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Volumn 13, Issue 14, 2007, Pages 1403-1413

Bio-basis function neural networks in protein data mining

Author keywords

Bio basis function; Bioinformatics; Neural networks; Protein data mining; Systems biology

Indexed keywords

ANTI HUMAN IMMUNODEFICIENCY VIRUS AGENT; ANTIRETROVIRUS AGENT; HUMAN IMMUNODEFICIENCY VIRUS VACCINE; INDINAVIR; PROTEINASE; PROTEINASE INHIBITOR; RNA DIRECTED DNA POLYMERASE INHIBITOR; SAQUINAVIR;

EID: 34249857996     PISSN: 13816128     EISSN: None     Source Type: Journal    
DOI: 10.2174/138161207780765927     Document Type: Review
Times cited : (13)

References (75)
  • 1
    • 0014405092 scopus 로고
    • On the active site of proteases. 3. Mapping the active site of papain; specific peptide inhibitors of papain
    • Schechter I, Berger A. On the active site of proteases. 3. Mapping the active site of papain; specific peptide inhibitors of papain. Biochem Biophys Res Comms 1968; 32: 898-902.
    • (1968) Biochem Biophys Res Comms , vol.32 , pp. 898-902
    • Schechter, I.1    Berger, A.2
  • 2
    • 0033579464 scopus 로고    scopus 로고
    • Sequence and structure based prediction of eukaryotic protein phosphorylation sites
    • Blom N, Gammeltoft S, Brunak S. Sequence and structure based prediction of eukaryotic protein phosphorylation sites. J Mol Biol 1999; 294: 13 51-62.
    • (1999) J Mol Biol , vol.294 , Issue.13 , pp. 51-62
    • Blom, N.1    Gammeltoft, S.2    Brunak, S.3
  • 3
    • 0002172016 scopus 로고
    • The carbohydrates of glycoproteins
    • Ginsburg V, Robins PW Eds, New York, John Wiley & Sons
    • Kobata A. The carbohydrates of glycoproteins. In: Ginsburg V, Robins PW Eds. Biology of carbohydrates. New York, John Wiley & Sons 1984.
    • (1984) Biology of carbohydrates
    • Kobata, A.1
  • 4
    • 0026345896 scopus 로고
    • A cumulative specificity model for protease from human immunodeficiency virus types 1 and 2, inferred from statistical analysis of an extended substrate data base
    • Poorman RA, Tomasselli AG, Heinrikson RL, Kezdy FJ. A cumulative specificity model for protease from human immunodeficiency virus types 1 and 2, inferred from statistical analysis of an extended substrate data base. J Biol Chem 1991; 22: 14554-61.
    • (1991) J Biol Chem , vol.22 , pp. 14554-14561
    • Poorman, R.A.1    Tomasselli, A.G.2    Heinrikson, R.L.3    Kezdy, F.J.4
  • 6
    • 0019034773 scopus 로고
    • Composition and properties of trypsin-like elongation factor Tu
    • Wittinghofer A, Frank R, Leberman R. Composition and properties of trypsin-like elongation factor Tu. Eur J Biochem 1980; 108: 423-31.
    • (1980) Eur J Biochem , vol.108 , pp. 423-431
    • Wittinghofer, A.1    Frank, R.2    Leberman, R.3
  • 7
    • 34249860664 scopus 로고    scopus 로고
    • Quinlan JR. C4.5: Programs for machine learning. Morgan Kaufmann Publishers, San Mateo, California 1988.
    • Quinlan JR. C4.5: Programs for machine learning. Morgan Kaufmann Publishers, San Mateo, California 1988.
  • 10
    • 0141721892 scopus 로고    scopus 로고
    • Mining viral protease data to extract cleavage knowledge
    • Narayanan A, Wu X, Yang ZR. Mining viral protease data to extract cleavage knowledge. Bioinformatics 2002; 18: 5-13.
    • (2002) Bioinformatics , vol.18 , pp. 5-13
    • Narayanan, A.1    Wu, X.2    Yang, Z.R.3
  • 11
    • 0842301301 scopus 로고    scopus 로고
    • Reduced bio basis function neural network for identification of protein phosphorylation sites: Comparison with pattern recognition algorithms
    • Berry E, Dalby A, Yang ZR. Reduced bio basis function neural network for identification of protein phosphorylation sites: Comparison with pattern recognition algorithms. Comput Biol Chem 2004; 28: 75-85.
