Merging network patterns: a general framework to summarize biomedical network data
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Almansoori W, Gao S, Jarada TN, Elsheikh AM, Murshed AN, Jida J, Alhajj R, Rokne J (2012) Link prediction and classification in social networks and its application in healthcare and systems biology. Netw Model Anal Health Inform Bioinforma. doi: 10.1007/s13721-012-0005-7
Bastian M, Heymann S, Gephi MJ (2009) An open source software for exploring and manipulating networks. In: ICWSM
Bron C, Kerbosch J (1973) Algorithm 457: finding all cliques of an undirected graph. Commun ACM 16(9):575–577
Burdick D, Calimlim M, Flannick J, Gehrke J, Yiu T (2005) Mafia: a maximal frequent itemset algorithm. IEEE Trans Knowl Data Eng 17(11):1490–1504
Carroll JS, Meyer CA, Song J, Li W et al (2006) Genome-wide analysis of estrogen receptor binding sites. Nat Genet 38(11):1289–1297
Desmedt C, Haibe-Kains B, Wirapati P et al (2008) Biological processes associated with breast cancer clinical outcome depend on the molecular subtypes. Clin Cancer Res 14(16):5158–5165
Du N, Wang B, Wu B, Wang Y (2008) Overlapping community detection in bipartite networks. In: Web intelligence, pp 176–179
Duan R, Pettie S, Su H-H (2011) Scaling algorithms for approximate and exact maximum weight matching
Han J, Kamber M, Pei J (2011) Data mining: concepts and techniques, 3rd edn. Elsevier
Jin R, Hong H, Wang H, Ruan N, Xiang Y (2010) Computing label-constraint reachability in graph databases. In: SIGMOD conference, pp 123–134
Jin R, Ruan N, Xiang Y, Lee VE (2012) A highway-centric labeling approach for answering distance queries on large sparse graphs. In: SIGMOD conference
Jin R, Xiang Y, Hong H, Huang K (2010) Block interaction: a generative summarization scheme for frequent patterns. In: UP ’10 proceedings of the ACM SIGKDD workshop on useful patterns, pp 55–64
Johnson DS, Yannakakis M, Papadimitriou CH (1988) On generating all maximal independent sets. Inf Process Lett 27(3):119–123
Karp R (1972) Reducibility among combinatorial problems. In: Miller R, Thatcher J (eds) Complexity of computer computations. Plenum Press, New York, pp 85–103
Kutalik Z, Beckmann JS, Bergmann S (2008) A modular approach for integrative analysis of large-scale gene-expression and drug-response data. Nat Biotechnol 26(5):531–539
Li J, Liu Y, Gao H (2011) Efficient algorithms for summarizing graph patterns. IEEE Trans Knowl Data Eng 23(9):1388–1405
Li J, Liu G, Li H, Wong L (2007) Maximal biclique subgraphs and closed pattern pairs of the adjacency matrix: a one-to-one correspondence and mining algorithms. IEEE Trans Knowl Data Eng 19(12):1625–1637
Li J, Sim K, Liu G, Wong L (2008) Maximal quasi-bicliques with balanced noise tolerance: concepts and co-clustering applications. In: SDM, pp 72–83
Lucchese C, Orlando S, Perego R (2010) A generative pattern model for mining binary datasets. In: SAC, pp 1109–1110
Micali S, Vazirani VV (1980) An $$\mathcal{O}(\sqrt{|V|}{|E|})$$ algorithm for finding maximum matching in general graphs. In: FOCS, pp 17–27
Miettinen P, Mielikäinen T, Gionis A, Das G, Mannila H (2008) The discrete basis problem. IEEE Trans Knowl Data Eng 20(10):1348–1362
Mushlin RA, Gallagher S, Kershenbaum A, Rebbeck TR (2009) Clique-finding for heterogeneity and multidimensionality in biomarker epidemiology research: the chamber algorithm. PloS one 4(3):4862
Ravetti MG, Moscato P (2008) Identification of a 5-protein biomarker molecular signature for predicting alzheimer’s disease. PLoS One 3(9):3111
Reyal F, van Vliet MH, Armstrong NJ et al (2008) A comprehensive analysis of prognostic signatures reveals the high predictive capacity of the proliferation, immune response and rna splicing modules in breast cancer. Breast Cancer Res 10(6):R93
Robinson PN, Köhler S, Bauer S, Seelow D, Horn D, Mundlos S (2008) The human phenotype ontology: a tool for annotating and analyzing human hereditary disease. Am J Hum Genet 83(5):610–615
Seidman SB, Foster BL (1978) A graph-theoretic generalization of the clique concept. J Math Sociol 6(1):139–154
Slink RS (1973) An optimally efficient algorithm for the single-link cluster method. Comput J 16(1):30–34
Tsukiyama S, Ide M, Ariyoshi H, Shirakawa I (1977) A new algorithm for generating all the maximal independent sets. SIAM J Comput 6:505
Uppalapati P, Xiang Y, Huang K (2010) Predicting prognostic markers for glioma using gene co-expression network analysis. In: Proceedings of the first ACM international conference on bioinformatics and computational biology, pp 546–551
van de Vijver MJ, He YD, van ’t Veer LJ et al (2002) A gene-expression signature as a predictor of survival in breast cancer. New Engl J Med 347(25):1999–2009
van’t Veer LJ, Dai H, van de Vijver MJ et al (2002) Gene expression profiling predicts clinical outcome of breast cancer. Nature 415(6871):530–536
Wang Y, Klijn PGM, Zhang Y et al (2005) Gene-expression profiles to predict distant metastasis of lymph-node-negative primary breast cancer. Lancet 365(9460):671–679
Wirapati P, Sotiriou C, Kunkel S et al (2008) Meta-analysis of gene expression profiles in breast cancer: toward a unified understanding of breast cancer subtyping and prognosis signatures. Breast Cancer Res 10(4):R65
Xiang Y, Zhang CQ, Huang K (2012) Predicting glioblastoma prognosis networks using weighted gene co-expression network analysis on tcga data. BMC Bioinform 13(Suppl 2):S12
Xiang Y, Jin R, Fuhry D, Dragan FF (2011) Summarizing transactional databases with overlapped hyperrectangles. Data Min Knowl Discov 23(2):215–251
Xiang Y, Payne P, Huang K (2012) Transactional database transformation and its application in prioritizing human disease genes. IEEE/ACM Trans Comput Biol Bioinform 9(1):294–304
