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Volumn 116, Issue 3, 2014, Pages 184-192

Discriminating protein structure classes by incorporating Pseudo Average Chemical Shift to Chou's general PseAAC and Support Vector Machine

Author keywords

Protein structure classes; PseAA composition; Pseudo Average Chemical Shift; SVM

Indexed keywords

AMINO ACIDS; BENCHMARKING; CHEMICAL SHIFT; FEATURE EXTRACTION; SUPPORT VECTOR MACHINES;

EID: 84904506417     PISSN: 01692607     EISSN: 18727565     Source Type: Journal    
DOI: 10.1016/j.cmpb.2014.06.007     Document Type: Article
Times cited : (56)

References (97)
  • 1
    • 84863864586 scopus 로고    scopus 로고
    • Accurate prediction of protein structural classes using functional domains and predicted secondary structure sequences
    • Adl A.A., Dalini A.N., Xue B., Uversky V.N., Qian X. Accurate prediction of protein structural classes using functional domains and predicted secondary structure sequences. J. Biomol. Struct. Dynam. 2012, 29:623-633.
    • (2012) J. Biomol. Struct. Dynam. , vol.29 , pp. 623-633
    • Adl, A.A.1    Dalini, A.N.2    Xue, B.3    Uversky, V.N.4    Qian, X.5
  • 2
    • 84862651693 scopus 로고    scopus 로고
    • Mito-GSAAC: mitochondria prediction using genetic ensemble classifier and split amino acid composition
    • Afridi T.H., Khan A., Lee Y.S. Mito-GSAAC: mitochondria prediction using genetic ensemble classifier and split amino acid composition. Amino Acids 2012, 42:1443-1454.
    • (2012) Amino Acids , vol.42 , pp. 1443-1454
    • Afridi, T.H.1    Khan, A.2    Lee, Y.S.3
  • 3
    • 45649085108 scopus 로고    scopus 로고
    • Suganthan Predicting protein structural class by SVM with class-wise optimized features and decision probabilities
    • Anand G., Pugalenthi P.N., Suganthan Predicting protein structural class by SVM with class-wise optimized features and decision probabilities. J. Theor. Biol. 2008, 253:375-380.
    • (2008) J. Theor. Biol. , vol.253 , pp. 375-380
    • Anand, G.1    Pugalenthi, P.N.2
  • 4
    • 0015859467 scopus 로고
    • Principles that govern the folding of protein chains
    • Anfinsen C. Principles that govern the folding of protein chains. Science 1973, 181:223-230.
    • (1973) Science , vol.181 , pp. 223-230
    • Anfinsen, C.1
  • 5
    • 77957895860 scopus 로고    scopus 로고
    • Protein secondary structure prediction using modular reciprocal bidirectional recurrent neural networks
    • Babaei S., Geranmayeh A., Seyyedsalehi S.A. Protein secondary structure prediction using modular reciprocal bidirectional recurrent neural networks. Comput. Methods Programs Biomed. 2010, 100:237-247.
    • (2010) Comput. Methods Programs Biomed. , vol.100 , pp. 237-247
    • Babaei, S.1    Geranmayeh, A.2    Seyyedsalehi, S.A.3
  • 6
    • 0030955263 scopus 로고    scopus 로고
    • Understanding the recognition of protein structural classes by amino acid composition
    • Bahar I., Atilgan A.R., Jernigan R.L., Erman B. Understanding the recognition of protein structural classes by amino acid composition. Proteins 1997, 29:172-185.
    • (1997) Proteins , vol.29 , pp. 172-185
    • Bahar, I.1    Atilgan, A.R.2    Jernigan, R.L.3    Erman, B.4
  • 7
    • 28444439947 scopus 로고    scopus 로고
    • Using LogitBoost classifier to predict protein structural classes
    • Cai Y.D., Feng K.Y., Lu W.C., Chou K.C. Using LogitBoost classifier to predict protein structural classes. J. Theor. Biol. 2006, 238:172-176.
    • (2006) J. Theor. Biol. , vol.238 , pp. 172-176
    • Cai, Y.D.1    Feng, K.Y.2    Lu, W.C.3    Chou, K.C.4
  • 8
    • 0033809190 scopus 로고    scopus 로고
    • Prediction of protein structural classes by neural network
    • Cai Y.D., Zhou G.P. Prediction of protein structural classes by neural network. Biochimie 2000, 82:783-785.
    • (2000) Biochimie , vol.82 , pp. 783-785
    • Cai, Y.D.1    Zhou, G.P.2
  • 9
    • 84875576158 scopus 로고    scopus 로고
    • Propy: a tool to generate various modes of Chou's PseAAC
    • Cao D.S., Xu Q.S., Liang Y.Z. Propy: a tool to generate various modes of Chou's PseAAC. Bioinformatics 2013, 29:960-962.
    • (2013) Bioinformatics , vol.29 , pp. 960-962
    • Cao, D.S.1    Xu, Q.S.2    Liang, Y.Z.3
  • 11
    • 46449128812 scopus 로고    scopus 로고
    • Prediction of protein structural class using novel evolutionary collocation-based sequence representation
    • Chen K., Kurgan L.A., Ruan J.S. Prediction of protein structural class using novel evolutionary collocation-based sequence representation. J. Comput. Chem. 2008, 29:1596-1604.
    • (2008) J. Comput. Chem. , vol.29 , pp. 1596-1604
    • Chen, K.1    Kurgan, L.A.2    Ruan, J.S.3
  • 12
    • 84897713538 scopus 로고    scopus 로고
    • A hybrid method for prediction and repositioning of drug Anatomical Therapeutic Chemical classes
    • Chen L., Lu J., Zhang N., Huang T., Cai Y.D. A hybrid method for prediction and repositioning of drug Anatomical Therapeutic Chemical classes. Mol. Biosyst. 2014, 10:868-877.
