This package contains the functions necessary to run the SCORER 2.0 algorithm. SCORER 2.0 can be used to differentiate between parallel dimeric and trimeric coiled-coil sequence, which are the two most more frequent coiled-coil structures observed naturally. As such, SCORER 2.0 is particularly useful for researchers looking to characterize novel coiled-coil sequences. It may also be used to assist in the structural characterization of synthetic coiled-coil sequences. Also included in this package are functions that allows the user to retrain the SCORER 2.0 algorithm using user-defined training data.
|Author||Craig T. Armstrong, Thomas L. Vincent <firstname.lastname@example.org>, Peter J. Green and Derek N. Woolfson <D.N.Woolfson@bristol.ac.uk>|
|Date of publication||2014-01-17 06:10:40|
|Maintainer||Thomas L. Vincent <email@example.com>|
|License||GPL (>= 2)|
CreatePssm: Compute profile scoring matrices for training data
EstimateProbability: Estimate oligomeric state score of coiled-coil sequences
pssm: Profile scoring matrix derived from the original SCORER 2.0...
RetrainScorer2: Retrain the SCORER 2.0 algorithm with user-defined training...
scorer2: Predict oligomerization state of coiled-coil sequences
scorer-package: Predict oligomerization state of coiled-coil sequences
training: Training dataset used to contruct the profile scoring matrix...