PrOCoil - Predicting the Oligomerization of Coiled Coil Proteins
This is a legacy page. The package is now hosted on GitHub.
We have developed an SVM-based classification method for predicting whether a given coiled coil sequence is a trimer or dimer (assuming that it is one of both). This method also allows for a deep analysis of the sequence which residues are mainly responsible for the outcome. The software is available as an R package procoil and as a simple-to-use Web application.Important Note: the prediction models have been updated with the release of version 2.0.0 of the PrOCoil R package. The updated data sets and some information on how they have been collected are available from the PrOCoil Data Repository (v2). If you want to use the original prediction models as published by Mahrenholz et al. (2011), please follow the instructions in Section 5.5.3 of the user manual). The data sets on which the original PrOCoil models were based are still available from the PrOCoil Data Repository (v1).
Installation
The R package procoil is available from Bioconductor. Therefore, the the simplest way to install the package is to enter
if (!requireNamespace("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("procoil")
into your R session. If, for what reason ever, you prefer to install the package manually, follow the instructions in the user manual.
User support
If you encounter any issues or if you have any question that might be of interest also for other users, before writing a private message to the package developers/maintainers, please create an issue in the source code repository and also consider posting on Bioconductor Support or StackOverflow.How to cite PrOCoil
If you use PrOCoil for research that is published later, you are kindly asked to cite it as follows:C. C. Mahrenholz, I. G. Abfalter, U. Bodenhofer, R. Volkmer, and S. Hochreiter. Complex networks govern coiled coil oligomerization - predicting and profiling by means of a machine learning approach. Mol. Cell. Proteomics 10(5):M110.004994, 2011. DOI: 10.1074/mcp.M110.004994