Computer Engineering and Applications ›› 2010, Vol. 46 ›› Issue (25): 211-213.DOI: 10.3778/j.issn.1002-8331.2010.25.061

• 工程与应用 • Previous Articles     Next Articles

Detection to singularity spot of cancer gene expression signals based on wavelet analysis

CHEN Jun,WU Ya-zhou,YI Dong   

  1. Department of Medical Statistics,Third Military Medical University,Chongqing 400038,China
  • Received:2009-04-07 Revised:2009-06-10 Online:2010-09-01 Published:2010-09-01
  • Contact: CHEN Jun

基于小波分析的肿瘤基因表达信号突变点检测

陈 军,伍亚舟,易 东   

  1. 第三军医大学 卫生统计教研室,重庆 400038
  • 通讯作者: 陈 军

Abstract: To detect singularity spot of gene expression signals of cancer cell organization,the doubtful break gene can be analyzed and a reference to medicinal diagnoses is given.After getting rid of high frequency of original gene expression signals,singularity gene spot of each experiment cell is detected via giving wavelet analysis to low frequency,combining the principium of module maximum.Wavelet analysis can detect the singularity component of signals expediently and effectively.It is effective in detecting and analyzing expression signals of cancer cell.The conclusion has significance to medicinal reference.

Key words: gene expression, wavelet analysis, singularity spot, module maximum

摘要:

对某肿瘤组织细胞基因表达信号进行突变点检测,分析可疑突变基因,为医学诊断提供参考。先去除原始基因表达信号的高频部分,再对低频进行小波分析,结合模极大值原理检测出各试验细胞所对应的突变基因点。小波变换能方便而有效地检测出信号的突变成分,它在对肿瘤基因表达信号奇异点进行检测和分析方面是有效的,结论具有一定的医学参考意义。

关键词: 基因表达, 小波分析, 突变点, 模极大值

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