    • (2014) Mol. Biosyst. , vol.10 , pp. 868-877
    • Chen, L.1    Lu, J.2    Zhang, N.3    Huang, T.4    Cai, Y.D.5
  • 13
    • 84876053736 scopus 로고    scopus 로고
    • IRSPOT-PSEDNC. Identify recombination spots with pseudo dinucleotide composition
    • Chen W., Feng P.M., Lin H., Chou K.C. IRSPOT-PSEDNC. Identify recombination spots with pseudo dinucleotide composition. Nucleic Acids Res. 2013, 41:e68.
    • (2013) Nucleic Acids Res. , vol.41
    • Chen, W.1    Feng, P.M.2    Lin, H.3    Chou, K.C.4
  • 14
    • 84868128310 scopus 로고    scopus 로고
    • INuc-PhysChem: a sequence-based predictor for identifying nucleosomes via physicochemical properties
    • Chen W., Lin H., Feng P.M., Ding C., Zuo Y.C., Chou K.C. iNuc-PhysChem: a sequence-based predictor for identifying nucleosomes via physicochemical properties. PLOS ONE 2012, 7:e47843.
    • (2012) PLOS ONE , vol.7
    • Chen, W.1    Lin, H.2    Feng, P.M.3    Ding, C.4    Zuo, Y.C.5    Chou, K.C.6
  • 15
    • 0027324791 scopus 로고
    • A joint prediction of the folding types of 1490 human proteins from their genetic codons
    • Chou J.J., Zhang C.T. A joint prediction of the folding types of 1490 human proteins from their genetic codons. J. Theor. Biol. 1993, 161:251-262.
    • (1993) J. Theor. Biol. , vol.161 , pp. 251-262
    • Chou, J.J.1    Zhang, C.T.2
  • 16
    • 0029051959 scopus 로고
    • A novel approach to predicting protein structural classes in a (20-1)-D amino acid composition space
    • Chou K.C. A novel approach to predicting protein structural classes in a (20-1)-D amino acid composition space. Proteins: Struct. Funct. Genet. 1995, 21:319-344.
    • (1995) Proteins: Struct. Funct. Genet. , vol.21 , pp. 319-344
    • Chou, K.C.1
  • 17
    • 0033554601 scopus 로고    scopus 로고
    • A key driving force in determination of protein structural classes
    • Chou K.C. A key driving force in determination of protein structural classes. Biochem. Biophys. Res. Commun. 1999, 264:216-224.
    • (1999) Biochem. Biophys. Res. Commun. , vol.264 , pp. 216-224
    • Chou, K.C.1
  • 18
    • 0035874091 scopus 로고    scopus 로고
    • Prediction of protein subcellular attributes using pseudo-amino acid composition
    • Chou K.C. Prediction of protein subcellular attributes using pseudo-amino acid composition. Proteins: Struct. Funct. Genet. 2001, 43:246-255.
    • (2001) Proteins: Struct. Funct. Genet. , vol.43 , pp. 246-255
    • Chou, K.C.1
  • 19
    • 0035874091 scopus 로고    scopus 로고
    • Prediction of protein cellular attributes using pseudo-amino acid composition
    • Chou K.C. Prediction of protein cellular attributes using pseudo-amino acid composition. Proteins 2001, 43:246-255.
    • (2001) Proteins , vol.43 , pp. 246-255
    • Chou, K.C.1
  • 20
    • 12744279642 scopus 로고    scopus 로고
    • Using amphiphilic pseudo amino acid composition to predict enzyme subfamily classes
    • Chou K.C. Using amphiphilic pseudo amino acid composition to predict enzyme subfamily classes. Bioinformatics 2005, 21:10-19.
    • (2005) Bioinformatics , vol.21 , pp. 10-19
    • Chou, K.C.1
  • 21
    • 79951518208 scopus 로고    scopus 로고
    • Some remarks on protein attribute prediction and pseudo amino acid composition (50th Anniversary Year Review)
    • Chou K.C. Some remarks on protein attribute prediction and pseudo amino acid composition (50th Anniversary Year Review). J. Theor. Biol. 2011, 273:236-247.
    • (2011) J. Theor. Biol. , vol.273 , pp. 236-247
    • Chou, K.C.1
  • 22
    • 3843117638 scopus 로고    scopus 로고
    • Predicting protein structural class by functional domain composition
    • Chou K.C., Cai Y.D. Predicting protein structural class by functional domain composition. Biochem. Biophys. Res. Commun. 2004, 321:1007-1009.
    • (2004) Biochem. Biophys. Res. Commun. , vol.321 , pp. 1007-1009
    • Chou, K.C.1    Cai, Y.D.2
  • 23
    • 77649339280 scopus 로고    scopus 로고
    • Review: recent advances in developing web-servers for predicting protein attributes
    • Chou K.C., Shen H.B. Review: recent advances in developing web-servers for predicting protein attributes. Nat. Sci. 2009, 2:63-92.
    • (2009) Nat. Sci. , vol.2 , pp. 63-92
    • Chou, K.C.1    Shen, H.B.2
  • 24
    • 84855641685 scopus 로고    scopus 로고
    • ILoc-Hum: using accumulation-label scale to predict subcellular locations of human proteins with both single and multiple sites
    • Chou K.C., Wu Z.C., Xiao X. iLoc-Hum: using accumulation-label scale to predict subcellular locations of human proteins with both single and multiple sites. Mol. Biosyst. 2012, 8:629-641.
    • (2012) Mol. Biosyst. , vol.8 , pp. 629-641
    • Chou, K.C.1    Wu, Z.C.2    Xiao, X.3
  • 26
    • 58849136179 scopus 로고    scopus 로고
    • Prediction of the protein structural class by specific peptide frequencies
    • Costantini S., Facchiano A.M. Prediction of the protein structural class by specific peptide frequencies. Biochimie 2009, 91:226-229.
