DPC_PSSM: DPC-PSSM,AAC-PSSM and AADP-PSSM feature vectors

Description Usage Arguments Value References Examples

View source: R/DPC-PSSM.R

Description

This feature is combination of amino asid composition and dipeptide composition feature vectors. DPC feature stands for dipeptide composition, which multiplies the values in two consecutive rows and two different columns, calculating this for each of the different columns and obtaining the sum of these and for each. And for both columns, the product divides their sum by L-1, and because the result depends on two different columns, length of this feature vector would be 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.

Usage

1
DPC_PSSM(pssm_name)

Arguments

pssm_name

name of PSSM Matrix file

Value

feature vector of length 420

References

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.

Examples

1
ss<-DPC_PSSM(system.file("extdata", "C7GQS7.txt.pssm", package="PSSMCOOL"))

Example output



PSSMCOOL documentation built on Oct. 25, 2020, 5:07 p.m.