{"title":"从大规模数据库中通过肿瘤原发-继发比较挖掘转移相关基因","authors":"Sangwoo Kim, Doheon Lee","doi":"10.1145/1458449.1458458","DOIUrl":null,"url":null,"abstract":"Metastasis is the most dangerous step in cancer progression and causes more than 90% of cancer death. Although many researchers have been working on biological features and characteristics of metastasis, most of its genetic level processes remain uncertain. Some studies succeeded in elucidating metastasis related genes and pathways, followed by predicting prognosis of cancer patients, but there still is a question whether the result genes or pathways contain enough information and noise features have been controlled appropriately. To address these problems, we conducted comparisons between primary tumors and secondary metastatic tumors. Noises from the differences of tissue specific characteristics between two types of tumors have been controlled by additional analyses. In this paper, we suggest a new method for identifying genes and pathways which secure metastasis dependency and are free of metastasis independent features.","PeriodicalId":143937,"journal":{"name":"Data and Text Mining in Bioinformatics","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2008-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Mining metastasis related genes by primary-secondary tumor comparisons from large-scale database\",\"authors\":\"Sangwoo Kim, Doheon Lee\",\"doi\":\"10.1145/1458449.1458458\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Metastasis is the most dangerous step in cancer progression and causes more than 90% of cancer death. Although many researchers have been working on biological features and characteristics of metastasis, most of its genetic level processes remain uncertain. Some studies succeeded in elucidating metastasis related genes and pathways, followed by predicting prognosis of cancer patients, but there still is a question whether the result genes or pathways contain enough information and noise features have been controlled appropriately. To address these problems, we conducted comparisons between primary tumors and secondary metastatic tumors. Noises from the differences of tissue specific characteristics between two types of tumors have been controlled by additional analyses. In this paper, we suggest a new method for identifying genes and pathways which secure metastasis dependency and are free of metastasis independent features.\",\"PeriodicalId\":143937,\"journal\":{\"name\":\"Data and Text Mining in Bioinformatics\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-10-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Data and Text Mining in Bioinformatics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/1458449.1458458\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Data and Text Mining in Bioinformatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/1458449.1458458","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Mining metastasis related genes by primary-secondary tumor comparisons from large-scale database
Metastasis is the most dangerous step in cancer progression and causes more than 90% of cancer death. Although many researchers have been working on biological features and characteristics of metastasis, most of its genetic level processes remain uncertain. Some studies succeeded in elucidating metastasis related genes and pathways, followed by predicting prognosis of cancer patients, but there still is a question whether the result genes or pathways contain enough information and noise features have been controlled appropriately. To address these problems, we conducted comparisons between primary tumors and secondary metastatic tumors. Noises from the differences of tissue specific characteristics between two types of tumors have been controlled by additional analyses. In this paper, we suggest a new method for identifying genes and pathways which secure metastasis dependency and are free of metastasis independent features.