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Volumn 7, Issue 2, 2012, Pages

Tangle: Two-Level support vector regression approach for protein backbone torsion angle prediction from primary sequences

Author keywords

[No Author keywords available]

Indexed keywords

SOLVENT; AMINO ACID; PROTEIN;

EID: 84863073485     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0030361     Document Type: Article
Times cited : (35)

References (87)
  • 1
    • 0027291015 scopus 로고
    • Prediction of protein secondary structure at better than 70% accuracy
    • Rost B, Sander C, (1993) Prediction of protein secondary structure at better than 70% accuracy. J Mol Biol 232: 584-599.
    • (1993) J Mol Biol , vol.232 , pp. 584-599
    • Rost, B.1    Sander, C.2
  • 2
    • 0027169638 scopus 로고
    • Improved prediction of protein secondary structure by use of sequence profiles and neural networks
    • Rost B, Sander C, (1993) Improved prediction of protein secondary structure by use of sequence profiles and neural networks. Proc Natl Acad Sci USA 90: 7558-7562.
    • (1993) Proc Natl Acad Sci USA , vol.90 , pp. 7558-7562
    • Rost, B.1    Sander, C.2
  • 3
    • 34249914807 scopus 로고    scopus 로고
    • Real-SPINE: an integrated system of neural networks for real-value prediction of protein structural properties
    • Dor O, Zhou Y, (2007) Real-SPINE: an integrated system of neural networks for real-value prediction of protein structural properties. Proteins 68: 76-81.
    • (2007) Proteins , vol.68 , pp. 76-81
    • Dor, O.1    Zhou, Y.2
  • 4
    • 0037103004 scopus 로고    scopus 로고
    • Prediction of protein solvent accessibility using support vector machines
    • Yuan Z, Burrage K, Mattick JS, (2002) Prediction of protein solvent accessibility using support vector machines. Proteins 48: 566-570.
    • (2002) Proteins , vol.48 , pp. 566-570
    • Yuan, Z.1    Burrage, K.2    Mattick, J.S.3
  • 5
    • 27644490770 scopus 로고    scopus 로고
    • Better prediction of protein contact number using a support vector regression analysis of amino acid sequence
    • Yuan Z, (2005) Better prediction of protein contact number using a support vector regression analysis of amino acid sequence. BMC Bioinformatics 6: 248.
    • (2005) BMC Bioinformatics , vol.6 , pp. 248
    • Yuan, Z.1
  • 6
    • 46249133956 scopus 로고    scopus 로고
    • HSEpred: predict half-sphere exposure from protein sequences
    • Song J, Tan H, Takemoto K, Akutsu T, (2008) HSEpred: predict half-sphere exposure from protein sequences. Bioinformatics 24: 1489-1497.
    • (2008) Bioinformatics , vol.24 , pp. 1489-1497
    • Song, J.1    Tan, H.2    Takemoto, K.3    Akutsu, T.4
  • 7
    • 33750378680 scopus 로고    scopus 로고
    • Predicting residue-wise contact orders in proteins by support vector regression
    • Song J, Burrage K, (2006) Predicting residue-wise contact orders in proteins by support vector regression. BMC Bioinformatics 7: 425.
    • (2006) BMC Bioinformatics , vol.7 , pp. 425
    • Song, J.1    Burrage, K.2
  • 8
    • 70349392341 scopus 로고    scopus 로고
    • Prodepth: predict residue depth by support vector regression approach from protein sequences only
    • Song J, Tan H, Mahmood K, Law RH, Buckle AM, et al. (2009) Prodepth: predict residue depth by support vector regression approach from protein sequences only. PLoS ONE 4: e7072.
    • (2009) PLoS ONE , vol.4
    • Song, J.1    Tan, H.2    Mahmood, K.3    Law, R.H.4    Buckle, A.M.5
  • 9
    • 61449123967 scopus 로고    scopus 로고
    • Improving the prediction accuracy of residue solvent accessibility and real-value backbone torsion angles of proteins by guided-learning through a two-layer neural network
    • Faraggi E, Xue B, Zhou Y, (2009) Improving the prediction accuracy of residue solvent accessibility and real-value backbone torsion angles of proteins by guided-learning through a two-layer neural network. Proteins 74: 847-856.
    • (2009) Proteins , vol.74 , pp. 847-856
    • Faraggi, E.1    Xue, B.2    Zhou, Y.3
  • 10
    • 70350738241 scopus 로고    scopus 로고
    • Predicting continuous local structure and the effect of its substitution for secondary structure in fragment-free protein structure prediction
    • Faraggi E, Yang Y, Zhang S, Zhou Y, (2009) Predicting continuous local structure and the effect of its substitution for secondary structure in fragment-free protein structure prediction. Structure 17: 1515-1527.
