___

• D.A. Benson, I. Karsch-Mizrachi, D.J. Lipman, J. Ostell, B.A. Rapp, and D.L. Wheeler. GenBank. Nucleic Acids Research, 28(1): 15—18, January 2000.
• A. Bairoch, B. Boeckmann, S. Ferro, and E. Gasteiger. Swiss-Prot: juggling between evolution and stability. Briefings in Bioinformatics, 1:39-55, 2004.
• Michael Baudis and Michael L. Cleary. Progenetix.net: an online repository for molecular cytogenetic aberration data. Bioinformatics, 17(12): 1228-1229, 2001.
• H Ogata, S Goto, K Sato,WFujibuchi, H Bono, and M Kanehisa. KEGG: Kyoto Encyclopedia of Genes and Genomes. Nucleic Acids Research, 27(1):29-34, 1999.
• Peter Damaschke. Graph-Theoretic Concepts in Computer Science, volume 484/1991 of Lecture Notes in Computer Science, pages 72-78. Springer Berlin / Heidelberg, 1991.
• Wojciech Szpankowski Mehmet Koyuturk, Ananth Grama. An efficient algorithm for detecting frequent subgraphs in biological networks. In ISMB/ECCB (Supplement of Bioinformatics), pages 200-207, 2004.
• Milo R, Shen-Orr S, Itzkovitz S, et al. Network motifs: simple building blocks of complex networks. Science 2002; 298:824-27.
• Kashtan N, Alon U. Spontaneous evolution of modularity and network motifs. Proc Natl Acad Sci USA 2005;102:13773-78.
• Sole' RV, Valverde S. Are network motifs the spandrels of cellular complexity? Trends Ecol Evol 2006;21:419-22.
• Bottani S, Vergassola M, Mazurie A. An evolutionary and functional assessment of regulatory network motifs. Genome Biol 2005;6:R35.
• Kashani ZRM, Ahrabian H, Elahi E, et al. Kavosh: a new algorithm for finding network motifs. BMC Bioinformatics 2009;10:318.[
• Grochow JA, Kellis M. Network motif discovery using sub-graph enumeration and symmetry breaking. Res Comp Mol Biol 2007;4456:92-106.
• Kuramochi M, Karypis G. Frequent sub-graph discovery. In: Proceedings of IEEE International Conference on Data Mining 2001, San Jose, California, 313-20.
• Schreiber F, Schwobbermeyer H. Frequency concepts and pattern detection for the analysis of motifs in networks. LectNotes Comput Sci 2005;3737:89-104.
• Babai, L., Luks, E. M., 1983. Canonical labeling of graphs. In: STOC. pp 171-183.
• Kuramochi M, Karypis G. Finding frequent patterns in a large sparse graph. Data Mining and Knowledge Discovery 2005, 11(3), 243-271.
• Baskerville, K., Paczuski, M., 2006. Subgraph ensembles and motif discovery using an alternative heuristic for graph isomorphism. Physical Review E 74 (5), 51903.
• R. Y. Pinter, O. Rokhlenko, E. Yeger-Lotem, and M. Ziv-Ukelson, Alignment of metabolic pathways, Bioinformatics. 21(16), 3401-3408 (Aug, 2005). doi: 10.1093/bioinformatics/bti554.
• T. Shlomi, D. Segal, E. Ruppin, and R. Sharan, QPath: a method for querying pathways in a protein-protein interaction network, BMC Bioinformatics. 7, 199 (2006). doi: 10.1186/1471 2105-7-199.
• F. Ay and T. Kahveci. SubMAP: Aligning Metabolic Pathways with Subnetwork Mappings. In RECOMB, pp. 15-30 (2010)
• F. Ay, T. Kahveci, and V. de Crecy-Lagard, A fast and accurate algorithm for comparative analysis of metabolic pathways, J. Bioinformatics and Computational Biology. 7(3), 389-428 (2009).
• Y. Tian, R. C. McEachin, C. Santos, D. J. States, and J. M. Patel, SAGA: a subgraph matching tool for biological graphs, Bioinformatics. 23(2), 232-239 (2007). doi: 10.1093/bioinformatics/btl571.
• R. Giugno and D. Shasha. GraphGrep: A fast and universal method for querying graphs. In Proc. 16th Int Pattern Recognition Conf, vol. 2, pp. 112-115 (2002). doi: 10.1109/ICPR.2002.1048250.
• X. Yan, P. S. Yu, and J. Han. Graph indexing: a frequent structure-based approach. In SIGMOD, pp. 335-346, ACM, New York, NY, USA (2004). ISBN 1-58113-859-8. doi: http://doi.acm.org/10.1145/1007568.1007607.
• X. Yan, P. S. Yu, and J. Han. Substructure similarity search in graph databases. In SIGMOD Conference, pp. 766-777 (2005).
• H. He and A. K. Singh, Closure-Tree: An index structure for graph queries, International Conference on Data Engineering. 0, 38 (2006).
• S. Berretti, A. D. Bimbo, and E. Vicario, Efficient matching and indexing of graph models in content-based retrieval, IEEE Trans. Pattern Anal. Mach. Intell. 23(10), 1089-1105 (2001).
• P. Ciaccia, M. Patella, and P. Zezula. M-tree: An efficient access method for similarity search in metric spaces. In VLDB'97, Proceedings of 23rd International Conference on Very Large Data Bases, pp. 426-435, Morgan Kaufmann (1997). ISBN 1-55860-470-7.
• J. Lee, J.-H. Oh, and S. Hwang. Strg-index: Spatio-temporal region graph indexing for large video databases. In SIGMOD Conference, pp. 718-729 (2005).
• G. Gulsoy and T. Kahveci, RINQ: Reference-based indexing for network queries, Bioinformatics [ISMB/ECCB]. 27(13), 149{158 (2011).