DocumentCode :
2564589
Title :
Statistical neural networks and support vector machine for the classification of genetic mutations in ovarian cancer
Author :
Sehga, Muhammad Shoaib B ; Gondal, Iqbal ; Dooley, Laurence
Author_Institution :
Gippsland Sch. of Comput. & Inf. Technol., Monash Univ., Clayton, Vic., Australia
fYear :
2004
fDate :
7-8 Oct. 2004
Firstpage :
140
Lastpage :
146
Abstract :
An optimal genetic mutation diagnosis requires proper selection of mutation classifier. This work investigates the performance of different classification, missing value estimation (MVE) and data dimension reduction techniques for the classification of gene expression data for BRCA1, BRCA2 and Sporadic mutations of epithelial ovarian cancer. Bayesian MVE and zero imputation techniques were employed to deal with missing values. Our study showed the better performance of the Bayesian technique. A novel approach is introduced to use generalized regression neural network (GRNN) as genetic mutation classifier which completely outperformed both well established support vector machine and probabilistic neural network.
Keywords :
belief networks; biology computing; cancer; generalisation (artificial intelligence); genetics; neural nets; pattern classification; support vector machines; BRCA1; BRCA2; Bayesian missing value estimation; Sporadic mutation; data dimension reduction technique; epithelial ovarian cancer; gene expression data; generalized regression neural network; genetic mutation classification; probabilistic neural network; statistical neural network; support vector machine; zero imputation technique; Bayesian methods; Cancer; Diseases; Gene expression; Genetic mutations; History; Intelligent networks; Neural networks; Support vector machine classification; Support vector machines;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence in Bioinformatics and Computational Biology, 2004. CIBCB '04. Proceedings of the 2004 IEEE Symposium on
Print_ISBN :
0-7803-8728-7
Type :
conf
DOI :
10.1109/CIBCB.2004.1393946
Filename :
1393946
Link To Document :
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