    • (2004) Comput Biol Chem , vol.28 , pp. 75-85
    • Berry, E.1    Dalby, A.2    Yang, Z.R.3
  • 12
    • 33645021017 scopus 로고    scopus 로고
    • Predict signal peptides using bio-basis function neural networks
    • Sidhu A, Yang ZR. Predict signal peptides using bio-basis function neural networks. Appl Bioinformatics 2006; 5: 13-9.
    • (2006) Appl Bioinformatics , vol.5 , pp. 13-19
    • Sidhu, A.1    Yang, Z.R.2
  • 13
    • 0345293243 scopus 로고    scopus 로고
    • Extracting decision rules from protein sequences using genetic programming methods
    • Yang ZR, Thomson R, Hodgman C, Doyle AK. Extracting decision rules from protein sequences using genetic programming methods. Biosystems 2003; 72: 159-76.
    • (2003) Biosystems , vol.72 , pp. 159-176
    • Yang, Z.R.1    Thomson, R.2    Hodgman, C.3    Doyle, A.K.4
  • 14
    • 12344324769 scopus 로고    scopus 로고
    • Mining HIV protease cleavage data using genetic programming with a sum-product function
    • Yang ZR, Dalby A, Qiu J. Mining HIV protease cleavage data using genetic programming with a sum-product function. Bioinformatics 2004; 20: 3398-405.
    • (2004) Bioinformatics , vol.20 , pp. 3398-3405
    • Yang, Z.R.1    Dalby, A.2    Qiu, J.3
  • 15
    • 0024610919 scopus 로고
    • A tutorial on hidden Markov models and selected applications in speech recognition
    • Rabiner LR. A tutorial on hidden Markov models and selected applications in speech recognition. Proc IEEE 1989; 77: 257-86.
    • (1989) Proc IEEE , vol.77 , pp. 257-286
    • Rabiner, L.R.1
  • 16
    • 0024791227 scopus 로고
    • Prediction of operator-binding protein by discriminant analysis
    • Nakata K, Maizel JV. Prediction of operator-binding protein by discriminant analysis. Gene Anal Tech 1989; 6:111-9.
    • (1989) Gene Anal Tech , vol.6 , pp. 111-119
    • Nakata, K.1    Maizel, J.V.2
  • 17
    • 0001911218 scopus 로고    scopus 로고
    • State-of-the-art in membrane protein prediction
    • Chen CP, Rost B. State-of-the-art in membrane protein prediction. Appl Bioinformatics 2002; 1: 21-35.
    • (2002) Appl Bioinformatics , vol.1 , pp. 21-35
    • Chen, C.P.1    Rost, B.2
  • 18
    • 0030853763 scopus 로고    scopus 로고
    • Grundy WN, Timothy LB, Charles PE, Michael EB. Meta-MEME: Motif-based hidden markov models of protein families. Comput Appl Biosci 1997; 13: 397-406.
    • Grundy WN, Timothy LB, Charles PE, Michael EB. Meta-MEME: Motif-based hidden markov models of protein families. Comput Appl Biosci 1997; 13: 397-406.
  • 19
    • 0028181441 scopus 로고
    • Hidden Markov models in computational biology: Applications to protein modelling
    • Krogh A, Brown M, Mian IS, Sjölander K, Haussler D. Hidden Markov models in computational biology: applications to protein modelling. J Mol Biol 1994; 235: 1501-31.
    • (1994) J Mol Biol , vol.235 , pp. 1501-1531
    • Krogh, A.1    Brown, M.2    Mian, I.S.3    Sjölander, K.4    Haussler, D.5
  • 20
    • 0035503929 scopus 로고    scopus 로고
    • A hybrid method for protein sequence modelling with improved accuracy
    • Olsson B, Laurio K, Gudjonsson L. A hybrid method for protein sequence modelling with improved accuracy. Inf Sci 2001; 139: 113-38.
    • (2001) Inf Sci , vol.139 , pp. 113-138
    • Olsson, B.1    Laurio, K.2    Gudjonsson, L.3
  • 21
    • 23844495275 scopus 로고    scopus 로고
    • Predicting the phosphorylation sites using hidden markov models and machine learning methods
    • Senawongse P, Dalby AD, Yang ZR. Predicting the phosphorylation sites using hidden markov models and machine learning methods. J Chem Inf Model 2005; 45: 1147-52.
