DocumentCode
2142996
Title
Biological Pathway Conducting Microarray-Based Cancer Classification
Author
Zeng, Tao ; Luo, Fei ; Liu, Juan
Author_Institution
Sch. of Comput., Wuhan Univ., Wuhan, China
fYear
2009
fDate
17-19 Oct. 2009
Firstpage
1
Lastpage
5
Abstract
The cancer classification is a major and important study field in the medical research, and DNA microarrays have been proved to provide useful and great information for cancer classification at molecular level, compared with traditional clinical or histopathological information. Bio-markers from microarray gene expression analysis have developed to a new approach for cancer classification but still face the problems such as: different genetic signatures for same cancer under different methods; disregards of small but consistent changes in expression; and lack of biological systematic opinion. Here, this paper proposes biological pathway conducting cancer classification based on gene expression data with pathway information in KEGG. There are experiments on four different data-sets for breast, colon, gloimas and lymphoma cancer: the accuracy of these classifications are all promoted about 10%, and even achieve 100% in LOOCV on gloimas data;the pathway conducting classifiers show more significant biological functional features than genetic bio-markers.
Keywords
DNA; cancer; lab-on-a-chip; molecular biophysics; patient diagnosis; DNA microarrays; biological pathway conducting microarray; biomarkers; breast cancer; cancer classification; colon cancer; genetic signature; glioma cancer; histopathological information; lymphoma cancer; microarray gene expression analysis; Biology computing; Breast; Cancer; Colon; DNA computing; Data analysis; Gene expression; Genetics; Signal to noise ratio; Systematics;
fLanguage
English
Publisher
ieee
Conference_Titel
Biomedical Engineering and Informatics, 2009. BMEI '09. 2nd International Conference on
Conference_Location
Tianjin
Print_ISBN
978-1-4244-4132-7
Electronic_ISBN
978-1-4244-4134-1
Type
conf
DOI
10.1109/BMEI.2009.5303634
Filename
5303634
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