    • (2009) Biochimie , vol.91 , pp. 226-229
    • Costantini, S.1    Facchiano, A.M.2
  • 27
    • 41149143721 scopus 로고    scopus 로고
    • Exploring an alignment free approach for protein classification and structural class prediction
    • Deschavanne P., Tuffery P. Exploring an alignment free approach for protein classification and structural class prediction. Biochimie 2008, 90:615-625.
    • (2008) Biochimie , vol.90 , pp. 615-625
    • Deschavanne, P.1    Tuffery, P.2
  • 28
    • 84870391329 scopus 로고    scopus 로고
    • Identification of mycobacterial membrane proteins and their types using over-represented tripeptide compositions
    • Ding C., Yuan L.F., Guo S.H., Lin H., Chen W. Identification of mycobacterial membrane proteins and their types using over-represented tripeptide compositions. J. Proteomics 2012, 77:321-328.
    • (2012) J. Proteomics , vol.77 , pp. 321-328
    • Ding, C.1    Yuan, L.F.2    Guo, S.H.3    Lin, H.4    Chen, W.5
  • 29
    • 78751550064 scopus 로고    scopus 로고
    • Identify Golgi protein types with modified Mahalanobis discriminant algorithm and pseudo amino acid composition
    • Ding H., Liu L., Guo F.B., Huang J., Lin H. Identify Golgi protein types with modified Mahalanobis discriminant algorithm and pseudo amino acid composition. Protein Pept. Lett. 2011, 18:58-63.
    • (2011) Protein Pept. Lett. , vol.18 , pp. 58-63
    • Ding, H.1    Liu, L.2    Guo, F.B.3    Huang, J.4    Lin, H.5
  • 30
    • 65349165718 scopus 로고    scopus 로고
    • Prediction of cell wall lytic enzymes using Chou's amphiphilic pseudo amino acid composition
    • Ding H., Luo L., Lin H. Prediction of cell wall lytic enzymes using Chou's amphiphilic pseudo amino acid composition. Protein Pept. Lett. 2009, 16:351-355.
    • (2009) Protein Pept. Lett. , vol.16 , pp. 351-355
    • Ding, H.1    Luo, L.2    Lin, H.3
  • 31
    • 84895429516 scopus 로고    scopus 로고
    • PseAAC-General. Fast building various modes of general form of Chou's pseudo-amino acid composition for large-scale protein datasets
    • Du P., Gu S., Jiao Y. PseAAC-General. Fast building various modes of general form of Chou's pseudo-amino acid composition for large-scale protein datasets. Int. J. Mol. Sci. 2014, 15:3495-3509.
    • (2014) Int. J. Mol. Sci. , vol.15 , pp. 3495-3509
    • Du, P.1    Gu, S.2    Jiao, Y.3
  • 32
    • 84859932176 scopus 로고    scopus 로고
    • PseAAC-Builder. A cross-platform stand-alone program for generating various special Chou's pseudo-amino acid compositions
    • Du P., Wang X., Xu C., Gao Y. PseAAC-Builder. A cross-platform stand-alone program for generating various special Chou's pseudo-amino acid compositions. Anal. Biochem. 2012, 425:117-119.
    • (2012) Anal. Biochem. , vol.425 , pp. 117-119
    • Du, P.1    Wang, X.2    Xu, C.3    Gao, Y.4
  • 33
    • 84859635404 scopus 로고    scopus 로고
    • Predict mycobacterial proteins subcellular locations by incorporating pseudo-average chemical shift into the general form of Chou's pseudo amino acid composition
    • Fan G.L., Li Q.Z. Predict mycobacterial proteins subcellular locations by incorporating pseudo-average chemical shift into the general form of Chou's pseudo amino acid composition. J. Theor. Biol. 2012, 304:88-95.
    • (2012) J. Theor. Biol. , vol.304 , pp. 88-95
    • Fan, G.L.1    Li, Q.Z.2
  • 34
    • 84864779292 scopus 로고    scopus 로고
    • Predicting protein submitochondria locations by combining different descriptors into the general form of Chou's pseudo amino acid composition
    • Fan G.L., Li Q.Z. Predicting protein submitochondria locations by combining different descriptors into the general form of Chou's pseudo amino acid composition. Amino Acids 2012, 43:545-555.
    • (2012) Amino Acids , vol.43 , pp. 545-555
    • Fan, G.L.1    Li, Q.Z.2
  • 35
    • 84879708816 scopus 로고    scopus 로고
    • Discriminating bioluminescent proteins by incorporating average chemical shift and evolutionary information into the general form of Chou's pseudo amino acid composition
    • Fan G.L., Li Q.Z. Discriminating bioluminescent proteins by incorporating average chemical shift and evolutionary information into the general form of Chou's pseudo amino acid composition. J. Theor. Biol. 2013, 334:45-51.
    • (2013) J. Theor. Biol. , vol.334 , pp. 45-51
    • Fan, G.L.1    Li, Q.Z.2
  • 36
    • 84880069651 scopus 로고    scopus 로고
    • Predicting acidic and alkaline enzymes by incorporating the average chemical shift and gene ontology informations into the general form of Chou's PseAAC
    • Fan G.L., Li Q.Z. Predicting acidic and alkaline enzymes by incorporating the average chemical shift and gene ontology informations into the general form of Chou's PseAAC. Process Biochem. 2013, 48:1048-1053.
    • (2013) Process Biochem. , vol.48 , pp. 1048-1053
    • Fan, G.L.1    Li, Q.Z.2
  • 37
    • 84878657414 scopus 로고    scopus 로고
    • Naïve Bayes classifier with feature selection to identify phage virion proteins
    • Feng P.M., Ding H., Chen W., Lin H. Naïve Bayes classifier with feature selection to identify phage virion proteins. Comput. Math. Methods Med. 2013, 530696.