    • (2009) Structure , vol.17 , pp. 1515-1527
    • Faraggi, E.1    Yang, Y.2    Zhang, S.3    Zhou, Y.4
  • 11
    • 54849412811 scopus 로고    scopus 로고
    • ANGLOR: a composite machine-learning algorithm for protein backbone torsion angle prediction
    • Wu S, Zhang Y, (2008) ANGLOR: a composite machine-learning algorithm for protein backbone torsion angle prediction. PLoS One 3: e3400.
    • (2008) PLoS One , vol.3
    • Wu, S.1    Zhang, Y.2
  • 12
    • 44949201613 scopus 로고    scopus 로고
    • Real-value prediction of backbone torsion angles
    • Xue B, Dor O, Faraggi E, Zhou Y, (2008) Real-value prediction of backbone torsion angles. Proteins 72: 427-433.
    • (2008) Proteins , vol.72 , pp. 427-433
    • Xue, B.1    Dor, O.2    Faraggi, E.3    Zhou, Y.4
  • 13
    • 80052204561 scopus 로고    scopus 로고
    • Structural Protein Descriptors in 1-Dimension and their Sequence-Based Predictions
    • Kurgan L, Disfani FM, (2011) Structural Protein Descriptors in 1-Dimension and their Sequence-Based Predictions. Curr Protein Pept Sci 12: 470-489.
    • (2011) Curr Protein Pept Sci , vol.12 , pp. 470-489
    • Kurgan, L.1    Disfani, F.M.2
  • 14
    • 0035782925 scopus 로고    scopus 로고
    • Review: protein secondary structure prediction continues to rise
    • Rost B, (2001) Review: protein secondary structure prediction continues to rise. J Struct Biol 134: 204-218.
    • (2001) J Struct Biol , vol.134 , pp. 204-218
    • Rost, B.1
  • 15
    • 33847073796 scopus 로고    scopus 로고
    • Achieving 80% ten-fold cross-validated accuracy for secondary structure prediction by large-scale training
    • Dor O, Zhou Y, (2007) Achieving 80% ten-fold cross-validated accuracy for secondary structure prediction by large-scale training. Proteins 66: 838-845.
    • (2007) Proteins , vol.66 , pp. 838-845
    • Dor, O.1    Zhou, Y.2
  • 16
    • 80052202875 scopus 로고    scopus 로고
    • Critical assessment of high-throughput standalone methods for secondary structure prediction
    • Zhang H, Zhang T, Chen K, Kedarisetti KD, Mizianty MJ, et al. (2011) Critical assessment of high-throughput standalone methods for secondary structure prediction. Brief Bioinform 12: 672-688.
    • (2011) Brief Bioinform , vol.12 , pp. 672-688
    • Zhang, H.1    Zhang, T.2    Chen, K.3    Kedarisetti, K.D.4    Mizianty, M.J.5
  • 17
    • 17844373552 scopus 로고    scopus 로고
    • Protein secondary structure prediction with dihedral angles
    • Wood MJ, Hirst JD, (2005) Protein secondary structure prediction with dihedral angles. Proteins 59: 476-481.
    • (2005) Proteins , vol.59 , pp. 476-481
    • Wood, M.J.1    Hirst, J.D.2
  • 18
    • 77955078003 scopus 로고    scopus 로고
    • Predicting beta-turns and their types using predicted backbone dihedral angles and secondary structures
    • Kountouris P, Hirst JD, (2010) Predicting beta-turns and their types using predicted backbone dihedral angles and secondary structures. BMC Bioinformatics 11: 407.
    • (2010) BMC Bioinformatics , vol.11 , pp. 407
    • Kountouris, P.1    Hirst, J.D.2
  • 19
    • 0037133641 scopus 로고    scopus 로고
    • Fold prediction of helical proteins using torsion angle dynamics and predicted restraints
    • Zhang C, Hou J, Kim SH, (2002) Fold prediction of helical proteins using torsion angle dynamics and predicted restraints. Proc Natl Acad Sci USA 99: 3581-3585.
    • (2002) Proc Natl Acad Sci USA , vol.99 , pp. 3581-3585
    • Zhang, C.1    Hou, J.2    Kim, S.H.3
  • 20
    • 48449085801 scopus 로고    scopus 로고
    • SP5: improving protein fold recognition by using torsion angle profiles and profile-based gap penalty model
    • Zhang W, Liu S, Zhou Y, (2008) SP5: improving protein fold recognition by using torsion angle profiles and profile-based gap penalty model. PLoS ONE 3: e2325.
    • (2008) PLoS ONE , vol.3
    • Zhang, W.1    Liu, S.2    Zhou, Y.3
  • 21
    • 46449123146 scopus 로고    scopus 로고
    • MUSTER: Improving protein sequence profile-profile alignments by using multiple sources of structure information
    • Wu S, Zhang Y, (2008) MUSTER: Improving protein sequence profile-profile alignments by using multiple sources of structure information. Proteins 72: 547-556.
