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Ikeda Nobuhiko


Classification of cancer cell using protein information by SOM

大島商船高等専門学校紀要 Volume 41 Page 9-19
published_at 2008-12
OS10041000002.pdf
[fulltext] 2.04 MB
Title
SOMによる蛋白質情報を用いた癌細胞の分類手法
Classification of cancer cell using protein information by SOM
Creators Kitakaze Hironori
Creators Matsuoka Hidemi
Creators Ikeda Nobuhiko
Creators Matsuno Hiroshi
Source Identifiers
Creator Keywords
cancer cells LSC amount of protein cohesiveness of protein SOM classification
The analysis of cancer cells at the level has been studied. However, it was difficult to clarify the characteristics of cancer cells such as the speed of becoming worse, the efficiency of the medicine on the cell level. Recently, Laser Scanning Cytometer(LSC) which measures the data of cancer cells has been developed. Dr.Furuya et al. tried to analyze the characteristics of cancer cells using to the amount and the cohesiveness of protein. However, they could not find the efficient method for lassification of cancer cells. In the paper, we try to classify cancer cells using the amount and the cohesiveness of protein by Self-Organizing Map (SOM). The data used in the classification is the image data created from the amount and the cohesiveness of protein of cancer cell extracted from the patient by LSC. The result shows the probability that SOM would be able to classify cancer cells by those protein information.
Languages jpn
Resource Type departmental bulletin paper
Publishers 大島商船高等専門学校
Date Issued 2008-12
File Version Version of Record
Access Rights open access
Relations
[ISSN]0387-9232
[NCID]AN00031668