    • (2013) Comput. Math. Methods Med. , pp. 530696
    • Feng, P.M.1    Ding, H.2    Chen, W.3    Lin, H.4
  • 38
    • 84884269845 scopus 로고    scopus 로고
    • Identification of antioxidants from sequence information using naïve Bayes
    • Feng P.M., Lin H., Chen W. Identification of antioxidants from sequence information using naïve Bayes. Comput. Math. Methods Med. 2013.
    • (2013) Comput. Math. Methods Med.
    • Feng, P.M.1    Lin, H.2    Chen, W.3
  • 39
    • 59649123088 scopus 로고    scopus 로고
    • Use of fuzzy clustering technique and matrices to classify amino acids and its impact to Chou's pseudo amino acid composition
    • Georgiou D.N., Karakasidis T.E., Nietoc J.J., Torresd A. Use of fuzzy clustering technique and matrices to classify amino acids and its impact to Chou's pseudo amino acid composition. J. Theor. Biol. 2009, 257:17-26.
    • (2009) J. Theor. Biol. , vol.257 , pp. 17-26
    • Georgiou, D.N.1    Karakasidis, T.E.2    Nietoc, J.J.3    Torresd, A.4
  • 40
    • 84896463976 scopus 로고    scopus 로고
    • INuc-PseKNC: a sequence-based predictor for predicting nucleosome positioning in genomes with pseudo k-tuple nucleotide composition
    • Guo S.H., Deng E.Z., Xu L.Q., Ding H., Lin H., Chen W., et al. iNuc-PseKNC: a sequence-based predictor for predicting nucleosome positioning in genomes with pseudo k-tuple nucleotide composition. Bioinformatics 2014, 30(11):1522-1529.
    • (2014) Bioinformatics , vol.30 , Issue.11 , pp. 1522-1529
    • Guo, S.H.1    Deng, E.Z.2    Xu, L.Q.3    Ding, H.4    Lin, H.5    Chen, W.6
  • 41
    • 84858833657 scopus 로고    scopus 로고
    • Discriminating outer membrane proteins with fuzzy k-nearest neighbor algorithms based on the general form of Chou's PseAAC
    • Hayat M., Khan A. Discriminating outer membrane proteins with fuzzy k-nearest neighbor algorithms based on the general form of Chou's PseAAC. Protein Pept. Lett. 2011, 18:411-421.
    • (2011) Protein Pept. Lett. , vol.18 , pp. 411-421
    • Hayat, M.1    Khan, A.2
  • 42
    • 78649756877 scopus 로고    scopus 로고
    • Predicting membrane protein types by fusing composite protein sequence features into pseudo amino acid composition
    • Hayat M., Khan A. Predicting membrane protein types by fusing composite protein sequence features into pseudo amino acid composition. J. Theor. Biol. 2011, 271:10-17.
    • (2011) J. Theor. Biol. , vol.271 , pp. 10-17
    • Hayat, M.1    Khan, A.2
  • 43
    • 84858731996 scopus 로고    scopus 로고
    • Mem-PHybrid. Hybrid features based prediction system for classifying membrane protein types
    • Hayat M., Khan A. Mem-PHybrid. Hybrid features based prediction system for classifying membrane protein types. Anal. Biochem. 2012, 424:35-44.
    • (2012) Anal. Biochem. , vol.424 , pp. 35-44
    • Hayat, M.1    Khan, A.2
  • 44
    • 80054071147 scopus 로고    scopus 로고
    • MemHyb. Predicting membrane protein types by hybridizing SAAC and PSSM
    • Hayat M., Khan A. MemHyb. Predicting membrane protein types by hybridizing SAAC and PSSM. J. Theor. Biol. 2012, 292:93-102.
    • (2012) J. Theor. Biol. , vol.292 , pp. 93-102
    • Hayat, M.1    Khan, A.2
  • 45
    • 84862763732 scopus 로고    scopus 로고
    • Prediction of membrane proteins using split amino acid composition and ensemble classification
    • Hayat M., Khan A., Yeasin M. Prediction of membrane proteins using split amino acid composition and ensemble classification. J. Amino Acids 2012, 42:2447-2460.
    • (2012) J. Amino Acids , vol.42 , pp. 2447-2460
    • Hayat, M.1    Khan, A.2    Yeasin, M.3
  • 46
    • 79952448515 scopus 로고    scopus 로고
    • Prediction of mitochondrial proteins of malaria parasite using bi-profile Bayes feature extraction
    • Jia C., Liu T., Chang A.K., Zhai Y. Prediction of mitochondrial proteins of malaria parasite using bi-profile Bayes feature extraction. Biochimie 2011, 93:778-782.
    • (2011) Biochimie , vol.93 , pp. 778-782
    • Jia, C.1    Liu, T.2    Chang, A.K.3    Zhai, Y.4
  • 47
    • 33747182577 scopus 로고    scopus 로고
    • Classifier ensembles for protein structural class prediction with varying homology
    • Kedarisetti K.D., Kurgan L., Dick S. Classifier ensembles for protein structural class prediction with varying homology. Biochem. Biophys. Res. Commun. 2006, 348.
    • (2006) Biochem. Biophys. Res. Commun. , vol.348
    • Kedarisetti, K.D.1    Kurgan, L.2    Dick, S.3
  • 48
    • 34247094836 scopus 로고    scopus 로고
    • Prediction of protein structural class for the twilight zone sequences
    • Kurgan L., Chen K. Prediction of protein structural class for the twilight zone sequences. Biochem. Biophys. Res. Commun. 2007, 357:453-460.
    • (2007) Biochem. Biophys. Res. Commun. , vol.357 , pp. 453-460
    • Kurgan, L.1    Chen, K.2
  • 49
    • 44349134514 scopus 로고    scopus 로고
    • SCPRED: accurate prediction of protein structural class for sequences of twilight-zone similarity with predicting sequences
    • Kurgan L., Cios K., Chen K. SCPRED: accurate prediction of protein structural class for sequences of twilight-zone similarity with predicting sequences. BMC Bioinformatics 2008, 9:226.
