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GC-Profile:一个用于可视化和分析基因组序列中GC含量变化的基于网络的工具。

GC-Profile: a web-based tool for visualizing and analyzing the variation of GC content in genomic sequences.

作者信息

Gao Feng, Zhang Chun-Ting

机构信息

Department of Physics, Tianjin University, Tianjin 300072, China.

出版信息

Nucleic Acids Res. 2006 Jul 1;34(Web Server issue):W686-91. doi: 10.1093/nar/gkl040.

Abstract

In order to understand the evolution, structure and function of genomes, it is important to know the general compositional features of DNA sequences. Based on the quadratic divergence, a new segmentation algorithm to partition a given genome or DNA sequence into compositionally distinct domains has been put forward. With the aid of the technique of cumulative GC profile, the distribution of segmentation points can be displayed intuitively. We have therefore developed them into GC-Profile, an interactive web-based software system, which can be used to segment prokaryotic and eukaryotic genomes. GC-Profile provides a quantitative and qualitative view of genome organization. Based on the obtained results, the relationships between the G+C content and other genomic features, such as distributions of genes and CpG islands, can be analyzed in a perceivable manner. It shows that GC-Profile would be an appropriate starting point for analyzing the isochore structure of higher eukaryotic genomes, and an intuitive tool for identifying genomic islands in prokaryotic genomes. GC-Profile is freely available at the website http://tubic.tju.edu.cn/GC-Profile/. In addition, precompiled binaries, together with examples and documentation, can also be freely downloaded for a local execution.

摘要

为了理解基因组的进化、结构和功能,了解DNA序列的一般组成特征非常重要。基于二次发散,提出了一种新的分割算法,用于将给定的基因组或DNA序列划分为组成不同的结构域。借助累积GC分布图技术,可以直观地显示分割点的分布。因此,我们将它们开发成了GC-Profile,这是一个基于网络的交互式软件系统,可用于分割原核生物和真核生物基因组。GC-Profile提供了基因组组织的定量和定性视图。根据获得的结果,可以以一种可感知的方式分析G+C含量与其他基因组特征(如基因分布和CpG岛)之间的关系。结果表明,GC-Profile将是分析高等真核生物基因组等密度区结构的合适起点,也是识别原核生物基因组中基因组岛的直观工具。GC-Profile可在网站http://tubic.tju.edu.cn/GC-Profile/上免费获取。此外,预编译的二进制文件以及示例和文档也可以免费下载用于本地执行。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/67ae/1538862/0761760d5d3a/gkl040f1.jpg

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