A hybrid SOM-SVM method for analyzing zebra fish gene expression

Proceedings - International Conference on Pattern Recognition

Volumn 2, Issue , 2004, Pages 323-326

  Wu, Wei ^a   Xin, Liu ^a   Min, Xu ^a   Jinrong, Peng ^a   Setiono, Rudy ^a  

^a NATIONAL UNIVERSITY OF SINGAPORE   (Singapore)

Author keywords

[No Author keywords available]

Indexed keywords

EXPRESSION SEQUENCE TAG (EST); SELF-ORGANIZING MAPS (SOM); SUPPORT VECTOR MACHINE (SVM); ZEBRA FISH GENES;

ALGORITHMS; DATA ACQUISITION; DNA; ENZYMES; GENES; MATRIX ALGEBRA; METABOLISM; PROTEINS;

IMAGE ANALYSIS;

EID: 10044276804     PISSN: 10514651     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICPR.2004.1334191     Document Type: Conference Paper

References (6)

1. Brown, M.P.S. et al. (2000). Knowledge-based Analysis of Microarray Gene Expression Data by Using Support Vector Machines. PNAS, 97, 262-267.
2. Datta, S. et al. (2003). Comparisons and Validation of Statistical Clustering Techniques for Microarray Gene Expression Data. Bioinformatics, 19:4, 459-466.
3. Furey, T. S. et al. (2000). Support Vector Machine Classification and Validation of Cancer Tissue Samples Using Microarray Expression Data, Bioinformatics, 16, 906-914.
4. Kohonen, T. (1997). Self-Organizing Maps, Springer, Berlin.
5. Lo, J. et al. (2003). 15,000 Unique Zebrafish EST Clusters and Their Use in Microarray for Profiling Gene Expression Patterns During Embryogenesis. Genome Research, 13, 455-466.
6. Tamayo, P. et al. (1999). Interpreting Patterns of Gene Expression with Self-organizing Maps: Methods and Application to Hematopoietic Differentiation, PNAS, 96, 2907-12.