    • (2008) BMC Bioinformatics , vol.9 , pp. 226
    • Kurgan, L.1    Cios, K.2    Chen, K.3
  • 50
    • 33748415440 scopus 로고    scopus 로고
    • Prediction of structural classes for protein sequences and domains - impact of prediction algorithms, sequence representation and homology, and test procedures on accuracy
    • Kurgan L., Homaeian L. Prediction of structural classes for protein sequences and domains - impact of prediction algorithms, sequence representation and homology, and test procedures on accuracy. Pattern Recogn. 2006, 39:2323-2343.
    • (2006) Pattern Recogn. , vol.39 , pp. 2323-2343
    • Kurgan, L.1    Homaeian, L.2
  • 51
    • 78650209947 scopus 로고    scopus 로고
    • Prediction of thermophilic proteins using feature selection technique
    • Lin H., Chen W. Prediction of thermophilic proteins using feature selection technique. J. Microbiol. Methods 2011, 84:67-70.
    • (2011) J. Microbiol. Methods , vol.84 , pp. 67-70
    • Lin, H.1    Chen, W.2
  • 52
    • 84878789801 scopus 로고    scopus 로고
    • Using over-represented tetrapeptides to predict protein submitochondria locations
    • Lin H., Chen W., Yuan L.F., Li Z.Q., Ding H. Using over-represented tetrapeptides to predict protein submitochondria locations. Acta Biotheor. 2013, 61:259-268.
    • (2013) Acta Biotheor. , vol.61 , pp. 259-268
    • Lin, H.1    Chen, W.2    Yuan, L.F.3    Li, Z.Q.4    Ding, H.5
  • 53
    • 84863873149 scopus 로고    scopus 로고
    • The prediction of protein structural class using averaged chemical shifts
    • Lin H., Ding C., Song Q., Yang P., Ding H., Deng K.J., et al. The prediction of protein structural class using averaged chemical shifts. J. Biomol. Struct. Dynam. 2012, 29:1147-1153.
    • (2012) J. Biomol. Struct. Dynam. , vol.29 , pp. 1147-1153
    • Lin, H.1    Ding, C.2    Song, Q.3    Yang, P.4    Ding, H.5    Deng, K.J.6
  • 54
    • 78650178724 scopus 로고    scopus 로고
    • Prediction of subcellular location of mycobacterial protein using feature selection techniques
    • Lin H., Ding H., Guo F.B., Huang J. Prediction of subcellular location of mycobacterial protein using feature selection techniques. Mol. Divers. 2010, 14:667-671.
    • (2010) Mol. Divers. , vol.14 , pp. 667-671
    • Lin, H.1    Ding, H.2    Guo, F.B.3    Huang, J.4
  • 55
    • 34249807035 scopus 로고    scopus 로고
    • Using pseudo amino acid composition to predict protein structural class: approached by incorporating 400 dipeptide components
    • Lin H., Li Q.Z. Using pseudo amino acid composition to predict protein structural class: approached by incorporating 400 dipeptide components. J. Comput. Chem. 2007, 28:1463-1466.
    • (2007) J. Comput. Chem. , vol.28 , pp. 1463-1466
    • Lin, H.1    Li, Q.Z.2
  • 56
    • 70350437815 scopus 로고    scopus 로고
    • Prediction of subcellular localization of apoptosis protein using Chou's pseudo amino acid composition
    • Lin H., Wang H., Ding H., Chen Y.L., Li Q.Z. Prediction of subcellular localization of apoptosis protein using Chou's pseudo amino acid composition. Acta Biotheor. 2009, 57:321-330.
    • (2009) Acta Biotheor. , vol.57 , pp. 321-330
    • Lin, H.1    Wang, H.2    Ding, H.3    Chen, Y.L.4    Li, Q.Z.5
  • 57
    • 84883658706 scopus 로고    scopus 로고
    • Theoretical and experimental biology in one
    • Lin S.X., Lapointe J. Theoretical and experimental biology in one. J. Biomed. Sci. Eng. 2013, 6:435-442.
    • (2013) J. Biomed. Sci. Eng. , vol.6 , pp. 435-442
    • Lin, S.X.1    Lapointe, J.2
  • 58
    • 84892954329 scopus 로고    scopus 로고
    • Combining evolutionary information extracted from frequency profiles with sequence-based kernels for protein remote homology detection
    • Liu B., Zhang D., Xu R., Xu J., Wang X., Chen Q., et al. Combining evolutionary information extracted from frequency profiles with sequence-based kernels for protein remote homology detection. Bioinformatics 2014, 30:472-479.
    • (2014) Bioinformatics , vol.30 , pp. 472-479
    • Liu, B.1    Zhang, D.2    Xu, R.3    Xu, J.4    Wang, X.5    Chen, Q.6
  • 59
    • 77957124553 scopus 로고    scopus 로고
    • Prediction of protein structural class for low-similarity sequences using support vector machine and PSI-BLAST profile
    • Liu T., Zheng X., Wang J. Prediction of protein structural class for low-similarity sequences using support vector machine and PSI-BLAST profile. Biochimie 2010, 92:1330-1334.
    • (2010) Biochimie , vol.92 , pp. 1330-1334
    • Liu, T.1    Zheng, X.2    Wang, J.3
  • 60
    • 0001455222 scopus 로고
    • Statistical basis for the use of 13C a chemical shifts in protein structure determination
    • Luginbuhl P., Szyperski T., Wuthrich K. Statistical basis for the use of 13C a chemical shifts in protein structure determination. J. Magn. Reson. B 1995, 109:229-233.
    • (1995) J. Magn. Reson. B , vol.109 , pp. 229-233
    • Luginbuhl, P.1    Szyperski, T.2    Wuthrich, K.3
  • 61
    • 0036051172 scopus 로고    scopus 로고
    • Prediction of protein structural class by amino acid and polypeptide composition
    • Luo R.Y., Feng Z.P., Liu J.K. Prediction of protein structural class by amino acid and polypeptide composition. Eur. J. Biochem. 2002, 269:4219-4225.
