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Volumn 37, Issue 4, 2004, Pages 224-239

Classification and knowledge discovery in protein databases

Author keywords

Class imbalance; Class distribution estimation; Classification; Clustering; Feature selection; Noise

Indexed keywords

ALGORITHM; ARTICLE; ARTIFICIAL NEURAL NETWORK; BIOINFORMATICS; DENSITY; FISHER EXACT TEST; LEARNING; LOGISTIC REGRESSION ANALYSIS; MACHINE; MODEL; PRIORITY JOURNAL; PROTEIN DATABASE;

EID: 4744344959     PISSN: 15320464     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jbi.2004.07.008     Document Type: Article
Times cited : (87)

References (71)
  • 1
    • 0033757822 scopus 로고    scopus 로고
    • An overview of structural genomics
    • S. Burley An overview of structural genomics Nat Struct Biol: Struct Genom Suppl 2000 932 934
    • (2000) Nat Struct Biol: Struct Genom , pp. 932-934
    • Burley, S.1
  • 2
    • 0035782925 scopus 로고    scopus 로고
    • Review: Protein secondary structure prediction continues to rise
    • B. Rost Review: protein secondary structure prediction continues to rise J Struct Biol 134 2-3 2001 204 218
    • (2001) J Struct Biol , vol.134 , Issue.23 , pp. 204-218
    • Rost, B.1
  • 4
    • 0036153571 scopus 로고    scopus 로고
    • What does it mean to be natively unfolded?
    • V.N. Uversky What does it mean to be natively unfolded? Eur J Biochem 269 1 2002 2 12
    • (2002) Eur J Biochem , vol.269 , Issue.1 , pp. 2-12
    • Uversky, V.N.1
  • 6
    • 0036568293 scopus 로고    scopus 로고
    • Prediction of coordination number and relative solvent accessibility in proteins
    • G. Pollastri, P. Baldi, P. Fariselli, and R. Casadio Prediction of coordination number and relative solvent accessibility in proteins Proteins 47 2 2002 142 153
    • (2002) Proteins , vol.47 , Issue.2 , pp. 142-153
    • Pollastri, G.1    Baldi, P.2    Fariselli, P.3    Casadio, R.4
  • 8
  • 9
    • 0029846866 scopus 로고    scopus 로고
    • Cleavage site analysis in picornaviral polyproteins: Discovering cellular targets by neural networks
    • N. Blom, J. Hansen, D. Blaas, and S. Brunak Cleavage site analysis in picornaviral polyproteins: discovering cellular targets by neural networks Protein Sci 5 11 1996 2203 2216
    • (1996) Protein Sci , vol.5 , Issue.11 , pp. 2203-2216
    • Blom, N.1    Hansen, J.2    Blaas, D.3    Brunak, S.4
  • 10
    • 0033579464 scopus 로고    scopus 로고
    • Sequence and structure-based prediction of eukaryotic protein phosphorylation sites
    • N. Blom, S. Gammeltoft, and S. Brunak Sequence and structure-based prediction of eukaryotic protein phosphorylation sites J Mol Biol 294 5 1999 1351 1362
    • (1999) J Mol Biol , vol.294 , Issue.5 , pp. 1351-1362
    • Blom, N.1    Gammeltoft, S.2    Brunak, S.3
  • 12
    • 0042622251 scopus 로고    scopus 로고
    • Scansite 2.0: Proteome-wide prediction of cell signaling interactions using short sequence motifs
    • J.C. Obenauer, L.C. Cantley, and M.B. Yaffe Scansite 2.0: Proteome-wide prediction of cell signaling interactions using short sequence motifs Nucleic Acids Res 31 2003 3635 3641
    • (2003) Nucleic Acids Res , vol.31 , pp. 3635-3641
    • Obenauer, J.C.1    Cantley, L.C.2    Yaffe, M.B.3
  • 13
    • 0031743421 scopus 로고    scopus 로고
    • Profile hidden Markov models
    • S.R. Eddy Profile hidden Markov models Bioinformatics 14 9 1998 755 763
    • (1998) Bioinformatics , vol.14 , Issue.9 , pp. 755-763
