ProCope
ProCope is a software package which provides easy access to
different methods used for the prediction and evaluation of protein
complexes from purification data experiments.
Large scale protein purification experiments provide a vast amount of indirect protein-protein interaction information. As these data are inherently noisy and incomplete, sophisticated methods are required to predict actual protein complexes existing and operating in-vivo. Since the publication of two large-scale purification datasets for the yeast Saccharomyces cerevisiae in 2006 (Gavin et al. and Krogan et al.) different methods for the processing of these datasets have been developed. These include methods for the derivation of PPI score networks from the data, the clustering of these networks to predict actual complexes and the evaluation of the predictions using experimental data.
ProCope implements many of the methods described in the literature along with further useful methods for PPI score network manipluation, complex set manipulation, data integration with Petri nets and result visualization. All functionality can be accessed using a graphical user interface, a collection of command line tools and an application programming interface (API) to use all these features in your own computer programs. In addition, ProCope contains a plugin for the Cytoscape software platform which allows the user to visualize protein networks, complex sets and purification data sets. The whole software package is written in Java and requires the Java Runtime Environment 5.0 or higher.
ProCope is freely available under the GNU Lesser General Pub lic License (LGPL).
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Large scale protein purification experiments provide a vast amount of indirect protein-protein interaction information. As these data are inherently noisy and incomplete, sophisticated methods are required to predict actual protein complexes existing and operating in-vivo. Since the publication of two large-scale purification datasets for the yeast Saccharomyces cerevisiae in 2006 (Gavin et al. and Krogan et al.) different methods for the processing of these datasets have been developed. These include methods for the derivation of PPI score networks from the data, the clustering of these networks to predict actual complexes and the evaluation of the predictions using experimental data.
ProCope implements many of the methods described in the literature along with further useful methods for PPI score network manipluation, complex set manipulation, data integration with Petri nets and result visualization. All functionality can be accessed using a graphical user interface, a collection of command line tools and an application programming interface (API) to use all these features in your own computer programs. In addition, ProCope contains a plugin for the Cytoscape software platform which allows the user to visualize protein networks, complex sets and purification data sets. The whole software package is written in Java and requires the Java Runtime Environment 5.0 or higher.
ProCope is freely available under the GNU Lesser General Pub lic License (LGPL).
Show all