    • (2008) Proteins , vol.72 , pp. 547-556
    • Wu, S.1    Zhang, Y.2
  • 22
    • 32544461476 scopus 로고    scopus 로고
    • Improved pairwise alignments of proteins in the Twilight Zone using local structure predictions
    • Huang YM, Bystroff C, (2006) Improved pairwise alignments of proteins in the Twilight Zone using local structure predictions. Bioinformatics 22: 413-422.
    • (2006) Bioinformatics , vol.22 , pp. 413-422
    • Huang, Y.M.1    Bystroff, C.2
  • 23
    • 37049039413 scopus 로고    scopus 로고
    • TALI: local alignment of protein structures using backbone torsion angles
    • Miao X, Waddell PJ, Valafar H, (2008) TALI: local alignment of protein structures using backbone torsion angles. J Bioinform Comput Biol 6: 163-181.
    • (2008) J Bioinform Comput Biol , vol.6 , pp. 163-181
    • Miao, X.1    Waddell, P.J.2    Valafar, H.3
  • 24
    • 3543101355 scopus 로고    scopus 로고
    • Protein backbone angle prediction with machine learning approaches
    • Kuang R, Leslie CS, Yang AS, (2004) Protein backbone angle prediction with machine learning approaches. Bioinformatics 20: 1612-1621.
    • (2004) Bioinformatics , vol.20 , pp. 1612-1621
    • Kuang, R.1    Leslie, C.S.2    Yang, A.S.3
  • 26
    • 0026009212 scopus 로고
    • Prediction of protein backbone conformation based on seven structure assignments: Influence of local interactions
    • Rooman MJ, Kocher JP, Wodak SJ, (1991) Prediction of protein backbone conformation based on seven structure assignments: Influence of local interactions. J Mol Biol 221: 961-979.
    • (1991) J Mol Biol , vol.221 , pp. 961-979
    • Rooman, M.J.1    Kocher, J.P.2    Wodak, S.J.3
  • 27
    • 0027407722 scopus 로고
    • Estimation and use of protein backbone angle probabilities
    • Kang HS, Kurochkina NA, Lee B, (1993) Estimation and use of protein backbone angle probabilities. J Mol Biol 229: 448-460.
    • (1993) J Mol Biol , vol.229 , pp. 448-460
    • Kang, H.S.1    Kurochkina, N.A.2    Lee, B.3
  • 28
    • 0034604368 scopus 로고    scopus 로고
    • HMMSTR: a hidden Markov model for local sequence-structure correlations in proteins
    • Bystroff C, Thorsson V, Baker D, (2000) HMMSTR: a hidden Markov model for local sequence-structure correlations in proteins. J Mol Biol 301: 173-190.
    • (2000) J Mol Biol , vol.301 , pp. 173-190
    • Bystroff, C.1    Thorsson, V.2    Baker, D.3
  • 29
    • 0034669774 scopus 로고    scopus 로고
    • Bayesian probabilistic approach for predicting backbone structures in terms of protein blocks
    • de Brevern AG, Etchebest C, Hazout S, (2000) Bayesian probabilistic approach for predicting backbone structures in terms of protein blocks. Proteins 41: 271-287.
    • (2000) Proteins , vol.41 , pp. 271-287
    • de Brevern, A.G.1    Etchebest, C.2    Hazout, S.3
  • 30
    • 0038278386 scopus 로고    scopus 로고
    • Hidden Markov models that use predicted local structure for fold recognition: alphabets of backbone geometry
    • Karchin R, Cline M, Mandel-Gutfreund Y, Karplus K, (2003) Hidden Markov models that use predicted local structure for fold recognition: alphabets of backbone geometry. Proteins 51: 504-514.
    • (2003) Proteins , vol.51 , pp. 504-514
    • Karchin, R.1    Cline, M.2    Mandel-Gutfreund, Y.3    Karplus, K.4
  • 31
    • 39049179145 scopus 로고    scopus 로고
    • Protein structural motif prediction in multidimensional phi-psi space leads to improved secondary structure prediction
    • Mooney C, Vullo A, Pollastri G, (2006) Protein structural motif prediction in multidimensional phi-psi space leads to improved secondary structure prediction. J Comput Biol 13: 1489-1502.
    • (2006) J Comput Biol , vol.13 , pp. 1489-1502
    • Mooney, C.1    Vullo, A.2    Pollastri, G.3
  • 32
    • 33845366830 scopus 로고    scopus 로고
    • Support vector machines for prediction of dihedral angle regions
    • Zimmermann O, Hansmann UH, (2006) Support vector machines for prediction of dihedral angle regions. Bioinformatics 22: 3009-3015.
    • (2006) Bioinformatics , vol.22 , pp. 3009-3015
    • Zimmermann, O.1    Hansmann, U.H.2
  • 33
    • 70450252107 scopus 로고    scopus 로고
    • Predicting dihedral angle probability distributions for protein coil residues from primary sequence using neural networks
    • Helles G, Fonseca R, (2009) Predicting dihedral angle probability distributions for protein coil residues from primary sequence using neural networks. BMC Bioinformatics 10: 338.
