메뉴 건너뛰기




Volumn , Issue , 2008, Pages 1-367

Introduction to machine learning and bioinformatics

Author keywords

[No Author keywords available]

Indexed keywords


EID: 85128444485     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.1201/b17186     Document Type: Book
Times cited : (23)

References (539)
  • 6
    • 0002344794 scopus 로고
    • Bootstrap Methods: Another Look at the Jackknife
    • Efron, B. (1979) Bootstrap Methods: Another Look at the Jackknife. In The Annals of Statistics 7:1, pp. 1-26.
    • (1979) The Annals of Statistics , vol.7 , Issue.1 , pp. 1-26
    • Efron, B.1
  • 17
    • 33745156863 scopus 로고    scopus 로고
    • Some theory for Fisher's Linear Discriminant function, "naive Bayes," and some alternatives when there are many more variables than observations
    • Bickel, P.J. and Levina, E. (2004), Some theory for Fisher's Linear Discriminant function, "naive Bayes," and some alternatives when there are many more variables than observations, Bernoulli, 10, 989-1010
    • (2004) Bernoulli , vol.10 , pp. 989-1010
    • Bickel, P.J.1    Levina, E.2
  • 20
    • 0030211964 scopus 로고    scopus 로고
    • Bagging predictors
    • Breiman L. (1996), Bagging predictors, Machine Learning, 24, 123-140
    • (1996) Machine Learning , vol.24 , pp. 123-140
    • Breiman, L.1
  • 21
    • 0346786584 scopus 로고    scopus 로고
    • Arcing classifiers
    • Breiman L. (1998), Arcing classifiers, Annals of Statistics, 26, 801-849
    • (1998) Annals of Statistics , vol.26 , pp. 801-849
    • Breiman, L.1
  • 22
    • 0035478854 scopus 로고    scopus 로고
    • Random forests
    • Breiman L. (2001), Random forests, Machine Learning, 45, 5-32
    • (2001) Machine Learning , vol.45 , pp. 5-32
    • Breiman, L.1
  • 23
    • 28944450149 scopus 로고    scopus 로고
    • Prediction of proteinprotein interactions using random decision forest framework
    • Chen, X.W. and Liu, M. (2005), Prediction of proteinprotein interactions using random decision forest framework, Bioinformatics, 21, 4394-4400
    • (2005) Bioinformatics , vol.21 , pp. 4394-4400
    • Chen, X.W.1    Liu, M.2
  • 24
    • 13944255457 scopus 로고    scopus 로고
    • Protein classification based on text classification techniques
    • Cheng B.Y., Carbonell J.G., Klein-Seetharaman J. (2005), Protein classification based on text classification techniques, Proteins, 58, 955-970
    • (2005) Proteins , vol.58 , pp. 955-970
    • Cheng, B.Y.1    Carbonell, J.G.2    Klein-Seetharaman, J.3
  • 26
    • 0010442827 scopus 로고    scopus 로고
    • On the algorithmic implementation of multi-class kernel-based vector machines
    • Crammer, K. and Singer, Y. (2001), On the algorithmic implementation of multi-class kernel-based vector machines, Journal of Machine Learning Research, 2, 265-292
    • (2001) Journal of Machine Learning Research , vol.2 , pp. 265-292
    • Crammer, K.1    Singer, Y.2
  • 27
    • 0036489046 scopus 로고    scopus 로고
    • Comparison of discrimination methods for the classification of tumors using gene expression data
    • Dudoit, S., Fridlyand, J. and Speed, T.P. (2002), Comparison of discrimination methods for the classification of tumors using gene expression data, Journal of the American Statistical Association, 97, 77-87
    • (2002) Journal of the American Statistical Association , vol.97 , pp. 77-87
    • Dudoit, S.1    Fridlyand, J.2    Speed, T.P.3
  • 28
    • 0000406788 scopus 로고
    • Solving multi-class learning profilems via error correcting output codes
    • Dietterich, T.G. and Bakiri, G. (1995), Solving multi-class learning profilems via error correcting output codes, Journal of Artificial Intelligence Research, 2, 263-286
    • (1995) Journal of Artificial Intelligence Research , vol.2 , pp. 263-286
    • Dietterich, T.G.1    Bakiri, G.2
  • 29
    • 0000764772 scopus 로고
    • The use of multiple measurements in taxonomic profilems
    • Fisher, R.A. (1936), The use of multiple measurements in taxonomic profilems, Annals of Eugenics, 7, 179-188
    • (1936) Annals of Eugenics , vol.7 , pp. 179-188
    • Fisher, R.A.1
  • 30
    • 0003909532 scopus 로고    scopus 로고
    • Nonparametric Discrimination; Consistency Properties, Report Number 4, USAF School of Aviation Medicine, Randolph Field, TX
