Krumsiek Jan, Friedel Caroline C, Zimmer Ralf
Institut für Informatik, Ludwig-Maximilians-Universität München, Amalienstrasse 17, 80333 München, Germany.
Bioinformatics. 2008 Sep 15;24(18):2115-6. doi: 10.1093/bioinformatics/btn376. Epub 2008 Jul 17.
Recent advances in high-throughput technology have increased the quantity of available data on protein complexes and stimulated the development of many new prediction methods. In this article, we present ProCope, a Java software suite for the prediction and evaluation of protein complexes from affinity purification experiments which integrates the major methods for calculating interaction scores and predicting protein complexes published over the last years. Methods can be accessed via a graphical user interface, command line tools and a Java API. Using ProCope, existing algorithms can be applied quickly and reproducibly on new experimental results, individual steps of the different algorithms can be combined in new and innovative ways and new methods can be implemented and integrated in the existing prediction framework.
Source code and executables are available at http://www.bio.ifi.lmu.de/Complexes/ProCope/.
高通量技术的最新进展增加了蛋白质复合物可用数据的数量,并推动了许多新预测方法的发展。在本文中,我们介绍了ProCope,这是一个用于从亲和纯化实验中预测和评估蛋白质复合物的Java软件套件,它整合了过去几年发表的计算相互作用分数和预测蛋白质复合物的主要方法。可以通过图形用户界面、命令行工具和Java API访问这些方法。使用ProCope,可以在新的实验结果上快速且可重复地应用现有算法,不同算法的各个步骤可以以新颖的方式组合,并且可以在现有的预测框架中实现和集成新方法。