    • (2009) BMC Bioinformatics , vol.10 , pp. 338
    • Helles, G.1    Fonseca, R.2
  • 34
    • 75649083757 scopus 로고    scopus 로고
    • Prediction of backbone dihedral angles and protein secondary structure using support vector machines
    • Kountouris P, Hirst JD, (2009) Prediction of backbone dihedral angles and protein secondary structure using support vector machines. BMC Bioinformatics 10: 437.
    • (2009) BMC Bioinformatics , vol.10 , pp. 437
    • Kountouris, P.1    Hirst, J.D.2
  • 35
    • 17844373552 scopus 로고    scopus 로고
    • Protein secondary structure prediction with dihedral angles
    • Wood MJ, Hirst JD, (2005) Protein secondary structure prediction with dihedral angles. Proteins 59: 476-481.
    • (2005) Proteins , vol.59 , pp. 476-481
    • Wood, M.J.1    Hirst, J.D.2
  • 36
    • 0030801002 scopus 로고    scopus 로고
    • Gapped BLAST and PSI-BLAST: a new generation of protein database search programs
    • Altschul SF, Madden TL, Schaffer AA, Zhang J, Zhang Z, et al. (1997) Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res 25: 3389-3402.
    • (1997) Nucleic Acids Res , vol.25 , pp. 3389-3402
    • Altschul, S.F.1    Madden, T.L.2    Schaffer, A.A.3    Zhang, J.4    Zhang, Z.5
  • 37
    • 33747831881 scopus 로고    scopus 로고
    • PREDITOR: a web server for predicting protein torsion angle restraints
    • Web Server issue
    • Berjanskii MV, Neal S, Wishart DS, (2006) PREDITOR: a web server for predicting protein torsion angle restraints. Nucleic Acids Res 34 (Web Server issue): W63-69.
    • (2006) Nucleic Acids Res , vol.34
    • Berjanskii, M.V.1    Neal, S.2    Wishart, D.S.3
  • 38
    • 78349301599 scopus 로고    scopus 로고
    • Fluctuations of backbone torsion angles obtained from NMR-determined structures and their prediction
    • Zhang T, Faraggi E, Zhou Y, (2010) Fluctuations of backbone torsion angles obtained from NMR-determined structures and their prediction. Proteins 78: 3353-3362.
    • (2010) Proteins , vol.78 , pp. 3353-3362
    • Zhang, T.1    Faraggi, E.2    Zhou, Y.3
  • 39
    • 77958502965 scopus 로고    scopus 로고
    • Integrated prediction of one-dimensional structural features and their relationships with conformational flexibility in helical membrane proteins
    • Ahmad S, Singh YH, Paudel Y, Mori T, Sugita Y, et al. (2010) Integrated prediction of one-dimensional structural features and their relationships with conformational flexibility in helical membrane proteins. BMC Bioinformatics 11: 533.
    • (2010) BMC Bioinformatics , vol.11 , pp. 533
    • Ahmad, S.1    Singh, Y.H.2    Paudel, Y.3    Mori, T.4    Sugita, Y.5
  • 40
    • 0020997912 scopus 로고
    • Dictionary of protein secondary structure: pattern recognition of hydrogen-bonded and geometrical features
    • Kabsch W, Sander C, (1983) Dictionary of protein secondary structure: pattern recognition of hydrogen-bonded and geometrical features. Biopolymers 22: 2577-2637.
    • (1983) Biopolymers , vol.22 , pp. 2577-2637
    • Kabsch, W.1    Sander, C.2
  • 43
    • 6344258643 scopus 로고    scopus 로고
    • Prediction of protein accessible surface areas by support vector regression
    • Yuan Z, Huang B, (2004) Prediction of protein accessible surface areas by support vector regression. Proteins 57: 558-564.
    • (2004) Proteins , vol.57 , pp. 558-564
    • Yuan, Z.1    Huang, B.2
  • 44
    • 33748468024 scopus 로고    scopus 로고
    • Potential for assessing quality of protein structure based on contact number prediction
    • Ishida T, Nakamura S, Shimizu K, (2006) Potential for assessing quality of protein structure based on contact number prediction. Proteins 64: 940-947.
    • (2006) Proteins , vol.64 , pp. 940-947
    • Ishida, T.1    Nakamura, S.2    Shimizu, K.3
  • 45
    • 13944277320 scopus 로고    scopus 로고
    • Prediction of protein B-factor profiles
    • Yuan Z, Bailey TL, Teasdale RD, (2005) Prediction of protein B-factor profiles. Proteins 58: 905-912.
    • (2005) Proteins , vol.58 , pp. 905-912
    • Yuan, Z.1    Bailey, T.L.2    Teasdale, R.D.3
  • 46
    • 36549021546 scopus 로고    scopus 로고
    • Predicting disulfide connectivity from protein sequence using multiple sequence feature vectors and secondary structure
    • Song J, Yuan Z, Tan H, Huber T, Burrage K, (2007) Predicting disulfide connectivity from protein sequence using multiple sequence feature vectors and secondary structure. Bioinformatics 23: 3147-3154.