    • (2005) J Chem Inf Model , vol.45 , pp. 1147-1152
    • Senawongse, P.1    Dalby, A.D.2    Yang, Z.R.3
  • 24
    • 0011921589 scopus 로고    scopus 로고
    • The kernel trick for distances
    • Technical Report. Microsoft Res May 2000
    • Scholkopf B. The kernel trick for distances, Technical Report. Microsoft Res May 2000.
    • Scholkopf, B.1
  • 26
    • 0141506120 scopus 로고    scopus 로고
    • Characterising proteolytic cleavage site activity using bio-basis function neural networks
    • Thomson R, Hodgman TC, Yang ZR, Doyle AK. Characterising proteolytic cleavage site activity using bio-basis function neural networks. Bioinformatics 2003; 19: 1741-7.
    • (2003) Bioinformatics , vol.19 , pp. 1741-1747
    • Thomson, R.1    Hodgman, T.C.2    Yang, Z.R.3    Doyle, A.K.4
  • 27
    • 0037407113 scopus 로고    scopus 로고
    • Reliable prediction of T-cell epitopes using neural networks with novel sequence representations
    • Nielsen M, Lundegaard C, Worning P, Lauemoller SL, Lamberth K, Buss S, et al. Reliable prediction of T-cell epitopes using neural networks with novel sequence representations. Protein Sci 2003; 12: 1007-17.
    • (2003) Protein Sci , vol.12 , pp. 1007-1017
    • Nielsen, M.1    Lundegaard, C.2    Worning, P.3    Lauemoller, S.L.4    Lamberth, K.5    Buss, S.6
  • 28
    • 0029003322 scopus 로고
    • Prediction of O-glycosylation of mammalian proteins: Specificity patterns of UDP-Ga1NAc: polypeptide N-acetylgalactosaminyltransferase
    • Hansen JE, Lund O, Engelbrecht J, Bohr H, Nielsen JO. Prediction of O-glycosylation of mammalian proteins: specificity patterns of UDP-Ga1NAc: polypeptide N-acetylgalactosaminyltransferase. Biochem J 1995; 30: 801-13.
    • (1995) Biochem J , vol.30 , pp. 801-813
    • Hansen, J.E.1    Lund, O.2    Engelbrecht, J.3    Bohr, H.4    Nielsen, J.O.5
  • 29
    • 0042674397 scopus 로고    scopus 로고
    • Using a neural network and spatial clustering to predict the location of active sites in enzymes
    • Gutteridge A, Bartlett GJ, Thornton JM. Using a neural network and spatial clustering to predict the location of active sites in enzymes. J Mol Biol 2003; 330: 719-34.
    • (2003) J Mol Biol , vol.330 , pp. 719-734
    • Gutteridge, A.1    Bartlett, G.J.2    Thornton, J.M.3
  • 30
    • 0031912107 scopus 로고    scopus 로고
    • Prediction of protein hydration sites from sequence by modular neural networks
    • Ehrlich L, Reczko M, Bohr H, Wade RC. Prediction of protein hydration sites from sequence by modular neural networks. Protein Eng 1998; 11: 11-9.
    • (1998) Protein Eng , vol.11 , pp. 11-19
    • Ehrlich, L.1    Reczko, M.2    Bohr, H.3    Wade, R.C.4
  • 31
    • 0033670134 scopus 로고    scopus 로고
    • Engineering support vector machine kernels that recognize translation initiation sites
    • Zien A, Ratsch G, Mika S, Scholkopf B, Lengauer T, Muller KR. Engineering support vector machine kernels that recognize translation initiation sites. Bioinformatics 2000; 16: 799-807.
    • (2000) Bioinformatics , vol.16 , pp. 799-807
    • Zien, A.1    Ratsch, G.2    Mika, S.3    Scholkopf, B.4    Lengauer, T.5    Muller, K.R.6
  • 32
    • 0036086337 scopus 로고    scopus 로고
    • Support vector machines with selective kernel scaling for protein classification and identification of key amino acid positions
    • Zavaljevski N, Stevens FJ, Reifman J. Support vector machines with selective kernel scaling for protein classification and identification of key amino acid positions. Bioinformatics 2002; 18: 689-96.
