Recently, many algorithms have also been introduced in this field to determine gene regulatory networks based on such high-throughput microarray data.
近年来， 人们引入了多种算法来利用基因芯片数据构建基因调控网络。
Missing values contained in microarray data will affect subsequent analysis.
微阵列数据中的缺失值会对随后的数据分析造成影响。
Objective To search an effective method on screening significant genes based on microarray data.
目的基于微阵列表达数据，探索筛选差异表达基因的有效方法。
Several classification methods based on DNA gene expression microarray data are introduced in this paper.
介绍了目前几种基于DNA微阵列基因表达数据的分类方法。
The importance of microarray data analysis lies in presenting functional annotations and classifications.
微阵列数据分析的重要性在于展示功能注释和分类。
Given a microarray data set, articulate all the sources of error in measurement and find them in the particular data set.
给出一个微阵列的数据组，标示出测定中的错误的所有来源，并在特定资料组中找出它们。
The new clustering algorithm is analyzed on several aspects and tested on the published yeast cell-cycle microarray data.
从多方面分析了该算法的性能，并将该算法应用于酵母细胞周期的芯片表达谱数据聚类。
In clinical bioinformatics, selecting appropriate software to analyze the microarray data for medical decision making is crucial.
在临床生物信息学中，选择适当的软件分析芯片数据制定医学决策是至关重要的。
We try to explore the method for explaining the mechanism of Cold - and Hot - ZHENG based on statistical analysis of microarray data.
本文尝试利用大规模基因芯片数据分析对中医寒热证机理进行了初步探索。
These steps are described here and placed in the context of commercial and public tools available for the analysis of microarray data.
这里描述了这些步骤，并将它们置于商用和公共可用的微阵列数据分析环境中。
In addition, an analysis object provides methods for data processing, and an image object enables the visualisation of microarray data.
此外，一个分析对象提供了用于数据处理的方法，及一个图形对象使得能够进行微阵列数据的可视化。
BACKGROUND: When processing microarray data sets, we recently noticed that some gene names were being changed inadvertently to non-gene names.
背景：当处理微阵列数据集时，我们最近注意到一些基因名字正在被不经意地转变为非基因名字。
Gene selection is a very important problem in microarray data analysis and has critical implications for the discovery of genes related to serious diseases.
基因选择是基因芯片数据分析中的一个重要问题。
The essential and initial problem of gene expression microarray data analysis is to identify differentially expressed genes (DEGs), under certain conditions.
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 adoption of common standards and ontologies for the management and sharing of microarray data is essential and will provide immediate benefit to the research community.
用于管理和分享微阵列数据的通用标准和本体论的采用是必要的，并将对研究社区提供直接的益处。
CONCLUSIONS: MAGE will help microarray data producers and users to exchange information by providing a common platform for data exchange, and MAGE-STK will make the adoption of MAGE easier.
结论：通过提供数据交换的一种常见平台，MAGE将帮助微阵列数据产生者和用户交换信息，并且MAGE - STK将使得MAGE的采用变得更加容易。
Microarray data in different tissues showed that it has significant expression signals in head and epidermis of day-3 5th instar larvae, which was verified by RT-PCR.
基因芯片数据显示在家蚕5龄第3天的头部和体壁组织中的表达量较高，RT - PCR验证结果与此一致。
Microarray data in different tissues showed that it has significant expression signals in head and epidermis of day-3 5th instar larvae, which was verified by RT-PCR.
基因芯片数据显示在家蚕5龄第3天的头部和体壁组织中的表达量较高，RT - PCR验证结果与此一致。
应用推荐