{ "_id": "6a1042f5acfb0bcc41c9dd8d", "Package": "PSSMCOOL", "Type": "Package", "Title": "Features Extracted from Position Specific Scoring Matrix (PSSM)", "Version": "0.2.2", "Authors@R": "c(\nperson(\"Javad\", \"zahiri\", email = \"zahiri@modares.ac.ir\", role = \"aut\"),\nperson(\"Alireza\", \"mohammadi\", email = \"alireza691111@gmail.com\", role = c(\"aut\",\"cre\")))", "Maintainer": "Alireza mohammadi ", "Description": "Returns almost all features that has been extracted from\nPosition Specific Scoring Matrix (PSSM) so far, which is a\nmatrix of L rows (L is protein length) and 20 columns produced\nby 'PSI-BLAST' which is a program to produce PSSM Matrix from\nmultiple sequence alignment of proteins see\n for mor details.\nsome of these features are described in Zahiri, J., et\nal.(2013) , Saini, H., et\nal.(2016) , Ding, S., et\nal.(2014) , Cheng, C.W., et\nal.(2008) , Juan, E.Y., et\nal.(2009) .", "License": "GPL-3", "URL": "https://github.com/Alireza9651501005/PSSMCOOL", 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"page": "AATP_TPCC", "title": "AATP_TPC feature vector", "topics": [ "AATP_TPCC" ] }, { "page": "AB_PSSM", "title": "AB-PSSM and RPM-PSSM feature vector", "topics": [ "AB_PSSM" ] }, { "page": "Averag_Block", "title": "Averag Block feature vector", "topics": [ "Averag_Block" ] }, { "page": "consunsus_sequence", "title": "consunsus_sequence", "topics": [ "consunsus_sequence" ] }, { "page": "CS_PSe_PSSM", "title": "CSP-SegPseP-SegACP feature vector", "topics": [ "CS_PSe_PSSM" ] }, { "page": "DFMCA_PSSM", "title": "DMACA-PSSM feature", "topics": [ "DFMCA_PSSM" ] }, { "page": "Discrete_Cosine_Transform", "title": "Discrete Cosin Transform Feature", "topics": [ "Discrete_Cosine_Transform" ] }, { "page": "disulfid", "title": "Disulfide connectivity feature", "topics": [ "disulfid" ] }, { "page": "DP_PSSM", "title": "DP_PSSM feature vector", "topics": [ "DP_PSSM" ] }, { "page": "DPC_PSSM", "title": "DPC-PSSM,AAC-PSSM and AADP-PSSM feature vectors", "topics": [ "DPC_PSSM" ] }, { "page": "dwt_PSSM", "title": "discrete wavelet transform feature vector", "topics": [ "dwt_PSSM" ] }, { "page": "EDP_MEDP", "title": "EDP_EEDP_MEDP feature vector", "topics": [ "EDP_MEDP" ] }, { "page": "FPSSM", "title": "D-FPSSM and SF-PSSM feature vectors", "topics": [ "FPSSM" ] }, { "page": "FPSSM2", "title": "Mixture of Two FPSSM Features", "topics": [ "FPSSM2" ] }, { "page": "grey_pssm_pseAAC", "title": "grey pssm feature vector", "topics": [ "grey_pssm_pseAAC" ] }, { "page": "k_mers", "title": "3-mer and 2-mer in dataframe", "topics": [ "k_mers" ] }, { "page": "k_seperated_bigrame", "title": "k_seperated_bigrame feature vector", "topics": [ "k_seperated_bigrame" ] }, { "page": "kiderafactor", "title": "kiderafactor feature", "topics": [ "kiderafactor" ] }, { "page": "LPC_PSSM", "title": "Linear predictive coding feature", "topics": [ "LPC_PSSM" ] }, { "page": "MBMGACPSSM", "title": "MBMGACPSSM feature", "topics": [ "MBMGACPSSM" ] }, { "page": "pse_pssm", "title": "pseudo position-specific scoring matrix feature", "topics": [ "pse_pssm" ] }, { "page": "pssm_ac", "title": "auto covariance transformation feature vector", "topics": [ "pssm_ac" ] }, { "page": "pssm_cc", "title": "Cross covarianse feature vector", "topics": [ "pssm_cc" ] }, { "page": "PSSM_SD", "title": "PSSM-SD feature", "topics": [ "PSSM_SD" ] }, { "page": "pssm_seg", "title": "PSSM-Seg feature vector", "topics": [ "pssm_seg" ] }, { "page": "pssm400", "title": "PSSM400 feature", "topics": [ "pssm400" ] }, { "page": "PSSMAC", "title": "PSSMAC feature", "topics": [ "PSSMAC" ] }, { "page": "PSSMBLOCK", "title": "PSSM BLOCK feature vector", "topics": [ "PSSMBLOCK" ] }, { "page": "rpssm", "title": "RPSSM feature", "topics": [ "rpssm" ] }, { "page": "scsh2", "title": "SCSH Feature vector", "topics": [ "scsh2" ] }, { "page": "single_Average", "title": "single Average feature", "topics": [ "single_Average" ] }, { "page": "smoothed_PSSM", "title": "smoothed PSSM feature", "topics": [ 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