    • (2002) Bioinformatics , vol.18 , pp. 689-696
    • Zavaljevski, N.1    Stevens, F.J.2    Reifman, J.3
  • 33
    • 8844219516 scopus 로고    scopus 로고
    • Prediction of phosphorylation sites using SVMs
    • Kim JH, Lee J, Oh B, Kimm K, Koh I. Prediction of phosphorylation sites using SVMs. Bioinformatics 2004; 20: 3179-84.
    • (2004) Bioinformatics , vol.20 , pp. 3179-3184
    • Kim, J.H.1    Lee, J.2    Oh, B.3    Kimm, K.4    Koh, I.5
  • 34
    • 0142148183 scopus 로고    scopus 로고
    • Application of support vector machines for T-cell epitopes prediction
    • Zhao Y, Pinilla C, Valmori D, Martin R, Simon R. Application of support vector machines for T-cell epitopes prediction. Bioinformatics 2003; 19: 1978-84.
    • (2003) Bioinformatics , vol.19 , pp. 1978-1984
    • Zhao, Y.1    Pinilla, C.2    Valmori, D.3    Martin, R.4    Simon, R.5
  • 35
    • 1842765629 scopus 로고    scopus 로고
    • Prediction of protein-protein interaction sites using support vector machines
    • Koike A, Takagi T. Prediction of protein-protein interaction sites using support vector machines'. Protein Eng Des Sel 2004; 17: 165-73.
    • (2004) Protein Eng Des Sel , vol.17 , pp. 165-173
    • Koike, A.1    Takagi, T.2
  • 36
    • 13244275013 scopus 로고    scopus 로고
    • What can we learn from noncoding regions of similarity between genomes?
    • Down TA, Hubbard JJ. What can we learn from noncoding regions of similarity between genomes? BMC Bioinformatics 2004; 5: 131.
    • (2004) BMC Bioinformatics , vol.5 , pp. 131
    • Down, T.A.1    Hubbard, J.J.2
  • 37
    • 0003527079 scopus 로고
    • Self organization and associative memory
    • 3rd Ed, Berling
    • Kohonen T. Self organization and associative memory. 3rd Ed Springer, Berling 1989.
    • (1989) Springer
    • Kohonen, T.1
  • 38
    • 0025814729 scopus 로고
    • Identification of a new motif on nucleic acid sequence data using Kohonen's self-organising map
    • Arrigo P, Giuliano F, Scalia F, Rapallo A, Damiani G. Identification of a new motif on nucleic acid sequence data using Kohonen's self-organising map. CABIOS 1991; 7: 353-7.
    • (1991) CABIOS , vol.7 , pp. 353-357
    • Arrigo, P.1    Giuliano, F.2    Scalia, F.3    Rapallo, A.4    Damiani, G.5
  • 39
    • 0025134507 scopus 로고
    • Efficient recognition of immunoglobulin domains from amino acid sequences using a neural network
    • Bengio Y, Pouliot Y. Efficient recognition of immunoglobulin domains from amino acid sequences using a neural network. CABIOS 1990; 6: 319-24
    • (1990) CABIOS , vol.6 , pp. 319-324
    • Bengio, Y.1    Pouliot, Y.2
  • 40
    • 0026268095 scopus 로고
    • Topological maps of protein sequences
    • Ferran EA, Ferrara P. Topological maps of protein sequences. Biol Cybern 1991; 65: 451-8.
    • (1991) Biol Cybern , vol.65 , pp. 451-458
    • Ferran, E.A.1    Ferrara, P.2
  • 41
    • 0031595301 scopus 로고    scopus 로고
    • Wang HC, Dopazo J, Carazo JM. Self-organising tree growing network for classifying amino acids. Bioinformatics1998; 14: 376-7.
    • Wang HC, Dopazo J, Carazo JM. Self-organising tree growing network for classifying amino acids. Bioinformatics1998; 14: 376-7.
  • 42
    • 0027764341 scopus 로고
    • hybrid method to cluster protein sequences based on statistics and artificial neural networks
    • Ferran EA, Pflugfelder BA. hybrid method to cluster protein sequences based on statistics and artificial neural networks. CABIOS 1993; 9: 671-80.