    • Eddy, S.R.1
  • 14
  • 16
    • 0023803244 scopus 로고
    • Predicting the secondary structure of globular proteins using neural network models
    • N. Qian, and T.J. Sejnowski Predicting the secondary structure of globular proteins using neural network models J Mol Biol 202 4 1988 865 884
    • (1988) J Mol Biol , vol.202 , Issue.4 , pp. 865-884
    • Qian, N.1    Sejnowski, T.J.2
  • 19
    • 0031334221 scopus 로고    scopus 로고
    • Selection of relevant features and examples in machine learning
    • A.L. Blum, and P. Langley Selection of relevant features and examples in machine learning Artif Intell 97 1-2 1997 245 271
    • (1997) Artif Intell , vol.97 , Issue.12 , pp. 245-271
    • Blum, A.L.1    Langley, P.2
  • 20
    • 33745561205 scopus 로고    scopus 로고
    • An introduction to variable and feature selection
    • I. Guyon, and A. Elisseeff An introduction to variable and feature selection J Mach Learn Res 3 2003 1157 1182
    • (2003) J Mach Learn Res , vol.3 , pp. 1157-1182
    • Guyon, I.1    Elisseeff, A.2
  • 21
    • 0242410408 scopus 로고    scopus 로고
    • Benchmarking attribute selection techniques for discrete class data mining
    • M.A. Hall, and G. Holmes Benchmarking attribute selection techniques for discrete class data mining IEEE Trans Knowledge Data Eng 15 6 2003 1437 1447
    • (2003) IEEE Trans Knowledge Data Eng , vol.15 , Issue.6 , pp. 1437-1447
    • Hall, M.A.1    Holmes, G.2
  • 22
    • 0031381525 scopus 로고    scopus 로고
    • Wrappers for feature selection
    • R. Kohavi, and G. John Wrappers for feature selection Artif Intell 97 1-2 1997 273 324
    • (1997) Artif Intell , vol.97 , Issue.12 , pp. 273-324
    • Kohavi, R.1    John, G.2
  • 24
    • 0036161259 scopus 로고    scopus 로고
    • Gene selection for cancer classification using support vector machines
    • I. Guyon, J. Weston, S. Barnhill, and V. Vapnik Gene selection for cancer classification using support vector machines Mach Learn 46 1-3 2002 389 422
    • (2002) Mach Learn , vol.46 , Issue.13 , pp. 389-422
    • Guyon, I.1    Weston, J.2    Barnhill, S.3    Vapnik, V.4
  • 26
    • 2942731012 scopus 로고    scopus 로고
    • An extensive empirical study of feature selection metrics for text classification
    • G. Forman An extensive empirical study of feature selection metrics for text classification J Mach Learn Res 3 2003 1289 1305
    • (2003) J Mach Learn Res , vol.3 , pp. 1289-1305
    • Forman, G.1
  • 29
    • 1442275185 scopus 로고    scopus 로고
    • Learning when training data are costly: The effect of class distribution on tree induction
    • G.M. Weiss, and F. Provost Learning when training data are costly: the effect of class distribution on tree induction J Artif Intell Res 19 2003 315 354
    • (2003) J Artif Intell Res , vol.19 , pp. 315-354
    • Weiss, G.M.1    Provost, F.2
  • 30
    • 0031998121 scopus 로고    scopus 로고
    • Detection of oil spills in satellite radar images of sea surface
    • M. Kubat, R.C. Holte, and S. Matwin Detection of oil spills in satellite radar images of sea surface Mach Learn 30 1998 195 215
    • (1998) Mach Learn , vol.30 , pp. 195-215
    • Kubat, M.1    Holte, R.C.2    Matwin, S.3
  • 32
    • 33845536164 scopus 로고    scopus 로고
    • The class imbalance problem: A systematic study
    • N. Japkowicz, and S. Stephen The class imbalance problem: a systematic study Intell Data Anal 6 5 2002 429 450
