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LocTree2 可预测所有生命领域的定位。

LocTree2 predicts localization for all domains of life.

机构信息

TUM, Bioinformatik-I12, Informatik, Boltzmannstrasse 3, Garching 85748, Germany.

出版信息

Bioinformatics. 2012 Sep 15;28(18):i458-i465. doi: 10.1093/bioinformatics/bts390.

Abstract

MOTIVATION

Subcellular localization is one aspect of protein function. Despite advances in high-throughput imaging, localization maps remain incomplete. Several methods accurately predict localization, but many challenges remain to be tackled.

RESULTS

In this study, we introduced a framework to predict localization in life's three domains, including globular and membrane proteins (3 classes for archaea; 6 for bacteria and 18 for eukaryota). The resulting method, LocTree2, works well even for protein fragments. It uses a hierarchical system of support vector machines that imitates the cascading mechanism of cellular sorting. The method reaches high levels of sustained performance (eukaryota: Q18=65%, bacteria: Q6=84%). LocTree2 also accurately distinguishes membrane and non-membrane proteins. In our hands, it compared favorably with top methods when tested on new data.

AVAILABILITY

Online through PredictProtein (predictprotein.org); as standalone version at http://www.rostlab.org/services/loctree2.

CONTACT

localization@rostlab.org

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

摘要

动机

亚细胞定位是蛋白质功能的一个方面。尽管高通量成像技术取得了进展,但定位图谱仍然不完整。有几种方法可以准确预测定位,但仍有许多挑战需要解决。

结果

在这项研究中,我们引入了一个框架来预测生命的三个领域的定位,包括球状蛋白和膜蛋白(古菌 3 类;细菌 6 类;真核生物 18 类)。由此产生的方法 LocTree2 即使对于蛋白质片段也能很好地工作。它使用支持向量机的分层系统来模拟细胞分选的级联机制。该方法达到了较高的持续性能水平(真核生物:Q18=65%,细菌:Q6=84%)。LocTree2 还能准确地区分膜蛋白和非膜蛋白。在我们的测试中,与新数据相比,它与顶级方法相比表现出色。

可用性

通过 PredictProtein(predictprotein.org)在线提供;作为独立版本在 http://www.rostlab.org/services/loctree2 上提供。

联系人

localization@rostlab.org

补充信息

补充数据可在生物信息学在线获得。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ebf6/3436817/d542ea887180/bts390f1.jpg

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