Description Usage Arguments Value Author(s) References Examples
Subfunction used in LOGICOIL to compute the oligomeric state score of input coiledcoil sequences.
1  EstimateProbability(id, seq, reg, pssm, LOGICOILfit, Model_Parameters)

id 
A string that represents the id name of the input sequence 
seq 
A character string of the aminoacid sequence to be predicted. Valid characters are all uppercase letters except ‘B’, ‘J’, ‘O’, ‘U’, ‘X’, and ‘Z’; 
reg 
A character string of register assignements. Valid characters are the lowercase letters ‘a’ to ‘g’. Register characters are not required to be in proper order and may start with any of the seven letters. It must always have the same length as the matching aminoacid sequence. 
pssm 
A profile scoring matrix generated from the LOGICOIL training data. 
LOGICOILfit 
The fitted model for LOGICOIL obtained using the original training data. 
Model_Parameters 
A list containing five elements, which are required to run the LOGICOIL model:

Returns a matrix of dimension n x 4, where n is the length of the input coiledcoil sequence, and each column represents the LOGICOIL scores for antiparallel dimer, parallel, trimer and higherorder coiled coiled. For examples, the first row gives the predicted LOGICOIL scores of the first position of the input coiledcoil sequence. If a given sequence scores f(x)==1, then there is no evidence for a particular oligomeric state. If f(x) > 1 then there is strong evidence for a particular oligimeric state, and if f(x) < 1 then there is less evidence against a particular oligimeric state.
Thomas L. Vincent tlfvincent@gmail.com
Thomas L. Vincent, Peter J. Green and Dek N. Woolfson. "LOGICOILmultistate prediction of coiledcoil oligomeric state", 29(1), pp6976, Bioinformatics, (2013). DOI: 10.1093/bioinformatics/bts648
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23  # load pssm data
library(nnet)
data(pssm)
data(Model_Parameters)
data(LOGICOILfit)
# priors obtained from LOGICOIL training set
prior < c(0.6331,0.237,0.053,0.0769)
# compute test scores
cat("Estimating oligomeric state of coiledcoil sequences")
prob.oligo < EstimateProbability("GCN4wt",
"MKQLEDKVEELLSKNYHLENEVARLKKLV",
"abcdefgabcdefgabcdefgabcdefga",
pssm,
LOGICOILfit,
Model_Parameters)
# compute final summary probability for whole sequence
score < apply(prob.oligo, 2, mean) / prior
# print output
print(score)

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