常用于基因表达数据分析的聚类方法有很多。
There are lots of cluster methods applied to the analysis of gene expression data.
现在已有不少的算法开始应用于基因表达数据分析，而且不断有新的算法提出。
There are many clustering algorithms have been applied to gene expression data now, and new algorithms are proposed continuously.
随着DNA芯片技术的广泛应用，基因表达数据分析已成为生命科学的研究热点。
Along with the research and extensive application of DNA chip technology, gene expression data analysis have become a hotspot in life science field.
特定条件下的差异表达基因筛选是科学家使用芯片的初衷，也是芯片数据分析中很重要的一种应用。
The essential and initial problem of gene expression microarray data analysis is to identify differentially expressed genes (DEGs), under certain conditions.
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.
虽然其他两个基因周围没有发现雄性不育的基因，但是表达数据分析表明，在这些基因周围有与雄性发育有关的基因，这些基因可以作为候选基因。
The expression data analysis showed that there were some male or flower development related genes around them. These genes could be candidate genes for further biological experiments.
老鼠胚胎发育解剖数据分析数据光盘，包括部分老鼠基因表达数据库内容。
The models can be used in conjunction with the software to browse the 3D structures, identify anatomy components, and prepare data for inclusion in the?database of gene expression.
老鼠胚胎发育解剖数据分析数据光盘，包括部分老鼠基因表达数据库内容。
The models can be used in conjunction with the software to browse the 3D structures, identify anatomy components, and prepare data for inclusion in the?database of gene expression.
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