    • (2007) Bioinformatics , vol.23 , pp. 3147-3154
    • Song, J.1    Yuan, Z.2    Tan, H.3    Huber, T.4    Burrage, K.5
  • 47
    • 77951972791 scopus 로고    scopus 로고
    • Cascleave: towards more accurate prediction of caspase substrate cleavage sites
    • Song J, Tan H, Shen H, Mahmood K, Boyd SE, et al. (2010) Cascleave: towards more accurate prediction of caspase substrate cleavage sites. Bioinformatics 26: 752-760.
    • (2010) Bioinformatics , vol.26 , pp. 752-760
    • Song, J.1    Tan, H.2    Shen, H.3    Mahmood, K.4    Boyd, S.E.5
  • 48
    • 25444464110 scopus 로고    scopus 로고
    • Correlation and prediction of gene expression level from amino acid and dipeptide composition of its protein
    • Raghava GP, Han JH, (2005) Correlation and prediction of gene expression level from amino acid and dipeptide composition of its protein. BMC Bioinformatics 6: 59.
    • (2005) BMC Bioinformatics , vol.6 , pp. 59
    • Raghava, G.P.1    Han, J.H.2
  • 49
    • 33645037239 scopus 로고    scopus 로고
    • Missing value estimation for DNA microarray gene expression data by Support Vector Regression imputation and orthogonal coding scheme
    • Wang X, Li A, Jiang Z, Feng H, (2006) Missing value estimation for DNA microarray gene expression data by Support Vector Regression imputation and orthogonal coding scheme. BMC Bioinformatics 7: 32.
    • (2006) BMC Bioinformatics , vol.7 , pp. 32
    • Wang, X.1    Li, A.2    Jiang, Z.3    Feng, H.4
  • 50
    • 33746352651 scopus 로고    scopus 로고
    • Quantitative prediction of mouse class I MHC peptide binding affinity using support vector machine regression (SVR) models
    • Liu W, Meng X, Xu Q, Flower DR, Li T, (2006) Quantitative prediction of mouse class I MHC peptide binding affinity using support vector machine regression (SVR) models. BMC Bioinformatics 7: 182.
    • (2006) BMC Bioinformatics , vol.7 , pp. 182
    • Liu, W.1    Meng, X.2    Xu, Q.3    Flower, D.R.4    Li, T.5
  • 51
    • 67549113661 scopus 로고    scopus 로고
    • A framework for multiple kernel support vector regression and its applications to siRNA efficacy prediction
    • Qiu S, Lane T, (2009) A framework for multiple kernel support vector regression and its applications to siRNA efficacy prediction. IEEE/ACM Trans Comput Biol Bioinform 6: 190-199.
    • (2009) IEEE/ACM Trans Comput Biol Bioinform , vol.6 , pp. 190-199
    • Qiu, S.1    Lane, T.2
  • 52
    • 65249163979 scopus 로고    scopus 로고
    • A new regularized least squares support vector regression for gene selection
    • Chen PC, Huang SY, Chen WJ, Hsiao CK, (2009) A new regularized least squares support vector regression for gene selection. BMC Bioinformatics 10: 44.
    • (2009) BMC Bioinformatics , vol.10 , pp. 44
    • Chen, P.C.1    Huang, S.Y.2    Chen, W.J.3    Hsiao, C.K.4
  • 53
    • 77956938868 scopus 로고    scopus 로고
    • DomSVR: domain boundary prediction with support vector regression from sequence information alone
    • Chen P, Liu C, Burge L, Li J, Mohammad M, et al. (2010) DomSVR: domain boundary prediction with support vector regression from sequence information alone. Amino Acids 39: 713-726.
    • (2010) Amino Acids , vol.39 , pp. 713-726
    • Chen, P.1    Liu, C.2    Burge, L.3    Li, J.4    Mohammad, M.5
  • 54
    • 77954543849 scopus 로고    scopus 로고
    • EPSVR and EPMeta: prediction of antigenic epitopes using support vector regression and multiple server results
    • Liang S, Zheng D, Standley DM, Yao B, Zacharias M, et al. (2010) EPSVR and EPMeta: prediction of antigenic epitopes using support vector regression and multiple server results. BMC Bioinformatics 11: 381.
    • (2010) BMC Bioinformatics , vol.11 , pp. 381
    • Liang, S.1    Zheng, D.2    Standley, D.M.3    Yao, B.4    Zacharias, M.5
  • 55
    • 33646036734 scopus 로고    scopus 로고
    • Two-stage support vector regression approach for predicting accessible surface areas of amino acids
    • Nguyen MN, Rajapakse JC, (2006) Two-stage support vector regression approach for predicting accessible surface areas of amino acids. Proteins 63: 542-550.
