Description Usage Arguments Value References Examples
This feature is combination of amino asid composition and dipeptide composition feature vectors. DPC feature stands for dipeptide composition, to get this feature vector for both different columns the elements in two consecutive rows corresponds to this columns, would be multiplied and this scenario is done for all L-1 consecutive rows (L is protein length) and finally summation of these numbers divides by L-1. since the result depends on two different columns, eventually DPC Feature vector would be of length 400. AAC-PSSM is actually mean of PSSM Matrix columns which its length is 20. eventually AADP-PSSM is combination of these vectors and with length 420.
1 | aadp_pssm(pssm_name)
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pssm_name |
name of PSSM Matrix file |
feature vector of length 420
Liu, T., Zheng, X. and Wang, J. (2010) Prediction of protein structural class for low-similarity sequences using support vector machine and PSI-BLAST profile, Biochimie, 92, 1330-1334.
1 | X<-aadp_pssm(system.file("extdata", "C7GQS7.txt.pssm", package="PSSMCOOL"))
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