AATP_TPCC: AATP_TPC feature vector

Description Usage Arguments Value References See Also Examples

View source: R/AATP_TPC.R

Description

For getting this feature which was 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 fusing it with other vector of length 400 called TPC, which is similar to DPC_PSSM AATP feature vector of length 420 is obtained.

Usage

1
AATP_TPCC(pssm_name)

Arguments

pssm_name

is name of PSSM Matrix file

Value

a feature vector of length 420

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

1
as<-AATP_TPCC(paste0(system.file("extdata",package="PSSMCOOL"),"/C7GQS7.txt.pssm"))

BioCool-Lab/R-PSSM documentation built on Jan. 1, 2022, 2:05 p.m.