    • (2002) Intell Data Anal , vol.6 , Issue.5 , pp. 429-450
    • Japkowicz, N.1    Stephen, S.2
  • 38
    • 0029718295 scopus 로고    scopus 로고
    • A large-scale evaluation of features for automatic detection of oil spills in ERS SAR images
    • Lincoln, NE;
    • Solberg A, Solberg R. A large-scale evaluation of features for automatic detection of oil spills in ERS SAR images. In: International Geoscience and Remote Sensing Symposium. Lincoln, NE; 1996. p. 1484-86
    • (1996) International Geoscience and Remote Sensing Symposium , pp. 1484-1486
    • Solberg, A.1    Solberg, R.2
  • 40
    • 0043130638 scopus 로고    scopus 로고
    • Prediction of boundaries between intrinsically ordered and disordered protein regions
    • P. Radivojac, Z. Obradovic, C.J. Brown, and A.K. Dunker Prediction of boundaries between intrinsically ordered and disordered protein regions Pac Symp Biocomput 8 2003 216 227
    • (2003) Pac Symp Biocomput , vol.8 , pp. 216-227
    • Radivojac, P.1    Obradovic, Z.2    Brown, C.J.3    Dunker, A.K.4
  • 41
    • 0036630282 scopus 로고    scopus 로고
    • A solution for imbalanced training sets problem by CombNET-II and its application on fog forecasting
    • A.S. Nugroho, S. Kuroyanagi, and A. Iwata A solution for imbalanced training sets problem by CombNET-II and its application on fog forecasting IEICE Trans Inform Syst E85-D(7) 2002 1165 1174
    • (2002) IEICE Trans Inform Syst , vol.E85-D , Issue.7 , pp. 1165-1174
    • Nugroho, A.S.1    Kuroyanagi, S.2    Iwata, A.3
  • 44
    • 0004735086 scopus 로고
    • A necessary condition for learning from positive examples
    • H. Shvaytser A necessary condition for learning from positive examples Mach Learn 5 1 1990 101 113
    • (1990) Mach Learn , vol.5 , Issue.1 , pp. 101-113
    • Shvaytser, H.1
  • 47
    • 0034133513 scopus 로고    scopus 로고
    • Distance-based outliers: Algorithms and applications
    • E.M. Knorr, R.T. Ng, and V. Tucakov Distance-based outliers: algorithms and applications VLDB J 8 3-4 2000 237 253
    • (2000) VLDB J , vol.8 , Issue.34 , pp. 237-253
    • Knorr, E.M.1    Ng, R.T.2    Tucakov, V.3
  • 50
    • 0003136237 scopus 로고
    • Efficient and effective clustering method for spatial data mining
    • September 12-15, Santiago, Chile;
    • Ng RT, Han J. Efficient and effective clustering method for spatial data mining. In: 20th International Conference on Very Large Data Bases, 1994, September 12-15, Santiago, Chile; 1994. p. 144-55
    • (1994) 20th International Conference on Very Large Data Bases, 1994 , pp. 144-155
    • Ng, R.T.1    Han, J.2
  • 53
    • 0000492326 scopus 로고
    • Learning from noisy examples
    • D. Angluin, and P. Laird Learning from noisy examples Mach Learn 2 1988 343 370
    • (1988) Mach Learn , vol.2 , pp. 343-370
    • Angluin, D.1    Laird, P.2
  • 54
    • 0032203519 scopus 로고    scopus 로고
    • Financial markets: Very noisy information processing
    • M. Magdon-Ismail, A. Nicholson, and Y.S. Abu-Mostafa Financial markets: very noisy information processing Proc IEEE 86 11 1998 2184 2195
    • (1998) Proc IEEE , vol.86 , Issue.11 , pp. 2184-2195
    • Magdon-Ismail, M.1    Nicholson, A.2    Abu-Mostafa, Y.S.3
  • 55
    • 0030211964 scopus 로고    scopus 로고
    • Bagging predictors
    • L. Breiman Bagging predictors Mach Learn 24 1996 123 140
    • (1996) Mach Learn , vol.24 , pp. 123-140
    • Breiman, L.1
  • 56
