microarray data中文是什么意思

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中文翻译
造句

[网络] 微阵列资料；用微阵列资料；基因芯片数据

microarray 微列; 微阵列
cdna microarray 微阵列
dna microarray dna微阵列; dna芯片; 基因微阵列晶片; 基因芯片; 生物晶片
liver2k microarray 肝基因微阵列晶片
microarray analysis 微阵列分析
microarray chip 微阵列晶片; 微阵列芯片
microarray technology 微阵技术; 微阵列技术
oligonucleotide microarray 微阵列
tissue microarray 组织微阵列
clustering analysis of microarray 表达谱的聚类分析
genome; gene chi(dna microarray) 基因图谱
data n. 1.资料，材料〔此词系 datum 的复数。但 datum 罕用，一般即以 data 作为集合词，在口语中往往用单数动词；如系指一件资料，则说作 this data〕。 2.〔美国〕(观察所得的)事实，知识。 a data book 参考资料书。 gather data on ...收集…的资料[数据]。 The data is not enough to be convincing. 资料不足，尚难令人信服。
data in 输入数据; 数据输入
data-in 记入数据; 输入数据; 输入诸元; 数据输入
for data 循环数据
no data 无数据
on data 昂达
the data 枣椰树
binary data data 二进制数据
data base data model 数据库数据模型
data base data name 数据库数据名
data- data negative 负线(自诊)
data-high rate data 高速率数据
data-medium rate data 中速率数据
microarray test 《英汉医学词典》microarray test ; 微阵列测试剂
microarray assays,protein 《英文msh词典》Microarray Assays,Protein ; [入口词] Microarray Assays,Protein ; [主题词] Protein Array Analysis ; [英文释义] Ligand-binding assays that measure protein-protein,protein-small molecule or protein-nucleic acid interactions using a very large set of capturing molecules,i.e.,those attached separately on the solid support,to measure the presence or interaction of target molecules in the sample.

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例句与用法

In this thesis, ai applications are developed and used to analyze biological sequence and microarray data, with the following points of innovation that can be summed up : 1
本文主要在算法创新和计算智能技术在生物信息学上的实际应用两方面做了以下工作：1
We validated the model with data from an independent cohort of 60 patients with nsclc and with a set of published microarray data from 86 patients with nsclc
我们已用一个独立队列研究（包含60位非小细胞肺癌患者）得到的数据和一组来自86位非小细胞肺癌患者的已发表的微点阵数据验证了这个模型。
A general genetic model for microarray data is developed, which includes effects of gene, array, dye, treatment and interaction of gene array, gene dye, and gene treatment
提出了分析芯片数据的一般模型，其中包括了基因、阵列效应、染料、处理效应以及基因阵列、基因染料、基因处理互作效应。
Therefore, instead of the traditional biomedicine methods, the partial independent component analysis ( pica ) is proposed in this paper to do the partial volume correction for getting the pure microarray data
因此，本文提出用部分独立分量分析方法代替传统的生物医学方法进行基因的部分体积修正从而获得真正感兴趣的微阵列数据。
But, because of the partial volume effect of the organism, directly processing of the gene microarray data will make that the characters extracted are not those of the biology genes, which will reduce the measurement sensitivity of the gene features
但是，机体组织所具有的部分体积效应，使得对基因微阵列数据的直接处理将造成所提取特征不是真正的生物基因特征本身，严重降低基因特征测量的灵敏度和指向性。
For real dna microarray data with 2308 genes and only 64 labeled samples belonging to 4 disease classes, only 6 genes are selected to be diagnostic genes; with 7129 genes and only 72 labeled samples belonging to 2 disease classes, only 11 genes are selected
经过对真实的基因微阵列数据进行大量实验，从2308个基因中找出了6个基因即可以诊断对应的4种疾病，从7129个基因中找出了11个基因即可以诊断对应的2种疾病。
Some open testing datasets and real gene microarray data are applied in experiments . the results have verified the feasibility and validity of the pica to get the gene microarray data and the advanced boosting algorithm for gene classification
经过对公开的测试数据集和真实的基因微阵列数据大量实验，证明了用部分独立分量分析方法获取基因微阵列数据及boosting改进算法进行基因模式分类的可行性和有效性，最终也完成了基因模式的识别任务。
Some open testing datasets and real gene microarray data are applied in experiments . the results have verified the feasibility and validity of the pica to get the gene microarray data and the advanced boosting algorithm for gene classification
经过对公开的测试数据集和真实的基因微阵列数据大量实验，证明了用部分独立分量分析方法获取基因微阵列数据及boosting改进算法进行基因模式分类的可行性和有效性，最终也完成了基因模式的识别任务。
In this paper, our method was performed in two separate steps . first, microarray data was normalized to eliminate experiment-wide systematic effects and then differentially expressed genes were prejudged under a loose standard via a single gene model . second, these differentially expressed genes were confirmed under a stricter standard to control the false positive via a multi-gene model
本文提出的方法主要分为两步来进行：首先，将芯片数据通过噪音过滤消除大的试验系统误差，然后在一个比较宽松的标准下通过单基因模型初步判断差异表达基因；其次，用多基因模型分析这些初定的差异表达基因以便在较严的标准下控制假阳性。
Fuzzy correlation coefficient and three other existed methods ( pearson, spearman and information entropy correlation coefficient ) were used to analyze three microarray data sets which were about human gene expression during the development of cns in embryonic period . to accomplish the construction of gene expression regulatory network, a program was completed with matlab package
利用matlab工作平台，进行程序设计，研制一种新的构建基因表达调控网络的软件，并将已有的三种相关系数和模糊相关系数应用到人类胚胎期中枢神经系统发育过程基因表达数据中，建立调控网络，并对结果进行分析和比较。