Other gene sets are responsible for additional tissues.
而其它的基因负责向其它的组织分化。
Instead, each allele of the gene sets out a series of probabilities.
此基因的等位基因有这一系列的可能性。
Secondly, using statistical significance analysis, we find out significant gene sets with respect to each microarray dataset;
然后用统计学方法找出在每组数据对应的生命过程中有显著意义的基因集；
The 13 gene sets associated with "apples and pears" only account for about one percent of the variety in waist-to-hip ratios among the population.
在所有人口中，决定“苹果型和梨形身材”的13组基因在人们腰围和臀围比例中只占百分之一。
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.
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。
In this book he explores a range of fascinating topics - like gene networks, auto-catalytic sets, rugged landscapes.
在这本书中，他讲述了一系列令人着迷的主题，像基因网络，自催化套和崎岖的景观等等。
Brualdi points out that large data sets, such as those generated by gene sequencing, medical imaging, or weather monitoring, often yield matrices with regular structures.
Brualdi指出，庞大的数据集，如通过基因测序，医疗成像或天气监测生成的那些，往往会产生常规结构的矩阵。
The search results are commonly adopted for various functional and comparative genomics tasks such as annotating unknown sequences, investigating gene models and comparing two sequence sets.
搜索结果通常被用于各种功能基因组学和比较基因组学任务，例如注释未知序列，研究基因模型和比较两个序列集合。
Similarly, in publicly available breast cancer gene expression data sets, overexpression of SF3B3, but not SF3B1, was significantly correlated with overall survival.
同样，在公开的乳腺癌基因表达数据库中，SF3B 3过表达与总生存率显著相关，SF 3b1则无此作用。
This method does not rely on gene sequence or protein structure homologies, and it can be applied to any organism and a wide variety of experimental data sets.
这个方法不依赖于基因的序列或者是蛋白的同源结构，它能够适用于任何的生物体和大量的实验数据集。
Expression levels of SF3B1 and SF3B3 and their prognostic value were validated in large cohorts using publicly available gene expression data sets including The Cancer Genome Atlas.
对SF3B1和SF3B3表达水平及其预后价值使用包括癌症基因数据库在内的公开可用的基因表达数据库进行了大样本验证。
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。
Using the processed data we will discuss the basis for clustering genes into sets and discovering gene set features that can be used for diagnostic purposes.
通过使用获得的资料，我们将讨论给凝块基因分组的基础并且探索用于诊断性的目的基因层组特色。
Using the processed data we will discuss the basis for clustering genes into sets and discovering gene set features that can be used for diagnostic purposes.
通过使用获得的资料，我们将讨论给凝块基因分组的基础并且探索用于诊断性的目的基因层组特色。
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