PSSMCOOL (version 0.2.4)

PSSMBLOCK: PSSM BLOCK feature vector

Description

In this feature at first PSSM Matrix is divided to Blocks based on Number N which user imports. Then for each Block mean of columns is computed to get 20-dimensional vector, eventually by appending these vectors to each other final feature vector is obtained.

Usage

PSSMBLOCK(pssm_name, N = 5)

Arguments

pssm_name

neme of PSSM Matrix file

N

number of blocks

Value

feature vector that it's length depends on parameter N

References

J.-Y. An, L. Zhang, Y. Zhou, Y.-J. Zhao, and D.-F. J. J. o. c. Wang, "Computational methods using weighed-extreme learning machine to predict protein self-interactions with protein evolutionary information," vol. 9, no. 1, p. 47, 2017.

Examples

# NOT RUN {
X<-PSSMBLOCK(system.file("extdata", "C7GQS7.txt.pssm", package="PSSMCOOL"),5)
# }