메뉴 건너뛰기




Volumn 8, Issue 8, 2013, Pages

A Consistency-Based Feature Selection Method Allied with Linear SVMs for HIV-1 Protease Cleavage Site Prediction

Author keywords

[No Author keywords available]

Indexed keywords

HUMAN IMMUNODEFICIENCY VIRUS PROTEINASE;

EID: 84882994745     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0063145     Document Type: Article
Times cited : (16)

References (46)
  • 1
    • 84882959715 scopus 로고    scopus 로고
    • UNAIDS website. Available:. Accessed 2013 May 13
    • UNAIDS website. Available: http://www.unaids.org. Accessed 2013 May 13.
  • 2
    • 67349157017 scopus 로고    scopus 로고
    • Variable context Markov chains for HIV protease cleavage site prediction
    • Ogul H, (2009) Variable context Markov chains for HIV protease cleavage site prediction. Bio Systems 96: 246-250.
    • (2009) Bio Systems , vol.96 , pp. 246-250
    • Ogul, H.1
  • 3
    • 32544445260 scopus 로고    scopus 로고
    • A reliable method for HIV-1 protease cleavage site prediction
    • Nanni L, Lumini A, (2006) A reliable method for HIV-1 protease cleavage site prediction. Neurocomputing 69: 838-841.
    • (2006) Neurocomputing , vol.69 , pp. 838-841
    • Nanni, L.1    Lumini, A.2
  • 5
    • 33745822421 scopus 로고    scopus 로고
    • Machine learning for HIV-1 protease cleavage site prediction
    • Lumini A, Nanni L, (2006) Machine learning for HIV-1 protease cleavage site prediction. Pattern Recognition Letters 27: 1537-1544.
    • (2006) Pattern Recognition Letters , vol.27 , pp. 1537-1544
    • Lumini, A.1    Nanni, L.2
  • 6
    • 0031762518 scopus 로고    scopus 로고
    • Artificial neural network method for predicting HIV protease cleavage sites in protein
    • Cai YD, Yu H, Chou KC, (1998) Artificial neural network method for predicting HIV protease cleavage sites in protein. Journal of Protein Chemistry 17: 607-615.
    • (1998) Journal of Protein Chemistry , vol.17 , pp. 607-615
    • Cai, Y.D.1    Yu, H.2    Chou, K.C.3
  • 7
    • 13844272392 scopus 로고    scopus 로고
    • Bio-basis function neural network for prediction of protease cleavage sites in proteins
    • Yang ZR, Thomson R, (2005) Bio-basis function neural network for prediction of protease cleavage sites in proteins,. IEEE Transactions on Neural Networks 16: 263-274.
    • (2005) IEEE Transactions on Neural Networks , vol.16 , pp. 263-274
    • Yang, Z.R.1    Thomson, R.2
  • 9
  • 10
    • 0037196307 scopus 로고    scopus 로고
    • Support Vector Machines for predicting HIV protease cleavage sites in protein
    • Cai YD, Liu XJ, Xu XB, Chou KC, (2002) Support Vector Machines for predicting HIV protease cleavage sites in protein. Journal of Computational Chemistry 23: 267-274.
    • (2002) Journal of Computational Chemistry , vol.23 , pp. 267-274
    • Cai, Y.D.1    Liu, X.J.2    Xu, X.B.3    Chou, K.C.4
  • 12
    • 77951634085 scopus 로고    scopus 로고
    • An MLP-based feature subset selection for HIV-1 protease cleavage site analysis
    • Kim G, Kim Y, Lim H, Kim H, (2010) An MLP-based feature subset selection for HIV-1 protease cleavage site analysis,. Artificial Intelligence in Medicine 48: 83-89.
    • (2010) Artificial Intelligence in Medicine , vol.48 , pp. 83-89
    • Kim, G.1    Kim, Y.2    Lim, H.3    Kim, H.4
  • 13
    • 32044474813 scopus 로고    scopus 로고
    • Comparison among feature extraction methods for HIV-1 protease cleavage site prediction
    • Loris N, (2006) Comparison among feature extraction methods for HIV-1 protease cleavage site prediction. Pattern Recognition 39 (4) ().
    • (2006) Pattern Recognition , vol.39 , Issue.4
    • Loris, N.1
  • 15
    • 4043056488 scopus 로고    scopus 로고
    • Review: prediction of HIV protease cleavage sites in proteins
    • Chou KC, (1996) Review: prediction of HIV protease cleavage sites in proteins. Anal Biochem 233 (1) ().
    • (1996) Anal Biochem , vol.233 , Issue.1
    • Chou, K.C.1
  • 16
    • 25144487698 scopus 로고    scopus 로고
    • Comprehensive Bioinformatic Analysis of the Specificity of Human Immunodeficiency Virus Type 1 Protease
    • You L, Garwicz D, Rögnvaldsson T, (2005) Comprehensive Bioinformatic Analysis of the Specificity of Human Immunodeficiency Virus Type 1 Protease. Journal of Virology 79: 12477-12486.
    • (2005) Journal of Virology , vol.79 , pp. 12477-12486
