Tumor-specific gene expression patterns with gene expression profiles  

作　　者：RUAN Xiaogang LI Yingxin LI Jiangeng GONG Daoxiong WANG Jinlian 

机构地区：[1]School of Electronic Information and Control Engineering,Beijing University of Technology,Beijing 100022,China

出　　处：《Science China(Life Sciences)》2006年第3期293-304,共12页中国科学(生命科学英文版)

基　　金：supported in part by the National Natural Science Foundation of China(Grant No.60234020).

摘　　要：Gene expression profiles of 14 common tumors and their counterpart normal tissues were analyzed with machine learning methods to address the problem of selection of tumor-specific genes and analysis of their differential expressions in tumor tissues.First,a variation of the Relief algorithm,"RFE_Relief algorithm"was proposed to learn the relations between genes and tissue types.Then,a support vector machine was employed to find the gene subset with the best classification performance for distinguishing cancerous tissues and their counterparts.After tissue-specific genes were removed,cross validation experiments were employed to demonstrate the common deregulated expressions of the selected gene in tumor tissues.The results indicate the existence of a specific expression fingerprint of these genes that is shared in different tumor tissues,and the hallmarks of the expression patterns of these genes in cancerous tissues are summarized at the end of this paper.

关 键 词：CANCER informative gene selection gene expression profile support vector machine. 

分 类 号：N[自然科学总论]