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MeDor:一种用于预测蛋白质无序状态的元服务器。

MeDor: a metaserver for predicting protein disorder.

作者信息

Lieutaud Philippe, Canard Bruno, Longhi Sonia

机构信息

Architecture et Fonction des Macromolécules Biologiques, UMR 6098 CNRS et Universités Aix-Marseille I et II, 163 Avenue de Luminy, Case 932, 13288 Marseille Cedex 09, France.

出版信息

BMC Genomics. 2008 Sep 16;9 Suppl 2(Suppl 2):S25. doi: 10.1186/1471-2164-9-S2-S25.

Abstract

BACKGROUND

We have previously shown that using multiple prediction methods improves the accuracy of disorder predictions. It is, however, a time-consuming procedure, since individual outputs of multiple predictions have to be retrieved, compared to each other and a comprehensive view of the results can only be obtained through a manual, fastidious, non-automated procedure. We herein describe a new web metaserver, MeDor, which allows fast, simultaneous analysis of a query sequence by multiple predictors and provides a graphical interface with a unified view of the outputs.

RESULTS

MeDor was developed in Java and is freely available and downloadable at: http://www.vazymolo.org/MeDor/index.html. Presently, MeDor provides a HCA plot and runs a secondary structure prediction, a prediction of signal peptides and transmembrane regions and a set of disorder predictions. MeDor also enables the user to customize the output and to retrieve the sequence of specific regions of interest.

CONCLUSION

As MeDor outputs can be printed, saved, commented and modified further on, this offers a dynamic support for the analysis of protein sequences that is instrumental for delineating domains amenable to structural and functional studies.

摘要

背景

我们之前已经表明,使用多种预测方法可提高疾病预测的准确性。然而,这是一个耗时的过程,因为必须检索多种预测的单独输出,相互比较,并且只有通过手动、繁琐、非自动化的过程才能获得结果的全面视图。我们在此描述一种新的网络元服务器MeDor,它允许通过多个预测器对查询序列进行快速、同步分析,并提供一个具有统一输出视图的图形界面。

结果

MeDor是用Java开发的,可在以下网址免费获取和下载:http://www.vazymolo.org/MeDor/index.html。目前,MeDor提供一个热图聚类分析图,并运行二级结构预测、信号肽预测、跨膜区域预测以及一组无序预测。MeDor还允许用户自定义输出,并检索感兴趣的特定区域的序列。

结论

由于MeDor的输出可以打印、保存、注释并进一步修改,这为蛋白质序列分析提供了动态支持,有助于描绘适合进行结构和功能研究的结构域。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4d1e/2559890/3488f0202806/1471-2164-9-S2-S25-1.jpg

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