在基因表达谱数据获取过程中，基因表达谱数据含有较大的实验误差。
There is some obvious inaccuracy of gene expression in the experiment to obtain the gene expression data.
基因表达谱数据的聚类分析对于研究基因功能和基因调控机制有重要意义。
The cluster analysis of gene expression data is an important means for discovering gene functions and regular to mechanisms.
基因表达谱数据的聚类分析对于研究基因功能和基因调控机制有重要意义。
The cluster analysis of gene expression data is an important means for discovering gene functions and regulatory mechanisms.
通过分析酵母细胞的大规模基因表达谱数据，获得不同基因间表达的相关性。
Through seriate genome-wide mRNA expression data, similarity between two genes could be measured.
利用基因表达谱数据，通过计算互作蛋白质的表达相关系数，来筛选、优化蛋白质互作网络。
Correlation coefficient of gene expression profiles for each pair of interaction proteins is calculated to filter the protein interaction network.
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.
阵列数据目前可从三个传统和两个遗传工程大豆品种的一个实验全局基因表达谱中获得。
Array data is presently available from an experiment profiling global gene expression of three conventional and two genetically engineered soybean cultivars.
在大规模基因表达谱的数据分析中引入了一种全新的基于贝叶斯模型的聚类算法。
A novel clustering algorithm based on Bayesian model was introduced into the analysis of large-scale gene expression profiles.
利用ICA对基因微阵列表达谱数据进行分解获得由基因模型谱和对应系数构成的线性谱模型，并在此基础上进行基因分类。
The gene linear profile model, composed of model profiles and coefficients, is obtained by ica from gene expression data, so gene classification based on ica is presented.
利用ICA对基因微阵列表达谱数据进行分解获得由基因模型谱和对应系数构成的线性谱模型，并在此基础上进行基因分类。
The gene linear profile model, composed of model profiles and coefficients, is obtained by ica from gene expression data, so gene classification based on ica is presented.
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