{"title":"基于SOM基因分析的弥漫性大b细胞淋巴瘤预后预测","authors":"M. Furukawa, Michiko Watanabe","doi":"10.1109/CIRA.2005.1554267","DOIUrl":null,"url":null,"abstract":"The cause of death is moving to the life-habit disease from the infectious disease in Japan. Since 1981, the cancer has occupied the first cause of Japanese death. Therefore, it is an urgent matter to tackle the cancer problem. Recently, it is understood that outcome of the cancer disease in a prognosis is related to the special combination of genes. However, it is very difficult to predict outcome of the cancer disease in a prognosis, because a huge number of genes exist and we have to explore the special combination of genes among them. This study aims at finding the special genes combination, which affects on the outcome of the cancer disease in a prognosis. Self-organizing maps (SOM) is applied to accomplish our aim. Namely, SOM is used to cluster genes to predict the outcome of the cancer disease in a prognosis. Some tools are also developed to analyze the SOM results, because it is insufficient for SOM only to specify the combination of genes, which affects on outcome of the cancer disease in a prognosis. Numerical experiments present some useful information on the outcome of the cancer disease in a prognosis.","PeriodicalId":162553,"journal":{"name":"2005 International Symposium on Computational Intelligence in Robotics and Automation","volume":"87 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Prediction of diffuse large B-cell lymphoma outcome based on genes' analysis by use of SOM\",\"authors\":\"M. Furukawa, Michiko Watanabe\",\"doi\":\"10.1109/CIRA.2005.1554267\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The cause of death is moving to the life-habit disease from the infectious disease in Japan. Since 1981, the cancer has occupied the first cause of Japanese death. Therefore, it is an urgent matter to tackle the cancer problem. Recently, it is understood that outcome of the cancer disease in a prognosis is related to the special combination of genes. However, it is very difficult to predict outcome of the cancer disease in a prognosis, because a huge number of genes exist and we have to explore the special combination of genes among them. This study aims at finding the special genes combination, which affects on the outcome of the cancer disease in a prognosis. Self-organizing maps (SOM) is applied to accomplish our aim. Namely, SOM is used to cluster genes to predict the outcome of the cancer disease in a prognosis. Some tools are also developed to analyze the SOM results, because it is insufficient for SOM only to specify the combination of genes, which affects on outcome of the cancer disease in a prognosis. Numerical experiments present some useful information on the outcome of the cancer disease in a prognosis.\",\"PeriodicalId\":162553,\"journal\":{\"name\":\"2005 International Symposium on Computational Intelligence in Robotics and Automation\",\"volume\":\"87 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2005-06-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2005 International Symposium on Computational Intelligence in Robotics and Automation\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CIRA.2005.1554267\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2005 International Symposium on Computational Intelligence in Robotics and Automation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CIRA.2005.1554267","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Prediction of diffuse large B-cell lymphoma outcome based on genes' analysis by use of SOM
The cause of death is moving to the life-habit disease from the infectious disease in Japan. Since 1981, the cancer has occupied the first cause of Japanese death. Therefore, it is an urgent matter to tackle the cancer problem. Recently, it is understood that outcome of the cancer disease in a prognosis is related to the special combination of genes. However, it is very difficult to predict outcome of the cancer disease in a prognosis, because a huge number of genes exist and we have to explore the special combination of genes among them. This study aims at finding the special genes combination, which affects on the outcome of the cancer disease in a prognosis. Self-organizing maps (SOM) is applied to accomplish our aim. Namely, SOM is used to cluster genes to predict the outcome of the cancer disease in a prognosis. Some tools are also developed to analyze the SOM results, because it is insufficient for SOM only to specify the combination of genes, which affects on outcome of the cancer disease in a prognosis. Numerical experiments present some useful information on the outcome of the cancer disease in a prognosis.