    • (1993) CABIOS , vol.9 , pp. 671-680
    • Ferran, E.A.1    Pflugfelder, B.A.2
  • 43
    • 0344687170 scopus 로고    scopus 로고
    • Mining biological data using self-organizing map
    • Yang ZR, Chou KC. Mining biological data using self-organizing map. J Chem Inform Comput Sci 2003; 43: 1748-53.
    • (2003) J Chem Inform Comput Sci , vol.43 , pp. 1748-1753
    • Yang, Z.R.1    Chou, K.C.2
  • 44
    • 0023803244 scopus 로고
    • Predicting the secondary structure of globular proteins using neural network models
    • Qian N, Sejnowski TJ. Predicting the secondary structure of globular proteins using neural network models. J. Mol Biol 1988; 202: 865-84.
    • (1988) J. Mol Biol , vol.202 , pp. 865-884
    • Qian, N.1    Sejnowski, T.J.2
  • 45
    • 13844272392 scopus 로고    scopus 로고
    • A novel neural network method in mining molecular sequence data
    • Yang ZR, Thomson R. A novel neural network method in mining molecular sequence data. IEEE Trans Neural Netw 2005; 16: 263-74.
    • (2005) IEEE Trans Neural Netw , vol.16 , pp. 263-274
    • Yang, Z.R.1    Thomson, R.2
  • 47
    • 34249862825 scopus 로고    scopus 로고
    • Dayhoff MO, Schwartz RM, Orcutt BC. A model of evolutionary change in proteins. matrices for detecting distant relationships. In: Dayhoff MO Ed. Atlas of protein sequence and structure 1978; 5: 345-58.
    • Dayhoff MO, Schwartz RM, Orcutt BC. A model of evolutionary change in proteins. matrices for detecting distant relationships. In: Dayhoff MO Ed. Atlas of protein sequence and structure 1978; 5: 345-58.
  • 48
    • 0027361123 scopus 로고
    • A structural basis for sequence comparisons - an evaluation of scoring methodologies
    • Johnson MS, Overington JP. A structural basis for sequence comparisons - an evaluation of scoring methodologies. J Mol Biol 1993; 233: 716-38.
    • (1993) J Mol Biol , vol.233 , pp. 716-738
    • Johnson, M.S.1    Overington, J.P.2
  • 49
    • 34249859608 scopus 로고    scopus 로고
    • Bio-support vector machines for computational proteomics
    • Yang ZR, Chou KC. Bio-support vector machines for computational proteomics. Bioinformatics 2003; 19: 1-7.
    • (2003) Bioinformatics , vol.19 , pp. 1-7
    • Yang, Z.R.1    Chou, K.C.2
  • 50
    • 13644251956 scopus 로고    scopus 로고
    • Orthogonal kernel machine in prediction of functional sites in preteins
    • Yang ZR. Orthogonal kernel machine in prediction of functional sites in preteins. IEEE Trans Syst Man Cybern 2005; 35: 100-6.
    • (2005) IEEE Trans Syst Man Cybern , vol.35 , pp. 100-106
    • Yang, Z.R.1
  • 51
    • 4644262747 scopus 로고    scopus 로고
    • Reduced bio-basis function neural networks for protease cleavage site prediction
    • Yang ZR, Berry E. Reduced bio-basis function neural networks for protease cleavage site prediction. J Comput Biol Bioinform 2004; 2: 511-31.
    • (2004) J Comput Biol Bioinform , vol.2 , pp. 511-531
    • Yang, Z.R.1    Berry, E.2
  • 52
    • 20744444880 scopus 로고    scopus 로고
    • Predict disordered proteins using bio-basis function neural networks
    • Thomson R, Esnouf R. Predict disordered proteins using bio-basis function neural networks. Lect Notes Comput Sci 2004; 3177: 19-27.
    • (2004) Lect Notes Comput Sci , vol.3177 , pp. 19-27
    • Thomson, R.1    Esnouf, R.2
  • 53
    • 20744437001 scopus 로고    scopus 로고
    • RONN: Use of the biobasis function neural network technique for the detection of natively disordered regions in proteins
    • Yang ZR, Thomson R, McNeil P, Esnouf R. RONN: use of the biobasis function neural network technique for the detection of natively disordered regions in proteins. Bioinformatics 2005; 21: 3369-76.