    • (2006) Proteins , vol.63 , pp. 542-550
    • Nguyen, M.N.1    Rajapakse, J.C.2
  • 56
    • 14644440766 scopus 로고    scopus 로고
    • Prediction of protein relative solvent accessibility with a two-stage SVM approach
    • Nguyen MN, Rajapakse JC, (2005) Prediction of protein relative solvent accessibility with a two-stage SVM approach. Proteins 59: 30-37.
    • (2005) Proteins , vol.59 , pp. 30-37
    • Nguyen, M.N.1    Rajapakse, J.C.2
  • 57
    • 51349140594 scopus 로고    scopus 로고
    • Sequence based prediction of relative solvent accessibility using two-stage support vector regression with confidence values
    • Chen K, Kurgan M, Kurgan L, (2008) Sequence based prediction of relative solvent accessibility using two-stage support vector regression with confidence values. J Biomed Sci Eng 1: 1-9.
    • (2008) J Biomed Sci Eng , vol.1 , pp. 1-9
    • Chen, K.1    Kurgan, M.2    Kurgan, L.3
  • 58
    • 73449096798 scopus 로고    scopus 로고
    • Robust prediction of B-factor profile from sequence using two-stage SVR based on random forest feature selection
    • Pan XY, Shen HB, (2009) Robust prediction of B-factor profile from sequence using two-stage SVR based on random forest feature selection. Protein Pept Lett 16: 1447-1454.
    • (2009) Protein Pept Lett , vol.16 , pp. 1447-1454
    • Pan, X.Y.1    Shen, H.B.2
  • 59
    • 77953898349 scopus 로고    scopus 로고
    • Multilevel support vector regression analysis to identify condition-specific regulatory networks
    • Chen L, Xuan J, Riggins RB, Wang Y, Hoffman EP, et al. (2010) Multilevel support vector regression analysis to identify condition-specific regulatory networks. Bioinformatics 26: 1416-1422.
    • (2010) Bioinformatics , vol.26 , pp. 1416-1422
    • Chen, L.1    Xuan, J.2    Riggins, R.B.3    Wang, Y.4    Hoffman, E.P.5
  • 60
    • 0033578684 scopus 로고    scopus 로고
    • Protein secondary structure prediction based on position-specific scoring matrices
    • Jones DT, (1999) Protein secondary structure prediction based on position-specific scoring matrices. J Mol Biol 292: 195-202.
    • (1999) J Mol Biol , vol.292 , pp. 195-202
    • Jones, D.T.1
  • 62
    • 1542358787 scopus 로고    scopus 로고
    • Prediction and functional analysis of native disorder in proteins from the three kingdoms of life
    • Ward JJ, Sodhi JS, McGuffin LJ, Buxton BF, Jones DT, (2004) Prediction and functional analysis of native disorder in proteins from the three kingdoms of life. J Mol Biol 337: 635-645.
    • (2004) J Mol Biol , vol.337 , pp. 635-645
    • Ward, J.J.1    Sodhi, J.S.2    McGuffin, L.J.3    Buxton, B.F.4    Jones, D.T.5
  • 63
    • 25444524842 scopus 로고    scopus 로고
    • PSSM-based prediction of DNA binding sites in proteins
    • Ahmad S, Sarai A, (2005) PSSM-based prediction of DNA binding sites in proteins. BMC Bioinformatics 6: 33.
    • (2005) BMC Bioinformatics , vol.6 , pp. 33
    • Ahmad, S.1    Sarai, A.2
  • 64
    • 23144461988 scopus 로고    scopus 로고
    • LOCSVMPSI: a web server for subcellular localization of eukaryotic proteins using SVM and profile of PSI-BLAST
    • Jul 1, Web Server issue
    • Xie D, Li A, Wang M, Fan Z, Feng H, (2005) LOCSVMPSI: a web server for subcellular localization of eukaryotic proteins using SVM and profile of PSI-BLAST. Nucleic Acids Res Jul 1;33 (Web Server issue): W105-110.
    • (2005) Nucleic Acids Res , vol.33
    • Xie, D.1    Li, A.2    Wang, M.3    Fan, Z.4    Feng, H.5
  • 65
    • 33646195908 scopus 로고    scopus 로고
    • Prediction of cis/trans isomerization in proteins using PSI-BLAST profiles and secondary structure information
    • Mar 9
    • Song J, Burrage K, Yuan Z, Huber T, (2006) Prediction of cis/trans isomerization in proteins using PSI-BLAST profiles and secondary structure information. BMC Bioinformatics Mar 9;7: 124.
    • (2006) BMC Bioinformatics , vol.7 , pp. 124
    • Song, J.1    Burrage, K.2    Yuan, Z.3    Huber, T.4
  • 66
    • 34547852238 scopus 로고    scopus 로고
    • Prediction of DNA-binding residues from sequence
    • Ofran Y, Mysore V, Rost B, (2007) Prediction of DNA-binding residues from sequence. Bioinformatics 23: i347-i353.