    • (2002) Eur. J. Biochem. , vol.269 , pp. 4219-4225
    • Luo, R.Y.1    Feng, Z.P.2    Liu, J.K.3
  • 62
    • 84894240609 scopus 로고    scopus 로고
    • Prediction of human breast and colon cancers from imbalanced data using nearest neighbor and support vector machines
    • Majid A., Ali S., Iqbal M., Kausar N. Prediction of human breast and colon cancers from imbalanced data using nearest neighbor and support vector machines. Comput. Methods Programs Biomed. 2014, 113:792-808.
    • (2014) Comput. Methods Programs Biomed. , vol.113 , pp. 792-808
    • Majid, A.1    Ali, S.2    Iqbal, M.3    Kausar, N.4
  • 63
    • 0242661071 scopus 로고    scopus 로고
    • Protein structural class identification directly from NMR spectra using averaged chemical shifts
    • Mielke S.P., Krishnan V.V. Protein structural class identification directly from NMR spectra using averaged chemical shifts. Bioinformatics 2003, 19:2054-2064.
    • (2003) Bioinformatics , vol.19 , pp. 2054-2064
    • Mielke, S.P.1    Krishnan, V.V.2
  • 64
    • 75149123557 scopus 로고    scopus 로고
    • Modular prediction of protein structural classes from sequences of twilight-zone identity with predicting sequences
    • Mizianty M.J., Kurgan L. Modular prediction of protein structural classes from sequences of twilight-zone identity with predicting sequences. BMC Bioinformatics 2009, 10:414.
    • (2009) BMC Bioinformatics , vol.10 , pp. 414
    • Mizianty, M.J.1    Kurgan, L.2
  • 65
    • 77958497871 scopus 로고    scopus 로고
    • Prediction of cyclin proteins using Chou's pseudo amino acid composition
    • Mohabatkar H. Prediction of cyclin proteins using Chou's pseudo amino acid composition. Protein Pept. Lett. 2010, 17:1207-1214.
    • (2010) Protein Pept. Lett. , vol.17 , pp. 1207-1214
    • Mohabatkar, H.1
  • 66
    • 79955564229 scopus 로고    scopus 로고
    • Prediction of GABA(A) receptor proteins using the concept of Chou's pseudo-amino acid composition and support vector machine
    • Mohabatkar H., Mohammad Beigi M., Esmaeili A. Prediction of GABA(A) receptor proteins using the concept of Chou's pseudo-amino acid composition and support vector machine. J. Theor. Biol. 2011, 281:18-23.
    • (2011) J. Theor. Biol. , vol.281 , pp. 18-23
    • Mohabatkar, H.1    Mohammad Beigi, M.2    Esmaeili, A.3
  • 67
    • 0022631926 scopus 로고
    • The folding type of a protein is relevant to the amino acid composition
    • Nakashima H., Nishikawa K., Ooi T. The folding type of a protein is relevant to the amino acid composition. J. Biochem. 1986, 99:153-162.
    • (1986) J. Biochem. , vol.99 , pp. 153-162
    • Nakashima, H.1    Nishikawa, K.2    Ooi, T.3
  • 68
    • 43149097851 scopus 로고    scopus 로고
    • Genetic programming for creating Chou's pseudo amino acid based features for submitochondria localization
    • Nanni L., Lumini A. Genetic programming for creating Chou's pseudo amino acid based features for submitochondria localization. Amino Acids 2008, 34:653-660.
    • (2008) Amino Acids , vol.34 , pp. 653-660
    • Nanni, L.1    Lumini, A.2
  • 69
    • 84856475734 scopus 로고    scopus 로고
    • Identifying bacterial virulent proteins by fusing a set of classifiers based on variants of Chou's pseudo amino acid composition and on evolutionary information
    • Nanni L., Lumini A., Gupta D., Garg A. Identifying bacterial virulent proteins by fusing a set of classifiers based on variants of Chou's pseudo amino acid composition and on evolutionary information. IEEE/ACM Trans. Comput. Biol. Bioinform. 2012, 9:467-475.
    • (2012) IEEE/ACM Trans. Comput. Biol. Bioinform. , vol.9 , pp. 467-475
    • Nanni, L.1    Lumini, A.2    Gupta, D.3    Garg, A.4
  • 70
    • 17444397116 scopus 로고    scopus 로고
    • Porter: a new, accurate server for protein secondary structure prediction
    • Pollastri G., McLysaght A. Porter: a new, accurate server for protein secondary structure prediction. Bioinformatics 2005, 21:1719-1720.
    • (2005) Bioinformatics , vol.21 , pp. 1719-1720
    • Pollastri, G.1    McLysaght, A.2
  • 71
    • 66449105264 scopus 로고    scopus 로고
    • Using support vector machines for prediction of protein structural classes based on discrete wavelet transform
    • Qiu J.D., Luo S.H., Huang J.H., Liang R.P. Using support vector machines for prediction of protein structural classes based on discrete wavelet transform. J. Comput. Chem. 2009, 30:1344-1350.
    • (2009) J. Comput. Chem. , vol.30 , pp. 1344-1350
    • Qiu, J.D.1    Luo, S.H.2    Huang, J.H.3    Liang, R.P.4
  • 72
    • 84892958175 scopus 로고    scopus 로고
    • IRSpot-TNCPseAAC: identify recombination spots with trinucleotide composition and pseudo amino acid components
    • Qiu W.R., Xiao X., Chou K.C. iRSpot-TNCPseAAC: identify recombination spots with trinucleotide composition and pseudo amino acid components. Int. J. Mol. Sci. 2014, 15:1746-1766.