    • (2005) Bioinformatics , vol.21 , pp. 3369-3376
    • Yang, Z.R.1    Thomson, R.2    McNeil, P.3    Esnouf, R.4
  • 54
    • 33745043489 scopus 로고    scopus 로고
    • A bio-basis function neural netw for protein peptide cleavage activity characterisation
    • Yang ZR, Dry J, Thomson R, Hodgman C. A bio-basis function neural netw for protein peptide cleavage activity characterisation. Neural Netw 2006; 19: 401.
    • (2006) Neural Netw , vol.19 , pp. 401
    • Yang, Z.R.1    Dry, J.2    Thomson, R.3    Hodgman, C.4
  • 55
    • 1842439981 scopus 로고    scopus 로고
    • Bio-basis function neural networks for the prediction of the O-linkage sites in glyco-proteins
    • Yang ZR, Chou KC. Bio-basis function neural networks for the prediction of the O-linkage sites in glyco-proteins. Bioinformatics 2004; 20: 903-8.
    • (2004) Bioinformatics , vol.20 , pp. 903-908
    • Yang, Z.R.1    Chou, K.C.2
  • 56
    • 18744369642 scopus 로고    scopus 로고
    • Prediction of caspase cleavage sites using bayesian biobasis function neural networks
    • Yang ZR. Prediction of caspase cleavage sites using bayesian biobasis function neural networks. Bioinformatics 2005; 21: 1831-7.
    • (2005) Bioinformatics , vol.21 , pp. 1831-1837
    • Yang, Z.R.1
  • 57
    • 85142133783 scopus 로고    scopus 로고
    • Yang ZR. Mining SARS-CoV protease cleavage data using decision trees, a novel method for decisive template searching. Bioinformatics 2005; 21: 2644-50.
    • Yang ZR. Mining SARS-CoV protease cleavage data using decision trees, a novel method for decisive template searching. Bioinformatics 2005; 21: 2644-50.
  • 58
    • 34548677983 scopus 로고    scopus 로고
    • A probabilistic peptide machine for predicting Hepatitis C virus protease cleavage sites
    • in press
    • Yang ZR. A probabilistic peptide machine for predicting Hepatitis C virus protease cleavage sites. IEEE Trans Informat Technol Biomed (in press).
    • IEEE Trans Informat Technol Biomed
    • Yang, Z.R.1
  • 60
    • 26844446068 scopus 로고    scopus 로고
    • Bio-kernel self-organizing map for HIV drug resistance classification
    • Yang ZR and Young N. Bio-kernel self-organizing map for HIV drug resistance classification. Lect Notes Comput Sci 2005; 3610: 179-84.
    • (2005) Lect Notes Comput Sci , vol.3610 , pp. 179-184
    • Yang, Z.R.1    Young, N.2
  • 61
    • 0026577882 scopus 로고
    • How antibodies block HIV infection: Paths to an AIDS vaccine
    • Putney S. How antibodies block HIV infection: paths to an AIDS vaccine. Trends Biochem Sci 1992; 7: 191-6.
    • (1992) Trends Biochem Sci , vol.7 , pp. 191-196
    • Putney, S.1
  • 63
    • 0042067948 scopus 로고    scopus 로고
    • HIV vaccine still out of our grasp
    • Kathryn S. HIV vaccine still out of our grasp. Lancet Infect Dis 2003; 3: 457.
    • (2003) Lancet Infect Dis , vol.3 , pp. 457
    • Kathryn, S.1
  • 64
    • 0033001019 scopus 로고    scopus 로고
    • Weber IT, Harrison RW. Molecular mechanics analysis of drug-resistant mutants of HIV protease. Protein Eng1999; 12: 469-74.
    • Weber IT, Harrison RW. Molecular mechanics analysis of drug-resistant mutants of HIV protease. Protein Eng1999; 12: 469-74.
  • 65
    • 16244403666 scopus 로고    scopus 로고
    • Prediction of HIV-1 protease inhibitor resistance using a protein-inhibitor flexible docking approach
    • Jenwitheesuk E, Samudrala R. Prediction of HIV-1 protease inhibitor resistance using a protein-inhibitor flexible docking approach. Antivir Ther 2005; 10: 157-66.