    • Fix, E. and Hodges, J.L. (1951), Discriminatory Analysis. Nonparametric Discrimination; Consistency Properties, Report Number 4, USAF School of Aviation Medicine, Randolph Field, TX
    • Discriminatory Analysis , vol.1951
    • Fix, E.1    Hodges, J.L.2
  • 31
    • 0034164230 scopus 로고    scopus 로고
    • Additive logistic regression: A statistical view of boosting
    • (with discussion)
    • Friedman, J.H., Hastie, T. and Tibshirani, R. (1998), Additive logistic regression: A statistical view of boosting, Annals of Statistics, 28, 337-407 (with discussion)
    • (1998) Annals of Statistics , vol.28 , pp. 337-407
    • Friedman, J.H.1    Hastie, T.2    Tibshirani, R.3
  • 34
    • 0031211090 scopus 로고    scopus 로고
    • A decision-theoretic generalization of online learning and an application to boosting
    • Freund, Y. and Schapire, R.E. (1997), A decision-theoretic generalization of online learning and an application to boosting, Journal of Computer and System Sciences, 55, 119-139
    • (1997) Journal of Computer and System Sciences , vol.55 , pp. 119-139
    • Freund, Y.1    Schapire, R.E.2
  • 37
    • 0344740820 scopus 로고    scopus 로고
    • Functional classification of proteins using a nearest neighbour algorithm
    • Keck, H.P. and Wetter, T. (2003), Functional classification of proteins using a nearest neighbour algorithm, In Silico Biology, 3, 23
    • (2003) Silico Biology , vol.3 , pp. 23
    • Keck, H.P.1    Wetter, T.2
  • 40
    • 2142775432 scopus 로고    scopus 로고
    • Multi-category support vector machines, theory and application to the classification of microarray data and satellite radiance data
    • Lee, Y., Lin, Y. andWahba, G. (2004), Multi-category support vector machines, theory and application to the classification of microarray data and satellite radiance data, Journal of American Statistical Association, 99, 67-81
    • (2004) Journal of American Statistical Association , vol.99 , pp. 67-81
    • Lee, Y.1    Lin, Y.2    Wahba, G.3
  • 41
    • 0036258405 scopus 로고    scopus 로고
    • Support vector machines and the Bayes rule in classification
    • Lin, Y. (2002), Support vector machines and the Bayes rule in classification, Data Mining and Knowledge Discovery, 6, 259-275
    • (2002) Data Mining and Knowledge Discovery , vol.6 , pp. 259-275
    • Lin, Y.1
  • 42
    • 41549131613 scopus 로고    scopus 로고
    • Evidence contrary to the statistical view of boosting
    • Mease, D. and Wyner, A. (2008), Evidence contrary to the statistical view of boosting, Journal of Machine Learning Research, 9, 131-156
    • (2008) Journal of Machine Learning Research , vol.9 , pp. 131-156
    • Mease, D.1    Wyner, A.2
  • 43
    • 0242692461 scopus 로고    scopus 로고
    • The application of rule-based methods to class prediction profilems in genomics
    • Michailidis, G. and Shedden, K. (2003), The application of rule-based methods to class prediction profilems in genomics, Journal of Computational Biology, 10, 689-698
    • (2003) Journal of Computational Biology , vol.10 , pp. 689-698
    • Michailidis, G.1    Shedden, K.2
  • 46
    • 27644555055 scopus 로고    scopus 로고
    • Interpretation of shotgun proteomic data: The protein inference profilem
    • Nesvizhskii A.I., Aebersold R. (2005), Interpretation of shotgun proteomic data: The protein inference profilem, Molecular & Cellular Proteomics, 4, 1419-1440
    • (2005) Molecular & Cellular Proteomics , vol.4 , pp. 1419-1440
    • Nesvizhskii, A.I.1    Aebersold, R.2
  • 48
    • 0025448521 scopus 로고
    • The strength of weak learnability
    • Schapire, R. (1990), The strength of weak learnability, Machine Learning, 5, 197-227
    • (1990) Machine Learning , vol.5 , pp. 197-227
    • Schapire, R.1
  • 51
    • 15844413351 scopus 로고    scopus 로고
    • A comprehensive evaluation of multicategory classification methods for microarray gene expression cancer diagnosis
    • Statnikov, A., Aliferis, C.F., Tsamardinos, I., Hardini, D. and Levy, S. (2005), A comprehensive evaluation of multicategory classification methods for microarray gene expression cancer diagnosis, Bioinformatics, 21, 631 - 643.