    • (2014) Int. J. Mol. Sci. , vol.15 , pp. 1746-1766
    • Qiu, W.R.1    Xiao, X.2    Chou, K.C.3
  • 73
    • 78649324596 scopus 로고    scopus 로고
    • A novel feature representation method based on Chou's pseudo amino acid composition for protein structural class prediction
    • Sahu S.S., Panda G. A novel feature representation method based on Chou's pseudo amino acid composition for protein structural class prediction. Comput. Biol. Chem. 2010, 34:320-327.
    • (2010) Comput. Biol. Chem. , vol.34 , pp. 320-327
    • Sahu, S.S.1    Panda, G.2
  • 74
    • 62849118051 scopus 로고    scopus 로고
    • Computational identification of protein methylation sites through bi-profile Bayes feature extraction
    • Shao J., Xu D., Tsai S.N., Wang Y., Ngai S.M. Computational identification of protein methylation sites through bi-profile Bayes feature extraction. J. PLoS ONE 2009, 4.
    • (2009) J. PLoS ONE , vol.4
    • Shao, J.1    Xu, D.2    Tsai, S.N.3    Wang, Y.4    Ngai, S.M.5
  • 75
    • 22144498433 scopus 로고    scopus 로고
    • Using supervised fuzzy clustering to predict protein structural classes
    • Shen H.B., Yang J., Liu X.J., Chou K.C. Using supervised fuzzy clustering to predict protein structural classes. Biochem. Biophys. Res. Commun. 2005, 334:577-581.
    • (2005) Biochem. Biophys. Res. Commun. , vol.334 , pp. 577-581
    • Shen, H.B.1    Yang, J.2    Liu, X.J.3    Chou, K.C.4
  • 76
    • 0037304366 scopus 로고    scopus 로고
    • An empirical correlation between secondary structure content and averaged chemical shifts in proteins
    • Sibley A., Cosman M., Krishnan V. An empirical correlation between secondary structure content and averaged chemical shifts in proteins. J. Biophys. 2003, 84:1223-1227.
    • (2003) J. Biophys. , vol.84 , pp. 1223-1227
    • Sibley, A.1    Cosman, M.2    Krishnan, V.3
  • 77
    • 0347610773 scopus 로고
    • Empirical correlation between protein backbone conformation and C-alpha and C-beta 13C nuclear magnetic resonance chemical shifts
    • Spera S., Bax A. Empirical correlation between protein backbone conformation and C-alpha and C-beta 13C nuclear magnetic resonance chemical shifts. J. Am. Chem. Soc. 1991, 113:5490-5492.
    • (1991) J. Am. Chem. Soc. , vol.113 , pp. 5490-5492
    • Spera, S.1    Bax, A.2
  • 78
    • 33745093400 scopus 로고    scopus 로고
    • Prediction of protein structural classes using support vector machines
    • Sun X.D., Huang R.B. Prediction of protein structural classes using support vector machines. Amino Acids 2006, 30:469-475.
    • (2006) Amino Acids , vol.30 , pp. 469-475
    • Sun, X.D.1    Huang, R.B.2
  • 79
    • 84855185013 scopus 로고    scopus 로고
    • Protein subcellular localization of fluorescence imagery using spatial and transform domain features
    • Tahir M., Khan A., Majid A. Protein subcellular localization of fluorescence imagery using spatial and transform domain features. Bioinformatics 2012, 28:91-97.
    • (2012) Bioinformatics , vol.28 , pp. 91-97
    • Tahir, M.1    Khan, A.2    Majid, A.3
  • 81
    • 0034141493 scopus 로고    scopus 로고
    • How good is prediction of protein structural class by the component-coupled method
    • Wang Z.X., Yuan Z. How good is prediction of protein structural class by the component-coupled method. Proteins 2000, 38:165-175.
    • (2000) Proteins , vol.38 , pp. 165-175
    • Wang, Z.X.1    Yuan, Z.2
  • 82
    • 0026410969 scopus 로고
    • Relationship between nuclear magnetic resonance chemical shift and protein secondary structure
    • Wishart D., Sykes B., Richards F. Relationship between nuclear magnetic resonance chemical shift and protein secondary structure. J. Mol. Biol. 1991, 222:311-333.
    • (1991) J. Mol. Biol. , vol.222 , pp. 311-333
    • Wishart, D.1    Sykes, B.2    Richards, F.3
  • 83
    • 84887972825 scopus 로고    scopus 로고
    • Recent advances in predicting protein classification and their applications to drug development
    • Xiao X., Lin W.Z., Chou K.C. Recent advances in predicting protein classification and their applications to drug development. Curr. Top. Med. Chem. 2013, 13:1622-1635.
    • (2013) Curr. Top. Med. Chem. , vol.13 , pp. 1622-1635
    • Xiao, X.1    Lin, W.Z.2    Chou, K.C.3
  • 84
    • 84883661549 scopus 로고    scopus 로고
    • ICDI-PseFpt: identify the channel-drug interaction in cellular networking with PseAAC and molecular fingerprints
    • Xiao X., Min J.L., Wang P., Chou K.C. iCDI-PseFpt: identify the channel-drug interaction in cellular networking with PseAAC and molecular fingerprints. J. Theor. Biol. 2013, 337C:71-79.
    • (2013) J. Theor. Biol. , vol.337 C , pp. 71-79
    • Xiao, X.1    Min, J.L.2    Wang, P.3    Chou, K.C.4
  • 85
    • 33644889341 scopus 로고    scopus 로고
    • Using pseudo amino acid composition to predict protein structural classes: approached with complexity measure factor
    • Xiao X., Shao S.H., Huang Z.D., Chou K.C. Using pseudo amino acid composition to predict protein structural classes: approached with complexity measure factor. J. Comput. Chem. 2006, 27:478-482.
    • (2006) J. Comput. Chem. , vol.27 , pp. 478-482
    • Xiao, X.1    Shao, S.H.2    Huang, Z.D.3    Chou, K.C.4
  • 86
    • 84873575437 scopus 로고    scopus 로고
    • ISNO-PseAAC: predict cysteine S-nitrosylation sites in proteins by incorporating position specific amino acid propensity into pseudo amino acid composition
    • Xu Y., Ding J., Wu L.Y., Chou K.C. iSNO-PseAAC: predict cysteine S-nitrosylation sites in proteins by incorporating position specific amino acid propensity into pseudo amino acid composition. PLOS ONE 2013, 8:e55844.
