DocumentCode :
1974385
Title :
Classification of cancer gene expressions from micro-array analysis
Author :
Venkatesh, E.T. ; Tangaraj, P. ; Chitra, S.
Author_Institution :
Dept. of Comput. Technol., Kongu Eng. Coll., Erode, India
fYear :
2010
fDate :
12-13 Feb. 2010
Firstpage :
1
Lastpage :
5
Abstract :
The role of micro array expression data in cancer diagnosis is very significant. Mining for useful information from such micro array data consisting of thousands of genes and a small number of samples is often a tough task. Colon cancer is the second most common cause of cancer mortality in Western countries. According to the WHO 2006 report colorectal cancer causes 655,000 deaths worldwide per year. All the genes used in the expression profile are not informative; also many of them are redundant. Reducing the number of genes by feature selection and still retaining best class prediction accuracy for the classifier is vital in case of tumor classification. The emphasis in cancer classification is both on methods of gene selection and on choice of classifier. It is proposed to study various classification algorithms.
Keywords :
bioinformatics; cancer; data mining; medical computing; neural nets; pattern clustering; support vector machines; WHO; cancer gene expressions classification; cancer mortality; colon cancer; colorectal cancer; feature selection; gene selection; microarray analysis; tumor classification; Bioinformatics; Cancer; Colon; Data mining; Educational institutions; Gene expression; Neoplasms; RNA; Support vector machine classification; Support vector machines; DNA; RNA; Regression Analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Innovative Computing Technologies (ICICT), 2010 International Conference on
Conference_Location :
Tamil Nadu
Print_ISBN :
978-1-4244-6488-3
Type :
conf
DOI :
10.1109/ICINNOVCT.2010.5440095
Filename :
5440095
Link To Document :
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