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基因组生物医学研究中的当前生物信息学工具(综述)。

Current bioinformatics tools in genomic biomedical research (Review).

作者信息

Teufel Andreas, Krupp Markus, Weinmann Arndt, Galle Peter R

机构信息

Department of Medicine I, Johannes Gutenberg University, Mainz, Germany.

出版信息

Int J Mol Med. 2006 Jun;17(6):967-73.

Abstract

On the advent of a completely assembled human genome, modern biology and molecular medicine stepped into an era of increasingly rich sequence database information and high-throughput genomic analysis. However, as sequence entries in the major genomic databases currently rise exponentially, the gap between available, deposited sequence data and analysis by means of conventional molecular biology is rapidly widening, making new approaches of high-throughput genomic analysis necessary. At present, the only effective way to keep abreast of the dramatic increase in sequence and related information is to apply biocomputational approaches. Thus, over recent years, the field of bioinformatics has rapidly developed into an essential aid for genomic data analysis and powerful bioinformatics tools have been developed, many of them publicly available through the World Wide Web. In this review, we summarize and describe the basic bioinformatics tools for genomic research such as: genomic databases, genome browsers, tools for sequence alignment, single nucleotide polymorphism (SNP) databases, tools for ab initio gene prediction, expression databases, and algorithms for promoter prediction.

摘要

随着完整人类基因组的问世,现代生物学和分子医学步入了一个序列数据库信息日益丰富且高通量基因组分析的时代。然而,由于目前主要基因组数据库中的序列条目呈指数级增长,可用的已存储序列数据与通过传统分子生物学进行分析之间的差距正在迅速扩大,这使得高通量基因组分析的新方法成为必要。目前,跟上序列及相关信息急剧增长的唯一有效方法是应用生物计算方法。因此,近年来,生物信息学领域迅速发展成为基因组数据分析的重要辅助手段,并且已经开发出了强大的生物信息学工具,其中许多工具可通过万维网公开获取。在本综述中,我们总结并描述了用于基因组研究的基本生物信息学工具,例如:基因组数据库、基因组浏览器、序列比对工具、单核苷酸多态性(SNP)数据库、从头预测基因工具、表达数据库以及启动子预测算法。

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