    • (2013) PLOS ONE , vol.8
    • Xu, Y.1    Ding, J.2    Wu, L.Y.3    Chou, K.C.4
  • 87
    • 76649141763 scopus 로고    scopus 로고
    • Prediction of protein structural classes for low-homology sequences based on predicted secondary structure
    • Yang J.Y., Peng Z.L., Chen X. Prediction of protein structural classes for low-homology sequences based on predicted secondary structure. BMC Bioinformatics 2010, 9:11.
    • (2010) BMC Bioinformatics , vol.9 , pp. 11
    • Yang, J.Y.1    Peng, Z.L.2    Chen, X.3
  • 88
    • 62549159517 scopus 로고    scopus 로고
    • Prediction of protein structural classes by recurrence quantification analysis based on chaos game representation
    • Yang J.Y., Peng Z.L., Yu Z.G., Zhang R.J., Anh V., Wang D.S. Prediction of protein structural classes by recurrence quantification analysis based on chaos game representation. J. Theor. Biol. 2009, 257:618-626.
    • (2009) J. Theor. Biol. , vol.257 , pp. 618-626
    • Yang, J.Y.1    Peng, Z.L.2    Yu, Z.G.3    Zhang, R.J.4    Anh, V.5    Wang, D.S.6
  • 89
    • 84876673548 scopus 로고    scopus 로고
    • Learning protein multi-view features in complex space
    • Yu D.J., Hu J., Wu X.W., Shen H.B., Chen J., Tang Z.M., et al. Learning protein multi-view features in complex space. Amino Acids 2013, 44:1365-1379.
    • (2013) Amino Acids , vol.44 , pp. 1365-1379
    • Yu, D.J.1    Hu, J.2    Wu, X.W.3    Shen, H.B.4    Chen, J.5    Tang, Z.M.6
  • 90
    • 84872709647 scopus 로고    scopus 로고
    • Prediction of the types of ion channel-targeted conotoxins based on radial basis function network
    • Yuan L.F., Ding C., Guo S.H., Ding H., Chen W., Lin H. Prediction of the types of ion channel-targeted conotoxins based on radial basis function network. Toxicol. In Vitro 2013, 27:852-856.
    • (2013) Toxicol. In Vitro , vol.27 , pp. 852-856
    • Yuan, L.F.1    Ding, C.2    Guo, S.H.3    Ding, H.4    Chen, W.5    Lin, H.6
  • 91
    • 79952451732 scopus 로고    scopus 로고
    • High-accuracy prediction of protein structural class for low-similarity sequences based on predicted secondary structure
    • Zhang S., Ding S., Wang T. High-accuracy prediction of protein structural class for low-similarity sequences based on predicted secondary structure. Biochimie 2011, 1-5.
    • (2011) Biochimie , pp. 1-5
    • Zhang, S.1    Ding, S.2    Wang, T.3
  • 92
    • 67650747278 scopus 로고    scopus 로고
    • Use of information discrepancy measure to compare protein secondary structures
    • Zhang S., Yang L., Wang T. Use of information discrepancy measure to compare protein secondary structures. J. Mol. Struct. Theochem. 2009, 909:102-106.
    • (2009) J. Mol. Struct. Theochem. , vol.909 , pp. 102-106
    • Zhang, S.1    Yang, L.2    Wang, T.3
  • 93
    • 36448935288 scopus 로고    scopus 로고
    • Using pseudo amino acid composition and binary-tree support vector machines to predict protein structural classes
    • Zhang T.L., Ding Y.S. Using pseudo amino acid composition and binary-tree support vector machines to predict protein structural classes. Amino Acids 2007, 33:623-629.
    • (2007) Amino Acids , vol.33 , pp. 623-629
    • Zhang, T.L.1    Ding, Y.S.2
  • 94
    • 36348994911 scopus 로고    scopus 로고
    • Prediction protein structural classes with pseudo-amino acid composition: approximate entropy and hydrophobicity pattern
    • Zhang T.L., Ding Y.S., Chou K.C. Prediction protein structural classes with pseudo-amino acid composition: approximate entropy and hydrophobicity pattern. J. Theor. Biol. 2008, 250:186-193.
    • (2008) J. Theor. Biol. , vol.250 , pp. 186-193
    • Zhang, T.L.1    Ding, Y.S.2    Chou, K.C.3
  • 95
    • 77958544970 scopus 로고    scopus 로고
    • Protein secondary structure prediction using NMR chemical shift data
    • Zhao Y., Alipanahi B., Li S.C., Li M. Protein secondary structure prediction using NMR chemical shift data. J. Bioinform. Comput. Biol. 2010, 8:867-884.
    • (2010) J. Bioinform. Comput. Biol. , vol.8 , pp. 867-884
    • Zhao, Y.1    Alipanahi, B.2    Li, S.C.3    Li, M.4
  • 96
    • 54749084166 scopus 로고    scopus 로고
    • An intriguing controversy over protein structural class prediction
    • Zhou G.P. An intriguing controversy over protein structural class prediction. J. Protein Chem. 1998, 17:729-738.
    • (1998) J. Protein Chem. , vol.17 , pp. 729-738
    • Zhou, G.P.1
  • 97
    • 78650099168 scopus 로고    scopus 로고
    • Supersecondary structure prediction using Chou's pseudo amino acid composition
    • Zou D., He Z., He J., Xia Y. Supersecondary structure prediction using Chou's pseudo amino acid composition. J. Comput. Chem. 2011, 32:271-278.
    • (2011) J. Comput. Chem. , vol.32 , pp. 271-278
    • Zou, D.1    He, Z.2    He, J.3    Xia, Y.4


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