SOMA_PSSM: SOMA PSSM Feature

In PSSMCOOL: Features Extracted from Position Specific Scoring Matrix (PSSM)

Description

In this function each column can be viewed as a stochastic time series, and each PSSM contains 20 columns, in other words, each PSSM contains 20 stochastic time series and Second-order moving average (SOMA) algorithm is applied to these columns to extract SOMA PSSM feature vector.

Usage

SOMA_PSSM(pssm_name)

Arguments

pssm_name

name of PSSM file

Value

feature vector of length 160

References

Y. Liang, S. J. J. o. M. G. Zhang, and Modelling, "Predict protein structural class by incorporating two different modes of evolutionary information into Chou's general pseudo amino acid composition," vol. 78, pp. 110-117, 2017.

Examples

X<-SOMA_PSSM(system.file("extdata", "C7GQS7.txt.pssm", package="PSSMCOOL"))

PSSMCOOL documentation built on Jan. 4, 2022, 5:07 p.m.