PrOCoil - Predicting the Oligomerization of Coiled Coil Proteins
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
and as a simple-to-use Web application
. All data used for evaluating the computational approach
and for training the final models are available for download
Installation of R package procoil via Bioconductor
The R package procoil
is available from
The current version of the package is 1.12.0 and has been released as part of
on October 15, 2013. To install procoil
, follow the simple standard procedure
for installing Bioconductor packages, i.e. enter the following into your R session:
Please note that Bioconductor 2.13 requires an R version ≥ 3.0.2.
Manual installation on older R versions
We recommend potential users to use the latest version of R and Bioconductor and to follow the installation
procedure described above. The R package procoil
1.12.0, however, also works with older R versions.
If you have an R version ≥ 2.10.1, you can still use procoil
1.6.0, but you have to download and install
the package manually:
- Download the suitable package file from the Bioconductor 2.13 procoil page.
- Follow the standard procedure for installing the package file on your system.
To use the package, enter "library(procoil)
" in your R session.
To get a basic introduction, enter "help(procoil)
" or open the
user manual by entering "vignette("procoil")
- User Manual:
(also contains documentation of Web interface)
- Reference Manual:
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.