    • (2005) Bioinformatics , vol.21 , pp. 631-643
    • Statnikov, A.1    Aliferis, C.F.2    Tsamardinos, I.3    Hardini, D.4    Levy, S.5
  • 52
    • 0000439527 scopus 로고
    • Consistent nonparametric regression
    • Stone, C. (1977), Consistent nonparametric regression, Annals of Statistics, 5, 595-620
    • (1977) Annals of Statistics , vol.5 , pp. 595-620
    • Stone, C.1
  • 54
    • 33645467062 scopus 로고    scopus 로고
    • Improved classification of mass spectrometry database search results using newer machine learning approaches
    • Ulintz, P.J., Zhu, J., Qin, Z.S. and Andrews, P.C. (2006), Improved classification of mass spectrometry database search results using newer machine learning approaches, Molecular and Cellular Proteomics, 5, 497-509
    • (2006) Molecular and Cellular Proteomics , vol.5 , pp. 497-509
    • Ulintz, P.J.1    Zhu, J.2    Qin, Z.S.3    Andrews, P.C.4
  • 59
    • 34249649636 scopus 로고    scopus 로고
    • Improved centroids estimation for the nearest shrunken centroid classifier
    • Wang, S. and Zhu, J. (2007) Improved centroids estimation for the nearest shrunken centroid classifier, Bioinformatics, 23, 972-979
    • (2007) Bioinformatics , vol.23 , pp. 972-979
    • Wang, S.1    Zhu, J.2
  • 60
    • 0037388166 scopus 로고    scopus 로고
    • Cell and tumor classification using gene expression data: construction of forests
    • Zhang, H., Yu, C.Y. and Singer, B. (2003), Cell and tumor classification using gene expression data: construction of forests, Proceedings of the National Academies of Science USA, 100, 673-679
    • (2003) Proceedings of the National Academies of Science USA , vol.100 , pp. 673-679
    • Zhang, H.1    Yu, C.Y.2    Singer, B.3
  • 61
    • 0036808207 scopus 로고    scopus 로고
    • ProbID: A probabilistic algorithm to identify peptides through sequence database searching using tandem mass spectral data
    • Zhang, N., Aebersold, R. and Schwikowski, B. (2002), ProbID: A probabilistic algorithm to identify peptides through sequence database searching using tandem mass spectral data, Proteomics, 2, 1406-1412
    • (2002) Proteomics , vol.2 , pp. 1406-1412
    • Zhang, N.1    Aebersold, R.2    Schwikowski, B.3
  • 62
    • 0034598746 scopus 로고    scopus 로고
    • Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling
    • Alizadeh, A.A. et al. (2000), Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling, Nature, 403, 503-511
    • (2000) Nature , vol.403 , pp. 503-511
    • Alizadeh, A.A.1
  • 64
    • 0025898312 scopus 로고
    • Dualistic geometry of the manifold of higher-order neurons
    • Amari, S.I, (1991), Dualistic geometry of the manifold of higher-order neurons, Neural Networks, 4, 443-451
    • (1991) Neural Networks , vol.4 , pp. 443-451
    • Amari, S.I1
  • 65
    • 0027453616 scopus 로고
    • Model based Gaussian and non-Gaussian clustering
    • Banfield, J.D. and Raftery, A.E. (1993), Model based Gaussian and non-Gaussian clustering, Biometrics, 49, 803-821
    • (1993) Biometrics , vol.49 , pp. 803-821
    • Banfield, J.D.1    Raftery, A.E.2
  • 66
    • 0042378381 scopus 로고    scopus 로고
    • Laplacian eigenmaps for dimensionality reduction and data representation
    • Belkin, M. and Nyogi, P. (2003), Laplacian eigenmaps for dimensionality reduction and data representation, Neural Computation, 15, 1373-1396
    • (2003) Neural Computation , vol.15 , pp. 1373-1396
    • Belkin, M.1    Nyogi, P.2
