Visualization of transitions of developing of hepatitis C virus-associated hepatocellular carcinoma

Author

Miyamoto, Takanobu ; Fujita, Yusuke ; Uchimura, Shunji ; Hamamoto, Yoshihiko ; Iizuka, Norio ; Oka, Masaaki

Author_Institution

Yamaguchi Univ., Yamaguchi

fYear

2008

fDate

8-11 Dec. 2008

Firstpage

1

Lastpage

4

Abstract

In our previous study, we visualized microarray data of hepatocellular carcinoma (HCC) by using self-organizing-map, and investigated molecular signature representing the development of HCC. In this study, we propose two visualization methods of microarray data with Euclidean distance classifiers and Sammonpsilas nonlinear mapping. Our proposed methods will serve as tool to discover molecular signature representing the development of HCC for molecular biologists or doctors.

Keywords

cellular arrays; cellular biophysics; data visualisation; medical computing; molecular biophysics; Euclidean distance classifiers; Sammon nonlinear mapping; hepatitis C virus-associated hepatocellular carcinoma; molecular biologists; molecular signature; self-organizing-map; transitions visualization; visualized microarray data; Artificial neural networks; Data visualization; Euclidean distance; Filtering; Liver diseases; Medical treatment; Oncological surgery; Support vector machine classification; Support vector machines; Testing;

fLanguage

English

Publisher

ieee

Conference_Titel

Pattern Recognition, 2008. ICPR 2008. 19th International Conference on

Conference_Location

Tampa, FL

ISSN

1051-4651

Print_ISBN

978-1-4244-2174-9

Electronic_ISBN

1051-4651

Type

conf

DOI

10.1109/ICPR.2008.4761751

Filename

4761751