Gene expression data analysis with a dynamically extended self-organized map that exploits class information

Bioinformatics

Volumn 18, Issue 11, 2002, Pages 1446-1453

  Mavroudi, Seferina ^a   Papadimitriou, Stergios ^a,b   Bezerianos, Anastasios ^a  

^a UNIVERSITY OF PATRAS   (Greece)

^b TECHNOLOGICAL EDUCATIONAL INSTITUTE OF KAVALA   (Greece)

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; AUTOANALYSIS; CLASSIFICATION; CLUSTER ANALYSIS; COMPREHENSION; CONTROLLED STUDY; COST BENEFIT ANALYSIS; DATA ANALYSIS; DECISION MAKING; GENE EXPRESSION; GENE MAPPING; MATHEMATICAL COMPUTING; MOLECULAR MODEL; PERFORMANCE; PRIORITY JOURNAL; ALGORITHM; ARTIFICIAL NEURAL NETWORK; AUTOMATED PATTERN RECOGNITION; DNA MICROARRAY; DNA SEQUENCE; EVALUATION; FEEDBACK SYSTEM; GENE EXPRESSION PROFILING; GENE EXPRESSION REGULATION; GENETICS; GENOME; METHODOLOGY; NUCLEIC ACID DATABASE; SACCHAROMYCES CEREVISIAE; SENSITIVITY AND SPECIFICITY; SEQUENCE ALIGNMENT; VALIDATION STUDY;

DNA;

ALGORITHMS; DATABASES, NUCLEIC ACID; DNA; FEEDBACK; GENE EXPRESSION PROFILING; GENE EXPRESSION REGULATION; GENOME, FUNGAL; NEURAL NETWORKS (COMPUTER); OLIGONUCLEOTIDE ARRAY SEQUENCE ANALYSIS; PATTERN RECOGNITION, AUTOMATED; SACCHAROMYCES CEREVISIAE; SENSITIVITY AND SPECIFICITY; SEQUENCE ALIGNMENT; SEQUENCE ANALYSIS, DNA;

EID: 0036855422     PISSN: 13674803     EISSN: 13674811     Source Type: Journal    
DOI: 10.1093/bioinformatics/18.11.1446     Document Type: Article

References (25)

1. Alahakoon,D., Halgamuge,S. and Srinivasan,B. (2000) Dynamic self-organizing maps with controlled growth for knowledge discovery. IEEE Trans. Neural Networks, 11, 601-614.
2. Azuaje,F. (2001) A computational neural approach to support the discovery of gene function and classes of cancer. IEEE Trans. Biomed. Eng., 48, 332-339.
3. Bezerianos,A., Vladutu,L. and Papadimitriou,S. (2000) Hierarchical state space partitioning with the network self-organizing map for the effective recognition of the ST-T segment change. IEEE Medical and Biological Engineering and Computing, 38, 406-415.
4. Bishop,C.M. (1996) Neural Networks for Pattern Recognition. Clarendon Press, Oxford.
5. Brazma,A. and Jaak,V. (2000) Gene expression data analysis. FEBS Lett., 480, 17-24.
6. Brown,M., Grundy,W.N., Lin,D., Cristianini,N., Sugnet,C.W., Furey,T., Ares,M. and Haussler,D. (1997) Knowledge-based analysis of microarray gene expression data by using support vector machines. Proc Natl Acad. Sci. USA, 97, 262-267.
7. Campos,M. and Carpenter,G.A. (2001) S-TREE: self-organizing trees for data clustering and online vector quantization. Neural Networks, 14, 505-525.
8. Cheeseman,P. and Stutz,J. (1995) Bayesian classification (Auto-Class): theory and results. In Fayyad,U., Piatesky-Shapiro,G., Smyth,P. and Uthurusamy,R. (eds), Advances in Knowledge Discovery and Data Mining. AAAI Press, Menllo Park, CA., pp. 153-180.
9. Cheng,G. and Zell,A. (2001) Externally growing cell structures for data evaluation of chemical gas sensors. Neural Computing and Applications, Vol. 10, Springer, New York, pp. 89-97.
10. Cheung,V.G., Morley,M., Aguilar,F., Massimi,A., Kucherlapati,R. and Childs,G. (1999) Making and reading microarrays. Nature Genet., supplement, 21.
11. Eisen,M.B., Spellman,P.T., Brown,P. and Botstein,D. (1998) Cluster analysis and display of genome-wide expression patterns. Proc. Natl Acad. Sci. USA, 95, 14863-14868.
12. Friedman,N., Linial,M., Nachman,I. and D' Pe'er, (2000) Using Bayesian networks to analyze expression data. J. Comput. Biol., 7, 601-620.
13. Fritzke,B. (1995) Growing grid - a self organizing network with constant neighborhood range and adaptation strength. Neural Process. Lett., 2, 9-13.
14. Gerstein,M. and Jansen,R. (2000) The current excitement in Bioinformatics - analysis of whole genome expression data: how does it relate to protein structure and function. Curr. Opin. Struct. Biol., 10, 574-584.
15. Hastie,T., Tibshirani,R., Botstein,D. and Brown,P. (2001) Supervised harvesting of expression trees. Genome Biol., 2, http://genomebiology.com/2001/2/I.
16. Haykin,S. (1999) Neural Networks. Prentice-Hall, Second Edition, Englewood Cliffs, NJ.
17. Herrero,J., Valencia,A. and Dopazo,J. (2001) A hierarchical unsupervised growing neural network for clustering gene expression patterns. Bioinformatics, 17, 126-136.
18. Hunter,L., Taylor,R.C., Leach,S.M. and Simon,R. (2001) GEST: a gene expression search tool based on a novel Bayesian similarity metric. Bioinformatics, 17, 115-122.
19. Kohonen,T. (1997) Self-Organized Maps, Second Edition, Springer, New York.
20. Papadimitriou,S., Mavroudi,S., Vladutu,L. and Bezerianos,A. (2001) Ischemia detection with a self organizing map supplemented by supervised learning. IEEE Trans. Neural Networks, 12, 503-515.
21. Sable,C.L. and Hatzivassiloglou,V. (1999) Text-based approaches for the categorization of images. In Proceedings of the Third Annual Conference on Research and Advanced Technology for Digital Libraries. Paris, pp. 19-38.
22. Si,J., Lin,S. and Vuong,M.A. (2000) Dynamic topology representing networks. Neural Networks, 13, 617-627.
23. Tamayo,P., Slonim,D., Mesirov,J., Zhu,Q., Kitareewan,S., Dmitrovsky,E., Lander,E.S. and Golub,T.R. (1999) Interpreting patterns of gene expression with self-organizing maps: methods and application to hematopoietic differentiation. Proc. Natl Acad. Sci. USA, USA, 2907-2912.
24. Troyanskaya,O., Cantor,M., Shelock,G., Brown,P., Hastie,T., Tibshirani,R., Botstein,D. and Altman,R.B. (2001) Missing value estimation methods for DNA microarrays. Bioinformatics, 17.
25. Vesanto,J. and Alhoniemi,E. (2000) Clustering of the self-organized map. IEEE Trans. Neural Networks, 11, 586-600.