    • (2007) Bioinformatics , vol.23
    • Ofran, Y.1    Mysore, V.2    Rost, B.3
  • 67
    • 34547573955 scopus 로고    scopus 로고
    • Protein-Protein Interaction Hotspots Carved into Sequences
    • Ofran Y, Rost B, (2007) Protein-Protein Interaction Hotspots Carved into Sequences. PLoS Comput Biol 3: e119.
    • (2007) PLoS Comput Biol , vol.3
    • Ofran, Y.1    Rost, B.2
  • 68
    • 36448960843 scopus 로고    scopus 로고
    • PFRES: protein fold classification by using evolutionary information and predicted secondary structure
    • Chen K, Kurgan L, (2007) PFRES: protein fold classification by using evolutionary information and predicted secondary structure. Bioinformatics 23: 2843-2850.
    • (2007) Bioinformatics , vol.23 , pp. 2843-2850
    • Chen, K.1    Kurgan, L.2
  • 69
    • 38649127567 scopus 로고    scopus 로고
    • Identification of DNA-binding proteins using support vector machines and evolutionary profiles
    • Kumar M, Gromiha MM, Raghava GP, (2007) Identification of DNA-binding proteins using support vector machines and evolutionary profiles. BMC Bioinformatics 8: 463.
    • (2007) BMC Bioinformatics , vol.8 , pp. 463
    • Kumar, M.1    Gromiha, M.M.2    Raghava, G.P.3
  • 71
    • 53749083563 scopus 로고    scopus 로고
    • Accurate sequence-based prediction of catalytic residues
    • Zhang T, Zhang H, Chen K, Shen S, Ruan J, et al. (2008) Accurate sequence-based prediction of catalytic residues. Bioinformatics 24: 2329-2338.
    • (2008) Bioinformatics , vol.24 , pp. 2329-2338
    • Zhang, T.1    Zhang, H.2    Chen, K.3    Shen, S.4    Ruan, J.5
  • 72
    • 58149284018 scopus 로고    scopus 로고
    • Prediction of beta-turns at over 80% accuracy based on an ensemble of predicted secondary structures and multiple alignments
    • Zheng C, Kurgan L, (2008) Prediction of beta-turns at over 80% accuracy based on an ensemble of predicted secondary structures and multiple alignments. BMC Bioinformatics 9: 430.
    • (2008) BMC Bioinformatics , vol.9 , pp. 430
    • Zheng, C.1    Kurgan, L.2
  • 73
    • 54049091165 scopus 로고    scopus 로고
    • Sequence based residue depth prediction using evolutionary information and predicted secondary structure
    • Zhang H, Zhang T, Chen K, Shen S, Ruan J, et al. (2008) Sequence based residue depth prediction using evolutionary information and predicted secondary structure. BMC Bioinformatics 9: 388.
    • (2008) BMC Bioinformatics , vol.9 , pp. 388
    • Zhang, H.1    Zhang, T.2    Chen, K.3    Shen, S.4    Ruan, J.5
  • 74
    • 42949165918 scopus 로고    scopus 로고
    • Identification of proteins secreted by malaria parasite into erythrocyte using SVM and PSSM profiles
    • Verma R, Tiwari A, Kaur S, Varshney GC, Raghava GP, (2008) Identification of proteins secreted by malaria parasite into erythrocyte using SVM and PSSM profiles. BMC Bioinformatics 9: 201.
    • (2008) BMC Bioinformatics , vol.9 , pp. 201
    • Verma, R.1    Tiwari, A.2    Kaur, S.3    Varshney, G.C.4    Raghava, G.P.5
  • 75
    • 77952971734 scopus 로고    scopus 로고
    • Prediction of GTP interacting residues, dipeptides and tripeptides in a protein from its evolutionary information
    • Chauhan JS, Mishra NK, Raghava GP, (2010) Prediction of GTP interacting residues, dipeptides and tripeptides in a protein from its evolutionary information. BMC Bioinformatics 11: 301.
    • (2010) BMC Bioinformatics , vol.11 , pp. 301
    • Chauhan, J.S.1    Mishra, N.K.2    Raghava, G.P.3
  • 76
    • 78649768576 scopus 로고    scopus 로고
    • Improved identification of outer membrane beta barrel proteins using primary sequence, predicted secondary structure, and evolutionary information
    • Mizianty MJ, Kurgan L, (2011) Improved identification of outer membrane beta barrel proteins using primary sequence, predicted secondary structure, and evolutionary information. Proteins 79: 294-303.
    • (2011) Proteins , vol.79 , pp. 294-303
    • Mizianty, M.J.1    Kurgan, L.2
  • 77
    • 79954443219 scopus 로고    scopus 로고
    • iFC(2): an integrated web-server for improved prediction of protein structural class, fold type, and secondary structure content
    • Chen K, Stach W, Homaeian L, Kurgan L, (2011) iFC(2): an integrated web-server for improved prediction of protein structural class, fold type, and secondary structure content. Amino Acids 40: 963-973.