    • You, L.1    Garwicz, D.2    Rögnvaldsson, T.3
  • 17
    • 35748932917 scopus 로고    scopus 로고
    • A review of feature selection techniques in bioinformatics
    • Saeys Y, Inza I, Larrañaga P, (2007) A review of feature selection techniques in bioinformatics. Bioinformatics 23: 2507-17.
    • (2007) Bioinformatics , vol.23 , pp. 2507-2517
    • Saeys, Y.1    Inza, I.2    Larrañaga, P.3
  • 21
    • 84883017931 scopus 로고    scopus 로고
    • Information Fusion for Biological Prediction
    • Jaeger S, Chen SS, (2010) Information Fusion for Biological Prediction. Journal of Data Science pp. 8.
    • (2010) Journal of Data Science , pp. 8
    • Jaeger, S.1    Chen, S.S.2
  • 22
    • 4444262024 scopus 로고    scopus 로고
    • Why neural networks should not be used for HIV-1 protease cleavage site prediction
    • Rögnvaldsson T, You L, (2004) Why neural networks should not be used for HIV-1 protease cleavage site prediction. Bioinformatics 20: 1702-1709.
    • (2004) Bioinformatics , vol.20 , pp. 1702-1709
    • Rögnvaldsson, T.1    You, L.2
  • 23
    • 0036161259 scopus 로고    scopus 로고
    • Gene Selection for Cancer Classification using Support Vector Machines
    • Guyon I, Weston J, Barnhill S, Vapnik V, (2002) Gene Selection for Cancer Classification using Support Vector Machines. Machine Learning 46: 389-422.
    • (2002) Machine Learning , vol.46 , pp. 389-422
    • Guyon, I.1    Weston, J.2    Barnhill, S.3    Vapnik, V.4
  • 24
    • 34249753618 scopus 로고
    • Support-vector networks
    • Cortes C, Vapnik V, (1995) Support-vector networks. Machine Learning 20: 273-297.
    • (1995) Machine Learning , vol.20 , pp. 273-297
    • Cortes, C.1    Vapnik, V.2
  • 25
    • 33845703344 scopus 로고    scopus 로고
    • What is a support vector machine?
    • Noble WS, (2006) What is a support vector machine?. Nature Biotechnology 24: 1565-1567.
    • (2006) Nature Biotechnology , vol.24 , pp. 1565-1567
    • Noble, W.S.1
  • 26
    • 84882968642 scopus 로고    scopus 로고
    • A Novel SVM-RFE for Gene Selection
    • Tan JY, (2009) A Novel SVM-RFE for Gene Selection. ICOSB pp. 237-244.
    • (2009) ICOSB , pp. 237-244
    • Tan, J.Y.1
  • 27
    • 84883043944 scopus 로고    scopus 로고
    • SVM-RFE Algorithm for Gene Feature Selection
    • Yu Y, (2008) SVM-RFE Algorithm for Gene Feature Selection. Computer Engineering.
    • (2008) Computer Engineering
    • Yu, Y.1
  • 28
    • 0141721892 scopus 로고    scopus 로고
    • Mining viral protease data to extract cleavage knowledge
    • Narayanan A, Wu X, Yang ZR, (2002) Mining viral protease data to extract cleavage knowledge. Bioinformatics 18 (1) (): S5-S13.
    • (2002) Bioinformatics , vol.18 , Issue.1
    • Narayanan, A.1    Wu, X.2    Yang, Z.R.3
  • 29
    • 27544496497 scopus 로고    scopus 로고
    • An automated genotyping system for analysis of HIV-1 and other microbial sequences
    • De Oliveira T, Deforche K, Cassol S, Salminen M, Paraskevis D, et al. (2005) An automated genotyping system for analysis of HIV-1 and other microbial sequences. Bioinformatics 21: 3797-3800.
    • (2005) Bioinformatics , vol.21 , pp. 3797-3800
    • De Oliveira, T.1    Deforche, K.2    Cassol, S.3    Salminen, M.4    Paraskevis, D.5
  • 30
    • 1842455240 scopus 로고    scopus 로고
    • Bio-support vector machines for computational proteomics
    • Yang ZR, Chou KC, (2004) Bio-support vector machines for computational proteomics. Bioinformatics 20: 735-741.
    • (2004) Bioinformatics , vol.20 , pp. 735-741
    • Yang, Z.R.1    Chou, K.C.2
  • 32
    • 78650685659 scopus 로고    scopus 로고
    • A new encoding technique for peptide classification
    • Nanni L, Lumini A, (2010) A new encoding technique for peptide classification. Expert Systems with Applications 38: 3185-3191.
    • (2010) Expert Systems with Applications , vol.38 , pp. 3185-3191
    • Nanni, L.1    Lumini, A.2
  • 33
    • 0242302657 scopus 로고    scopus 로고
    • Consistency-based search in feature selection
    • Dash M, (2003) Consistency-based search in feature selection. Artificial Intelligence 151: 155-176.
    • (2003) Artificial Intelligence , vol.151 , pp. 155-176
    • Dash, M.1
  • 34
    • 0013326060 scopus 로고    scopus 로고
    • Feature selection for classification
    • Dash M, Liu H, (1997) Feature selection for classification. Intelligent Data Analysis 1: 131-156.