    • 0004296209 scopus 로고    scopus 로고
    • 4th ed. Prentice Hall Upper Saddle River, NJ
    • W.H. Green Econometric analysis 4th ed. 2000 Prentice Hall Upper Saddle River, NJ
    • (2000) Econometric Analysis
    • Green, W.H.1
  • 58
    • 0024861871 scopus 로고
    • Approximation by superpositions of a sigmoidal function
    • G. Cybenko Approximation by superpositions of a sigmoidal function MCSS, Math Contr Signals Syst 2 1989 303 314
    • (1989) MCSS, Math Contr Signals Syst , vol.2 , pp. 303-314
    • Cybenko, G.1
  • 59
    • 0028543366 scopus 로고
    • Training feedforward networks with the Marquardt algorithm
    • M.T. Hagan, and M.B. Menhaj Training feedforward networks with the Marquardt algorithm IEEE Trans Neural Netw 5 6 1994 989 993
    • (1994) IEEE Trans Neural Netw , vol.5 , Issue.6 , pp. 989-993
    • Hagan, M.T.1    Menhaj, M.B.2
  • 60
    • 84943274699 scopus 로고
    • A direct adaptive method for faster backpropogation learning: The RPROP algorithm
    • M. Riedmiller, and H. Braun A direct adaptive method for faster backpropogation learning: the RPROP algorithm Proc IEEE Int Conf Neural Netw 1 1993 586 591
    • (1993) Proc IEEE Int Conf Neural Netw , vol.1 , pp. 586-591
    • Riedmiller, M.1    Braun, H.2
  • 63
    • 0003942446 scopus 로고    scopus 로고
    • VCH Weinheim New York, Basel, Cambridge, Tokyo
    • F. Marks Protein phosphorylation 1996 VCH Weinheim New York, Basel, Cambridge, Tokyo
    • (1996) Protein Phosphorylation
    • Marks, F.1
  • 65
    • 4744367074 scopus 로고    scopus 로고
    • Adjusting the outputs of a classifier to new a priori probabilities may significantly improve classification accuracy: Evidence from a multi-class problem in remote sensing
    • Morgan Kaufmann Williamstown, MA, USA
    • P. Latinne, M. Saerens, and C. Decaestecker Adjusting the outputs of a classifier to new a priori probabilities may significantly improve classification accuracy: evidence from a multi-class problem in remote sensing Proceedings of the Eighteenth International Conference on Machine Learning 2001 Morgan Kaufmann Williamstown, MA, USA 298 305
    • (2001) Proceedings of the Eighteenth International Conference on Machine Learning , pp. 298-305
    • Latinne, P.1    Saerens, M.2    Decaestecker, C.3
  • 66
    • 0032922002 scopus 로고    scopus 로고
    • PhosphoBase, a database of phosphorylation sites: Release 2.0
    • A. Kreegipuu, N. Blom, and S. Brunak PhosphoBase, a database of phosphorylation sites: release 2.0 Nucleic Acids Res 27 1 1999 237 239
    • (1999) Nucleic Acids Res , vol.27 , Issue.1 , pp. 237-239
    • Kreegipuu, A.1    Blom, N.2    Brunak, S.3
  • 69
    • 0036080160 scopus 로고    scopus 로고
    • Bagging, boosting and the random subspace method for linear classifiers
    • M. Skurichina, and R.P.W. Duin Bagging, boosting and the random subspace method for linear classifiers Pattern Anal Appl 5 2002 121 135
    • (2002) Pattern Anal Appl , vol.5 , pp. 121-135
    • Skurichina, M.1    Duin, R.P.W.2
  • 70
    • 1242268938 scopus 로고    scopus 로고
    • Tree induction vs. logistic regression: A learning-curve analysis
    • C. Perlich, F. Provost, and J. Simonoff Tree induction vs. logistic regression: a learning-curve analysis J Mach Learn Res 4 2003 211 255
    • (2003) J Mach Learn Res , vol.4 , pp. 211-255
    • Perlich, C.1    Provost, F.2    Simonoff, J.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.