基于肿瘤基因表达谱研究了肿瘤相关基因及其功能模块的聚类算法，同时利用模块度评价了算法的有效性。
Second, the modularity function which was used to assess the performance of clustering algorithm was applied to the colon cancer gene modules.
另外，他们还观察那些有着肿瘤特异性变化的基因表达谱以及被拷贝基因的数量。
This comprehensive analysis led to the discovery of a variety of genes that were not known to be altered in GBMs.
尽管目前已经有很多工作利用基因表达谱数据以及一些其他的先验知识来寻找那些与肿瘤相关的基因集合，但还是没有一个恰当的基因集合的统计学方法。
Although there has been much work focused on searching gene sets using gene expression data or other prior information, proper statistical testing of the gene sets is still an open question.
基于基因表达谱建立具有有效预测性的肿瘤分类模型对肿瘤的临床诊断与治疗具有非常重要的意义。
Building an effective classification model based on gene expression profiles is of great importance in tumor diagnosing and its clinical therapy.
基于基因表达谱建立具有有效预测性的肿瘤分类模型对肿瘤的临床诊断与治疗具有非常重要的意义。
Building an effective classification model based on gene expression profiles is of great importance in tumor diagnosing and its clinical therapy.
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