DocumentCode :
3061072
Title :
Normalized Linear Transform for Cross-Platform Microarray Data Integration
Author :
Xiong, Huilin ; Zhang, Ya ; Chen, Xue-wen
Author_Institution :
Shanghai Jiao Tong Univ., Shanghai
fYear :
2007
fDate :
13-15 Dec. 2007
Firstpage :
612
Lastpage :
617
Abstract :
With microarray data being dramatically accumulated, integrating data from related studies represents a natural way to increase sample size so that more reliable statistical analysis may be performed. However, inherent variation among different microarray platforms makes the data integration not a trivial task. In this paper, we present a simple and effective integration scheme, called normalized linear transform (NLT), to combine data from different microarray platforms. The NLT scheme is compared with three other integration schemes for two tasks: classification analysis and gene marker selection. Our experiments demonstrate that the NLT scheme performs best in terms of classification accuracy under various classification settings, and leads to more biologically significant marker genes.
Keywords :
biology computing; data analysis; pattern classification; classification analysis; cross-platform microarray data integration; gene marker selection; integration scheme; microarray platforms; normalized linear transform; reliable statistical analysis; Application software; Computer science; Costs; Gene expression; Image processing; Machine learning; Pattern recognition; Statistical analysis; Support vector machine classification; Support vector machines;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Applications, 2007. ICMLA 2007. Sixth International Conference on
Conference_Location :
Cincinnati, OH
Print_ISBN :
978-0-7695-3069-7
Type :
conf
DOI :
10.1109/ICMLA.2007.65
Filename :
4457297
Link To Document :
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