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CLANS:一个基于成对相似性可视化蛋白质家族的Java应用程序。

CLANS: a Java application for visualizing protein families based on pairwise similarity.

作者信息

Frickey Tancred, Lupas Andrei

机构信息

Max Planck Institut fuer Entwicklungsbiologie, Spemannstrasse 35, 72076 Tuebingen, Germany.

出版信息

Bioinformatics. 2004 Dec 12;20(18):3702-4. doi: 10.1093/bioinformatics/bth444. Epub 2004 Jul 29.

Abstract

SUMMARY

The main source of hypotheses on the structure and function of new proteins is their homology to proteins with known properties. Homologous relationships are typically established through sequence similarity searches, multiple alignments and phylogenetic reconstruction. In cases where the number of potential relationships is large, for example in P-loop NTPases with many thousands of members, alignments and phylogenies become computationally demanding, accumulate errors and lose resolution. In search of a better way to analyze relationships in large sequence datasets we have developed a Java application, CLANS (CLuster ANalysis of Sequences), which uses a version of the Fruchterman-Reingold graph layout algorithm to visualize pairwise sequence similarities in either two-dimensional or three-dimensional space.

AVAILABILITY

CLANS can be downloaded at http://protevo.eb.tuebingen.mpg.de/download.

摘要

摘要

关于新蛋白质结构和功能的假设的主要来源是它们与具有已知特性的蛋白质的同源性。同源关系通常通过序列相似性搜索、多重比对和系统发育重建来建立。在潜在关系数量很大的情况下,例如在有成千上万个成员的P-loop NTPases中,比对和系统发育分析在计算上要求很高,会累积错误并失去分辨率。为了寻找一种更好的方法来分析大型序列数据集的关系,我们开发了一个Java应用程序CLANS(序列聚类分析),它使用Fruchterman-Reingold图布局算法的一个版本在二维或三维空间中可视化成对的序列相似性。

可用性

CLANS可从http://protevo.eb.tuebingen.mpg.de/download下载。

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