SOMによる蛋白質情報を用いた癌細胞の分類手法

概要

論文の詳細を見る
The analysis of cancer cells at the level has been studied. However, it was difficult to clarifythe characteristics of cancer cells such as the speed of becoming worse, the efficiency of themedicine on the cell level. Recently, Laser Scanning Cytometer(LSC) which measures the dataof cancer cells has been developed. Dr.Furuya et al. tried to analyze the characteristics ofcancer cells using to the amount and the cohesiveness of protein. However, they could not findthe efficient method for classification of cancer cells.In the paper, we try to classify cancer cells using the amount and the cohesiveness of proteinby Self-Organizing Map (SOM). The data used in the classification is the image data createdfrom the amount and the cohesiveness of protein of cancer cell extracted from the patient byLSC. The result shows the probability that SOM would be able to classify cancer cells by thoseprotein information.
大島商船高等専門学校の論文
2008-12-01