【摘要】 基因芯片或称微阵列 (gene chip或 microarrays)是最近分子生物学实验技术的一个突破 ,利用该技术可以对成千上万个基因的表达进行平行分析 ,已经产生了总量巨大的有用数据 ,分析与整理这些数据成为利用这一技术的一个主要瓶颈问题。原始的微阵列数据是图像 ,必须把它们转化成为基因表达矩阵表 ,矩阵的行代表基因 ,列代表各样本及条件(如 :组织、实验条件、处理因素等 ) ,每个格子的数据表示特定的基因在特定的样本中的表达水平。这些矩阵必须经过进一步的分析才能得到它们潜在生物学过程的信息。本文着重讨论了生物信息学方法在该领域的应用 ,主要探讨了监督与非监督数据分析方法在基因表达数据分析中的应用 ,如预测基因功能分类及恶性肿瘤分级。本文还讨论了如何利用基因表达矩阵预测序列中假想调控信号。更多还原

【Abstract】 Microarrays are one of the latest breakthroughs in experimental molecular biology,which allow monitoring of gene expression for tens of thousands of tenes in parallel and are already producing huge amounts of valuable data.Analysis and handling of such data is becoming one of the major bottlenecks in thde utilization of the technology.The raw microarray data are images,which hava to be transformde into gene expression matrices tables where rowsrepresent gengs,columns represent various samples such as tissues or experimental conditions,and numbers in each cell characterize the expression level of the particular gene in the particular sample.These matrices have to be analyzed further,if any knowledge about the underlying biological processes is to be extracted.In this paper we concentrate on discussing bioinformatics methods used for such analysis.We briefly discuss supervised and unsupervised data analysis and its applications,such as predicting gene function classes and cancer classification.Then we discuss how the gene expression matrix can be used to predict putative regulatory signals in the genome sequences.In conclusion we discuss some possible future directions.更多还原