  • 67
    • 84864994884 scopus 로고    scopus 로고
    • Iterative signature algorithm for the analysis of large-scale gene expression data
    • Bergmann, S., Ihmels, J. and Barkai, N. (2003), Iterative signature algorithm for the analysis of large-scale gene expression data, Physical Review E, 67, 201-218
    • (2003) Physical Review E , vol.67 , pp. 201-218
    • Bergmann, S.1    Ihmels, J.2    Barkai, N.3
  • 69
    • 0002365852 scopus 로고
    • Surface learning with applications to lipreading
    • in Cowan et al. (eds), Morgan Kaufman, San Mateo, CA
    • Bregler, C. and Omohundro, M. (1994), Surface learning with applications to lipreading, in Cowan et al. (eds), Advances in Neural Information Processing Systems, Morgan Kaufman, San Mateo, CA
    • (1994) Advances in Neural Information Processing Systems
    • Bregler, C.1    Omohundro, M.2
  • 70
    • 0034566393 scopus 로고    scopus 로고
    • Biclustering of expression data
    • AAAI Press
    • Church, G.M. and Cheng, Y. (2000), Biclustering of expression data, in Proceedings of ISMB 2000, 93-103, AAAI Press
    • (2000) Proceedings of ISMB 2000 , pp. 93-103
    • Church, G.M.1    Cheng, Y.2
  • 71
    • 0037948870 scopus 로고    scopus 로고
    • Hessian eigenmaps: locally linear embedding techniques for high-dimensional data
    • Donoho, D.L. and Grimes, C. (2003), Hessian eigenmaps: locally linear embedding techniques for high-dimensional data, Proceedings of the National Academies, USA, 100, 5591-5596
    • (2003) Proceedings of the National Academies, USA , vol.100 , pp. 5591-5596
    • Donoho, D.L.1    Grimes, C.2
  • 73
    • 0035162698 scopus 로고    scopus 로고
    • Genomic expression responses to DNA-damaging agents and the regulatory role of the yeast ATR homolog mec1p
    • Gasch, A.P. et al. (2001), Genomic expression responses to DNA-damaging agents and the regulatory role of the yeast ATR homolog mec1p, Molecular Biology of the Cell, 12, 2987-3003
    • (2001) Molecular Biology of the Cell , vol.12 , pp. 2987-3003
    • Gasch, A.P.1
  • 74
    • 0033746670 scopus 로고    scopus 로고
    • Super-paramagnetic clustering of yeast gene expression profiles
    • Getz, G., Levine, E., Domany, E. and Zhang, M.Q. (2000), Super-paramagnetic clustering of yeast gene expression profiles, Physica A, 279, 457
    • (2000) Physica A , vol.279 , pp. 457
    • Getz, G.1    Levine, E.2    Domany, E.3    Zhang, M.Q.4
  • 76
    • 0000950204 scopus 로고    scopus 로고
    • Cluster analysis and mathematical programming
    • Hansen, P. and Jaumard, B. (1997), Cluster analysis and mathematical programming, Mathematical Programming, 79, 191-215
    • (1997) Mathematical Programming , vol.79 , pp. 191-215
    • Hansen, P.1    Jaumard, B.2
  • 77
    • 0034628901 scopus 로고    scopus 로고
    • Computational identification of cis-regulatory elements associated with groups of functionally related genes in Saccharomyces Cerevisiae
    • Hughes, J.D., Estep, P.E., Tavazoie, S. and Church, G.M. (2000), Computational identification of cis-regulatory elements associated with groups of functionally related genes in Saccharomyces Cerevisiae, Journal of Molecular Biology, 296, 1205-1214
    • (2000) Journal of Molecular Biology , vol.296 , pp. 1205-1214
    • Hughes, J.D.1    Estep, P.E.2    Tavazoie, S.3    Church, G.M.4
  • 79
    • 45849153013 scopus 로고    scopus 로고
    • Mixture models with multiple levels, with application to the analysis of multifactor gene expression data
