AATP_TPC: AATP_TPC feature vector

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

Description

For getting this features which have been used to protein structural class prediction, at first mean of every column in PSSM Matrix is computed to achieve a 20-dimensional vector called AAC.then by combining it with other vector of length 400 called TPC, which is similar to dpc_pssm AATP feature vector of length 420 is obtained.

Usage

AATP_TPC(pssm_name)

Arguments

pssm_name

is name of PSSM Matrix file

Value

list of two feature vectors with 400 and 420 dimensions

References

Zhang, S., Ye, F. and Yuan, X. (2012) Using principal component analysis and support vector machine to predict protein structural class for low-similarity sequences via PSSM, Journal of Biomolecular Structure & Dynamics, 29, 634-642.

See Also

dpc_pssm

Examples

X<-AATP_TPC(paste0(system.file("extdata",package="PSSMCOOL"),"/C7GQS7.txt.pssm"))

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