Sequential patterns mining and gene sequence visualization to discover novelty from microarray data

Journal of Biomedical Informatics

Volumn 44, Issue 5, 2011, Pages 760-774

  Sallaberry, A ^a   Pecheur, N ^b   Bringay, S ^b,c   Roche, M ^b   Teisseire, M ^d  

^a UNIVERSITÉ BORDEAUX 1   (France)

^b LIRMM   (France)

^c UNIV MONTPELLIER   (France)

^d UMR TETIS   (France)

Author keywords

Bioinformatics; Data mining; Gene data; Microarray data; Sequential patterns; Visualization

Indexed keywords

ALZHEIMER'S DISEASE; BIOLOGICAL DOCUMENTS; END USERS; GENE SEQUENCES; MICROARRAY DATA; SEQUENTIAL PATTERNS; SEQUENTIAL PATTERNS MINING; SEQUENTIAL-PATTERN MINING; TREE-MAPS; VISUALIZATION SYSTEM; VISUALIZATION TECHNIQUE;

BIOINFORMATICS; DATA MINING; DISEASES; FLOW VISUALIZATION; GENES; VISUALIZATION;

DATA VISUALIZATION;

ALZHEIMER DISEASE; ARTICLE; DATA MINING; DNA MICROARRAY; GENE EXPRESSION; GENE SEQUENCE; HUMAN; MEDLINE; PRIORITY JOURNAL; SEQUENTIAL PATTERN MINING;

ALGORITHMS; ALZHEIMER DISEASE; DATA MINING; DATABASES, GENETIC; GENE EXPRESSION PROFILING; MICROARRAY ANALYSIS; NEOPLASMS;

EID: 80052902986     PISSN: 15320464     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jbi.2011.04.002     Document Type: Article

References (40)

