Features Extracted from Position Specific Scoring Matrix (PSSM)
PSSM400 feature
PSSM BLOCK feature vector
AAC-PSSM feature vectors
DPC-PSSM,AAC-PSSM and AADP-PSSM feature vectors
AATP_TPC feature vector
AB-PSSM feature vector
Averag Block feature vector
consunsus_sequence
CSP-SegPseP-SegACP feature vector
DMACA-PSSM feature
Discrete Cosin Transform Feature
Disulfide connectivity feature
DP_PSSM feature vector
DPC_PSSM feature vector
discrete wavelet transform feature vector
EDP_EEDP_MEDP feature vector
D-FPSSM and SF-PSSM feature vectors
Mixture of Two FPSSM Features
grey pssm feature vector
3-mer and 2-mer in dataframe
k_separated_bigrams_pssm feature vector
kiderafactor feature
Linear predictive coding feature
MBMGACPSSM feature
pseudo position-specific scoring matrix feature
auto covariance transformation feature vector
Cross covarianse feature vector
PSSM-COMPOSITION feature
PSSM-SD feature
PSSM-Seg feature vector
PSSMCOOL:Extracting Various Feature vectors from PSSM Matrix
RPM-PSSM feature vector
RPSSM feature
SCSH Feature vector
single Average feature
smoothed PSSM feature
SOMA PSSM Feature
Singular Value Decomposition (SVD)
3-Mer and 2-Mer
trigrame feature vector
Returns almost all features that has been extracted from Position Specific Scoring Matrix (PSSM) so far, which is a matrix of L rows (L is protein length) and 20 columns produced by 'PSI-BLAST' which is a program to produce PSSM Matrix from multiple sequence alignment of proteins see <https://www.ncbi.nlm.nih.gov/books/NBK2590/> for mor details. some of these features are described in Zahiri, J., et al.(2013) <DOI:10.1016/j.ygeno.2013.05.006>, Saini, H., et al.(2016) <DOI:10.17706/jsw.11.8.756-767>, Ding, S., et al.(2014) <DOI:10.1016/j.biochi.2013.09.013>, Cheng, C.W., et al.(2008) <DOI:10.1186/1471-2105-9-S12-S6>, Juan, E.Y., et al.(2009) <DOI:10.1109/CISIS.2009.194>.