    • (2011) Amino Acids , vol.40 , pp. 963-973
    • Chen, K.1    Stach, W.2    Homaeian, L.3    Kurgan, L.4
  • 78
    • 34547599318 scopus 로고    scopus 로고
    • Natively unstructured loops differ from other loops
    • Schlessinger A, Liu J, Rost B, (2007) Natively unstructured loops differ from other loops. PLoS Comput Biol 3: e140.
    • (2007) PLoS Comput Biol , vol.3
    • Schlessinger, A.1    Liu, J.2    Rost, B.3
  • 79
    • 84885949386 scopus 로고    scopus 로고
    • Improved disorder prediction by combination of orthogonal approaches
    • Schlessinger A, Punta M, Yachdav G, Kajan L, Rost B, (2009) Improved disorder prediction by combination of orthogonal approaches. PLoS One 4: e4433.
    • (2009) PLoS One , vol.4
    • Schlessinger, A.1    Punta, M.2    Yachdav, G.3    Kajan, L.4    Rost, B.5
  • 80
    • 34548750953 scopus 로고    scopus 로고
    • Natively unstructured regions in proteins identified from contact predictions
    • Schlessinger A, Punta M, Rost B, (2007) Natively unstructured regions in proteins identified from contact predictions. Bioinformatics 23: 2376-2384.
    • (2007) Bioinformatics , vol.23 , pp. 2376-2384
    • Schlessinger, A.1    Punta, M.2    Rost, B.3
  • 81
    • 14644435825 scopus 로고    scopus 로고
    • Intrinsically unstructured proteins and their functions
    • Dyson HJ, Wright PE, (2005) Intrinsically unstructured proteins and their functions. Nat Rev Mol Cell Biol 6: 197-208.
    • (2005) Nat Rev Mol Cell Biol , vol.6 , pp. 197-208
    • Dyson, H.J.1    Wright, P.E.2
  • 82
    • 33748074139 scopus 로고    scopus 로고
    • Intrinsic disorder is a common feature of hub proteins from four eukaryotic interactomes
    • Haynes C, Oldfield CJ, Ji F, Klitgord N, Cusick ME, et al. (2006) Intrinsic disorder is a common feature of hub proteins from four eukaryotic interactomes. PLoS Comput Biol 2: e100.
    • (2006) PLoS Comput Biol , vol.2
    • Haynes, C.1    Oldfield, C.J.2    Ji, F.3    Klitgord, N.4    Cusick, M.E.5
  • 83
    • 57149116929 scopus 로고    scopus 로고
    • Tight regulation of unstructured proteins: from transcript synthesis to protein degradation
    • Gsponer J, Futschik ME, Teichmann SA, Babu MM, (2008) Tight regulation of unstructured proteins: from transcript synthesis to protein degradation. Science 322: 1365-1368.
    • (2008) Science , vol.322 , pp. 1365-1368
    • Gsponer, J.1    Futschik, M.E.2    Teichmann, S.A.3    Babu, M.M.4
  • 84
    • 78650153738 scopus 로고    scopus 로고
    • Musite, a tool for global prediction of general and kinase-specific phosphorylation sites
    • Gao J, Thelen JJ, Dunker AK, Xu D, (2010) Musite, a tool for global prediction of general and kinase-specific phosphorylation sites. Mol Cell Proteomics 9: 2586-2600.
    • (2010) Mol Cell Proteomics , vol.9 , pp. 2586-2600
    • Gao, J.1    Thelen, J.J.2    Dunker, A.K.3    Xu, D.4
  • 85
    • 0033002698 scopus 로고    scopus 로고
    • A molecular mechanism for the phosphorylation-dependent regulation of heterotrimeric G proteins by phosducin
    • Gaudet R, Savage JR, McLaughlin JN, Willardson BM, Sigler PB, (1999) A molecular mechanism for the phosphorylation-dependent regulation of heterotrimeric G proteins by phosducin. Mol Cell 3: 649-660.
    • (1999) Mol Cell , vol.3 , pp. 649-660
    • Gaudet, R.1    Savage, J.R.2    McLaughlin, J.N.3    Willardson, B.M.4    Sigler, P.B.5
  • 86
    • 0030612122 scopus 로고    scopus 로고
    • The structure of enzyme IIAlactose from Lactococcus lactis reveals a new fold and points to possible interactions of a multicomponent system
    • Sliz P, Engelmann R, Hengstenberg W, Pai EF, (1997) The structure of enzyme IIAlactose from Lactococcus lactis reveals a new fold and points to possible interactions of a multicomponent system. Structure 5: 775-788.
    • (1997) Structure , vol.5 , pp. 775-788
    • Sliz, P.1    Engelmann, R.2    Hengstenberg, W.3    Pai, E.F.4


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