1. Hoerndli F., David D., Götz J. Functional genomics meets neurodegenerative disorders part ii: Application and data integration. Prog Neurobiol 2005, 76:169-188.
2. Cong GA, Tung X, Pan F, Yang J. Farmer: finding interesting rule groups in microarray datasets. In: SIGMOD conference; 2004. p. 143-54.
3. Khan J., Wei J.S., Ringner M., Saal L.H., Ladanyi M., Westermann F., et al. Classification and diagnostic prediction of cancers using gene expression profiling and artificial neural networks. Nat Med 2001, 76:673-679.
4. Pensa R, Besson J, Boulicaut JF. A methodology for biologically relevant pattern discovery from gene expression data. In: Discovery science, LNCS, vol. 3245; 2004. p. 230-41.
5. Korotkiy M., Middelburg R., Dekker H., Harmelen F.V., Lankelma J. A tool for gene expression based pubmed search through combining data sources. Bioinformatics 2004, 20(12):1980-1982.
6. Salle P, Bringay S, Teisseire M, Chakkour F, Roche M, Rassoul RA, et al. Genemining: identification, visualization, and interpretation of brain ageing signatures. In: MIE; 2009a. p. 767-71.
7. Salle P, Bringay S, Teisseire M. Mining discriminant sequential patterns for aging brain. In: AIME '09: proceedings of the 12th conference on artificial intelligence in medicine; 2009b. p. 365-9.
8. Tanabe L., Scherf U., Smith L.H., Lee J.K., Hunter L., Weinstein J.N. Medminer: an internet text-mining tool for biomedical information, with application to gene expression profiling. Biotechniques 1999, 27:210-214.
9. Zeeberg B.R., Feng W., Wang G., Wang M.D., Fojo A.T., Sunshine M., et al. Gominer: a resource for biological interpretation of genomic and proteomic data. Genome Biol 2003, 4:1-28.
10. Saneifar H, Bringay S, Laurent A, Teisseire M. S2mp: Similarity measure for sequential patterns. In: AusDM; 2008. p. 95-104.
11. Nin J, Salle P, Bringay S, Teisseire M. Using owa operators for gene sequential pattern clustering. In: 22nd IEEE international symposium on computer-based medical systems; 2009.
12. Shneiderman B. The eyes have it: a task by data type taxonomy for information visualizations. In: VL; 1996. p. 336-43.
13. Chi EH, Riedl J, Shoop E, Carlis JV, Retzel E, Barry P. Flexible information visualization of multivariate data from biological sequence similarity searches. In: IEEE visualization; 1996. p. 133-40.
14. Smoot M.E., Bass E.J., Guerlain S.A., Pearson W.R. A system for visualizing and analyzing near-optimal protein sequence alignments. Inf Vis 2005, 4(3):224-237.
15. Lungu M., Xu K. Biomedical information visualization. Lecture Notes in Computer Science 2006, vol. 4417:311-342. Springer. A. Kerren, A. Ebert, J. Meyer (Eds.).
16. Piipari M., Down T.A., Saini H., Enright A., Hubbard T.J. imotifs: an integrated sequence motif visualization and analysis environment. Bioinformatics 2010, 6(26):843-844.
17. Perlin K., Fox D. Pad: an alternative approach to the computer interface. SIGGRAPH '93: proceedings of the 20th annual conference on computer graphics and interactive techniques 1993, 57-64. ACM, New York, NY, USA, ISBN:0-89791-601-8, http://doi.acm.org/10.1145/166117.166125.
18. Stasko J., Görg C., Liu Z. Jigsaw: supporting investigative analysis through interactive visualization. Inf Vis 2008, 7(2):118-132. http://doi.acm.org/10.1145/1466620.1466622.
19. Hearst MA. Tilebars: visualization of term distribution information in full text information access. In: CHI '95: proceedings of the SIGCHI conference on human factors in computing systems; 1995. p. 59-66. ISBN:0-201-84705-1.
20. Sallaberry A, Pecheur N, Bringay S, Roche M, Teisseire M. Discovering novelty in gene data: from sequential patterns to visualization. In: ISVC, vol. 3; 2010. p. 534-43.
21. Brog I., Groenen P. Modern multidimensional scaling: theory and applications 1997, Springer-Verlag, New York, ISBN:0-387-94845-7.
22. Torgerson W.S. Multidimensional scaling I. Theory and method. PSym 1952, 17:401-419.
23. deLeeuw J. Applications of convex analysis to multidimensional scaling. Recent developments in statistics (Proc. European meeting statisticians, Grenoble, 1976) 1977, 133-145. North-Holland, Amsterdam.
24. Gansner, Koren, North. Graph drawing by stress majorization. In: GDRAWING: conference on graph drawing (GD); 2004.
25. de Leeuw J. Convergence of the majorization method for multidimensional scaling. J Classif 1988, 5(2):163-180.
26. Priyantha N.B., Balakrishnan H., Demaine E.D., Teller S.J. Anchor-free distributed localization in sensor networks. SenSys 2003, 340-341. ACM. I.F. Akyildiz, D. Estrin, D.E. Culler, M.B. Srivastava (Eds.).
27. Gansner E.R., Hu Y. Efficient node overlap removal using a proximity stress model. Lecture notes in computer science 2008, vol. 5417:206-217. Springer. I.G. Tollis, M. Patrignani (Eds.).
28. Delaunay B. Sur la sphère vide. Izvestia Akademia Nauk SSSR, VII Seria. Otdelenie Matematicheskii i Estestvennyka Nauk 1934, 7:793-800.
29. Willett W, Heer J, Agrawala M. Scented widgets: improving navigation cues with embedded visualizations. 2007;13:1129-36.
30. Fekete JD, Plaisant C. Excentric labeling: dynamic neighborhood labeling for data visualization. In: CHI; 1999. p. 512-9.
31. Nguyen T., Zhang J. A novel visualization model for web search results. IEEE Trans Vis Comput Graph 2006, 12(5):981-988. http://doi.ieeecomputersociety.org/10.1109/TVCG.2006.111.
32. Jacquemin C., Folch H., Garcia K., Nugier S. Visualisation interactive d'espaces documentaires. Inf Interact Intell 2005, 5(1):59-84.
33. Reingold E.M., Tilford J.S. Tidier drawings of trees. IEEE Trans Softw Eng 1981, 7(2):223-228.
34. Johnson B, Shneiderman B. Tree maps: a space-filling approach to the visualization of hierarchical information structures. In: IEEE visualization; 1991. p. 284-91.
35. Bruls M, Huizing K, van Wijk JJ. Squarified treemaps. In: Proc joint Eurographics/IEEE TVCG symp visualization, VisSym; 2000. p. 33-42.
36. Munzner T. A nested process model for visualization design and validation. IEEE Trans Vis Comput Graph 2009, 15(6):921-928.
37. Saraiya P., North C., Duca K. An insight-based methodology for evaluating bioinformatics visualizations. IEEE Trans Vis Comput Graph 2005, 11:443-456. http://portal.acm.org/citation.cfm?id=1070610.1070747. 10.1109/TVCG.2005.53.
38. Ammenwerth E. Can evaluation studies benefit from triangulation? a case study. Int J Med Inform 2003, 70(2-3):237-248.
39. Shneiderman B. Dynamic queries for visual information seeking. IEEE Softw 1994, 11:70-77.
40. Roberts J.C. State of the art: coordinated & multiple views in exploratory visualization. Proceedings of the 5th international conference on coordinated & multiple views in exploratory visualization (CMV2007) 2007, 61-71. IEEE Computer Society Press.