    • (2005) Antivir Ther , vol.10 , pp. 157-166
    • Jenwitheesuk, E.1    Samudrala, R.2
  • 66
    • 0041341885 scopus 로고    scopus 로고
    • Structure-based phenotyping predicts HIV-1 protease inhibitor resistance
    • Shenderovich MD, Kagan RM, Heseltine PN, Ramnarayan K. Structure-based phenotyping predicts HIV-1 protease inhibitor resistance. Protein Sci 2003; 12: 1706-18.
    • (2003) Protein Sci , vol.12 , pp. 1706-1718
    • Shenderovich, M.D.1    Kagan, R.M.2    Heseltine, P.N.3    Ramnarayan, K.4
  • 67
    • 0042154495 scopus 로고    scopus 로고
    • Comparison of nine resistance interpretation systems for HIV-1 genotyping
    • Sturmer M, Doerr HW, Staszewski S, Preiser W. Comparison of nine resistance interpretation systems for HIV-1 genotyping. Antivir Ther 2003; 8: 239-44.
    • (2003) Antivir Ther , vol.8 , pp. 239-244
    • Sturmer, M.1    Doerr, H.W.2    Staszewski, S.3    Preiser, W.4
  • 68
    • 0036189326 scopus 로고    scopus 로고
    • Characterizing the relationship between HIV-1 genotype and phenotype: Prediction-based classification
    • Foulkes AS, De GV. Characterizing the relationship between HIV-1 genotype and phenotype: prediction-based classification. Biometrics 2002; 58: 145-56.
    • (2002) Biometrics , vol.58 , pp. 145-156
    • Foulkes, A.S.1    GV, D.2
  • 69
    • 0036639447 scopus 로고    scopus 로고
    • The role of resistance characteristics of viral strains in the prediction of the response to antiretroviral therapy in HIV infection
    • Vergu E, Mallet A, Golmard JL. The role of resistance characteristics of viral strains in the prediction of the response to antiretroviral therapy in HIV infection. J Acquir Immune Defic Syndr 2002; 30: 263-70.
    • (2002) J Acquir Immune Defic Syndr , vol.30 , pp. 263-270
    • Vergu, E.1    Mallet, A.2    Golmard, J.L.3
  • 70
    • 0038238324 scopus 로고    scopus 로고
    • Variable prediction of antiretroviral treatment outcome by different systems for interpreting genotypic human immunodeficiency virus type 1 drug resistance
    • De Luca A, Cingolani A, Giambenedetto S, Trotta MP, Baldini F, Rizzo MG, et al. Variable prediction of antiretroviral treatment outcome by different systems for interpreting genotypic human immunodeficiency virus type 1 drug resistance. J Infect Dis 2003; 187: 1934-43.
    • (2003) J Infect Dis , vol.187 , pp. 1934-1943
    • De Luca, A.1    Cingolani, A.2    Giambenedetto, S.3    Trotta, M.P.4    Baldini, F.5    Rizzo, M.G.6
  • 71
    • 0037248697 scopus 로고    scopus 로고
    • Predicting HIV drug resistance with neural networks
    • Draghici S, Potter RB. Predicting HIV drug resistance with neural networks. Bioinformatics 2003; 19: 98-107.
    • (2003) Bioinformatics , vol.19 , pp. 98-107
    • Draghici, S.1    Potter, R.B.2
  • 74
    • 33745161050 scopus 로고    scopus 로고
    • Structural biology and drug discovery
    • Scapin, G. Structural biology and drug discovery. Curr Pharm Des 2006; 12(17): 2087-97.
    • (2006) Curr Pharm Des , vol.12 , Issue.17 , pp. 2087-2097
    • Scapin, G.1
  • 75
    • 33745135773 scopus 로고    scopus 로고
    • Recent developments of the chemistry development kit (CDK) - an open-source java library for chemo- and bioinformatics
    • Steinbeck C, Hoppe C, Kuhn S, Floris M, Guha R, Willighagen EL. Recent developments of the chemistry development kit (CDK) - an open-source java library for chemo- and bioinformatics. Curr Pharm Des 2006; 12(17): 2111-20.
    • (2006) Curr Pharm Des , vol.12 , Issue.17 , pp. 2111-2120
    • Steinbeck, C.1    Hoppe, C.2    Kuhn, S.3    Floris, M.4    Guha, R.5    Willighagen, E.L.6


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.