    • (1997) Intelligent Data Analysis , vol.1 , pp. 131-156
    • Dash, M.1    Liu, H.2
  • 37
    • 67649094096 scopus 로고    scopus 로고
    • Feature subset selection from positive and unlabelled examples
    • Calvo B, Larranaga P, Lozano JA, (2009) Feature subset selection from positive and unlabelled examples. Pattern Recognition Letters 30: 1027-1036.
    • (2009) Pattern Recognition Letters , vol.30 , pp. 1027-1036
    • Calvo, B.1    Larranaga, P.2    Lozano, J.A.3
  • 38
    • 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, (2003) Application of support vector machines for T-cell epitopes prediction. Bioinformatics 19: 1978-1984.
    • (2003) Bioinformatics , vol.19 , pp. 1978-1984
    • Zhao, Y.1    Pinilla, C.2    Valmori, D.3    Martin, R.4    Simon, R.5
  • 39
    • 24344458137 scopus 로고    scopus 로고
    • Feature selection based on mutual information: criteria of max-dependency, max-relevance, and min-redundancy
    • Peng HC, Long F, Ding C, (2005) Feature selection based on mutual information: criteria of max-dependency, max-relevance, and min-redundancy. IEEE Transactions on Pattern Analysis and Machine Intelligence 27 (8) (): 1226-1238.
    • (2005) IEEE Transactions on Pattern Analysis and Machine Intelligence , vol.27 , Issue.8 , pp. 1226-1238
    • Peng, H.C.1    Long, F.2    Ding, C.3
  • 40
    • 0030027067 scopus 로고    scopus 로고
    • Predicting human immunodeficiency virus protease cleavage sites in proteins by a discriminant function method
    • Chou KC, Tomasselli AG, Reardon IM, Heinrikson RL, (1996) Predicting human immunodeficiency virus protease cleavage sites in proteins by a discriminant function method. Proteins 24: 51-72.
    • (1996) Proteins , vol.24 , pp. 51-72
    • Chou, K.C.1    Tomasselli, A.G.2    Reardon, I.M.3    Heinrikson, R.L.4
  • 42
    • 84863856522 scopus 로고    scopus 로고
    • Using Rule-Based Machine Learning for Candidate Disease Gene Prioritization and Sample Classification of Cancer Gene Expression Data
    • Glaab E, Bacardit J, Garibaldi JM, Krasnogor N, (2012) Using Rule-Based Machine Learning for Candidate Disease Gene Prioritization and Sample Classification of Cancer Gene Expression Data. PLoS ONE 7 (7) (): e39932.
    • (2012) PLoS ONE , vol.7 , Issue.7
    • Glaab, E.1    Bacardit, J.2    Garibaldi, J.M.3    Krasnogor, N.4
  • 43
    • 34447331698 scopus 로고    scopus 로고
    • Classification based upon gene expression data: bias, precision of error rates
    • Wood I, Visscher P, Mengersen K, (2007) Classification based upon gene expression data: bias, precision of error rates. Bioinformatics 23: 1363-1370.
    • (2007) Bioinformatics , vol.23 , pp. 1363-1370
    • Wood, I.1    Visscher, P.2    Mengersen, K.3
  • 44
    • 77549084648 scopus 로고    scopus 로고
    • Advanced nonparametric tests for multiple comparisons in the design of experiments in computational intelligence and data mining: experimental analysis of power
    • Garcia S, Fernandez A, Luengo J, Herrera F, (2010) Advanced nonparametric tests for multiple comparisons in the design of experiments in computational intelligence and data mining: experimental analysis of power. Inf Sci 180 (10) (): 2044-2064.
    • (2010) Inf Sci , vol.180 , Issue.10 , pp. 2044-2064
    • Garcia, S.1    Fernandez, A.2    Luengo, J.3    Herrera, F.4
  • 45
    • 79960535211 scopus 로고    scopus 로고
    • A practical tutorial on the use of nonparametric statistical tests as a methodology for comparing evolutionary and swarm intelligence algorithms
    • Derrac J, García S, Molina D, Herrera F, (2011) A practical tutorial on the use of nonparametric statistical tests as a methodology for comparing evolutionary and swarm intelligence algorithms. Swarm and Evolutionary Computation pp. 3-18.
    • (2011) Swarm and Evolutionary Computation , pp. 3-18
    • Derrac, J.1    García, S.2    Molina, D.3    Herrera, F.4
  • 46
    • 35748932917 scopus 로고    scopus 로고
    • A review of feature selection techniques in bioinformatics
    • Saeys Y, Inza I, Larrañaga P, (2007) A review of feature selection techniques in bioinformatics. Bioinformatics 23 (19) (): 2507-2517.
    • (2007) Bioinformatics , vol.23 , Issue.19 , pp. 2507-2517
    • Saeys, Y.1    Inza, I.2    Larrañaga, P.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.