Recognizes anticancer peptides using the CancerGram algorithm.
further arguments passed to or from other methods.
CancerGram requires the external package, CancerGramModel, which
contains models necessary to perform the prediction. The model
can be installed using
Predictions for each protein are stored in objects of class
single_cancergram_pred. It consists of three elements:
Character vector of amino acid sequence of an analyzed peptide/protein
Matrix of predictions for each 5-mer (subsequence of 5 amino acids) of a sequence. Each row corresponds to one mer and columns to predicted classes (ACP, AMP or negative). Prediction value indicates probability that a 5-mer possesses anticancer activity (acp), antimicrobial activity (amp) or none of them (neg).
One row matrix of a single prediction value for a whole peptide/protein. Its value corresponds to the probability that a peptide/protein exhibits anticancer activity, antimicrobial activity or none of them.
list of objects of class
Each object of this class contains analyzed sequence, values of predictions
for 5-mers and result of the prediction for the whole peptide/protein.
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