. Han, gspan: Graph-based substructure pattern mining, in: Data Mining, pp.721-724, 2002.