【作者】 黄涛；

【导师】 周艳红；

【作者基本信息】 华中科技大学 ， 生物信息技术， 2007， 硕士

【摘要】 DNA微阵列技术的发展使得从基因组水平研究基因表达成为了可能,将该技术应用于细胞周期实验中,得到了一系列基因表达数据,从而进行基因的表达分析。对于基因的研究发现,某些基因的表达在细胞周期过程中呈现出一种明显的周期性,而这种周期性的表达与细胞周期的调控有着重要的联系,通过对这些基因的分析可以了解基因的调控机制。因此,如何识别这些周期表达基因成为了当前研究的热点。目前,已经有很多方法被用来分析基因表达谱数据,从而识别周期表达基因。然而这些方法都局限于基于特定周期函数的数学模型,因此不能从本质上描述基因的表达模式。为了解决这个问题,本文不使用特定的周期函数建立模型,而是将表达谱时序数据中基因在两个连续细胞周期内表达的相似性作为主要特征识别周期表达基因,采用线性回归分析中相关系数的方法计算。考虑到利用相关系数识别的误判,引入由方差衡量的波动性特征辅助筛选,最终得到周期表达基因的集合。本文选用了广泛使用的三个酵母基因表达谱数据集,通过对这三个数据集的分析识别周期表达基因,总共得到了989个潜在的周期表达基因,其中有95个已知周期表达基因,预测精度达到84%。更多还原

【Abstract】 The development of DNA microarray technology makes it possible to study the mechanism of gene expression on a genome-wide scale. The technology is used in cell cycle experiments to get gene expression data sets for gene expression analysis. The studies find that many genes show significantly periodical expression during the cell cycles, and these genes play important roles in the cell cycle regulation. According to the analysis of periodical genes, the mechanism of gene regulation can be realized. As a result, how to identify the periodically expressed genes becomes a challenge.Recently, many methods have been developed to identify periodically expressed genes based on expression profile data sets. Almost all the methods use a model based on some kinds of periodical functions, so these methods can not describe the expression patterns of genes essentially. This paper does not use a periodical function, but compares the similarity of time-course expression data sets in two continuous cell cycles. The similarity is measured by the correlation coefficient in linear regression analysis, and it is defined as the major feature to identify periodically expressed genes. Considering the misjudgment of correlation coefficient, this paper introduces the fluctuation feature measured by variance to help identifying periodically expressed genes.Three time-course expression data sets are used to identify the periodically expressed genes. As a result, 989 genes are identified to be potential periodically expressed genes, including 95 genes which are known to be periodically expressed genes, and the accuracy reaches 84%.更多还原