    • Jornsten, R. and Keles, S. (2008), Mixture models with multiple levels, with application to the analysis of multifactor gene expression data, to appear in Biostatistics
    • (2008) Biostatistics
    • Jornsten, R.1    Keles, S.2
  • 82
    • 0037399130 scopus 로고    scopus 로고
    • Spectral biclustering of microarray data: co-clustering genes and conditions
    • Kluger, Y., Barsi, R., Cheng, J.T. and Gerstein, M (2003), Spectral biclustering of microarray data: co-clustering genes and conditions, Genome Research, 13, 703-716
    • (2003) Genome Research , vol.13 , pp. 703-716
    • Kluger, Y.1    Barsi, R.2    Cheng, J.T.3    Gerstein, M.4
  • 84
    • 0036012349 scopus 로고    scopus 로고
    • Plaid models for gene expression data
    • Lazzeroni, L. and Owen, A. (2002), Plaid models for gene expression data, Statistica Sinica, 12, 61-86
    • (2002) Statistica Sinica , vol.12 , pp. 61-86
    • Lazzeroni, L.1    Owen, A.2
  • 85
    • 0345257348 scopus 로고    scopus 로고
    • Topological local principal components analysis
    • Liu, Z.Y. and Xu, L. (2003), Topological local principal components analysis, Neurocomputing, 55, 739-745
    • (2003) Neurocomputing , vol.55 , pp. 739-745
    • Liu, Z.Y.1    Xu, L.2
  • 86
    • 0002759015 scopus 로고    scopus 로고
    • The Gifi system of descriptive multivariate analysis
    • Michailidis, G. and de Leeuw, J. (1998), The Gifi system of descriptive multivariate analysis, Statistical Science, 13, 307-336
    • (1998) Statistical Science , vol.13 , pp. 307-336
    • Michailidis, G.1    de Leeuw, J.2
  • 88
    • 0034704222 scopus 로고    scopus 로고
    • Nonlinear dimensionality reduction by locally linear embedding
    • Roweis, S.T. and Saul, L.K. (2000), Nonlinear dimensionality reduction by locally linear embedding, Science, 290, 2323-2326
    • (2000) Science , vol.290 , pp. 2323-2326
    • Roweis, S.T.1    Saul, L.K.2
  • 89
    • 2342517502 scopus 로고    scopus 로고
    • Think globally, fit locally: unsupervised learning of low dimensional manifolds
    • Saul, L.K. and Roweis, S.T. (2003), Think globally, fit locally: unsupervised learning of low dimensional manifolds, Journal of Machine Learning Research, 4, 119-155
    • (2003) Journal of Machine Learning Research , vol.4 , pp. 119-155
    • Saul, L.K.1    Roweis, S.T.2
  • 90
    • 0347243182 scopus 로고    scopus 로고
    • Nonlinear component analysis as a kernel eigenvalue profilem
    • Scholkopf, B., Smola, A. and Muller, K.R. (1998), Nonlinear component analysis as a kernel eigenvalue profilem, Neural Computation, 4, 1299-1309
    • (1998) Neural Computation , vol.4 , pp. 1299-1309
    • Scholkopf, B.1    Smola, A.2    Muller, K.R.3
  • 91
    • 1542357674 scopus 로고    scopus 로고
    • Revealing modularity and organization in the yeast molecular network by integrated analysis of highly heterogeneous genome-wide data
    • Tanay, A., Sharan, R., Kupiec, M. and Shamir, R. (2004), Revealing modularity and organization in the yeast molecular network by integrated analysis of highly heterogeneous genome-wide data, Proceedings of the National Academies of the USA, 101, 2981-2986
    • (2004) Proceedings of the National Academies of the USA , vol.101 , pp. 2981-2986
    • Tanay, A.1    Sharan, R.2    Kupiec, M.3    Shamir, R.4
  • 92
    • 0034704229 scopus 로고    scopus 로고
    • A global geometric framework for nonlinear dimensionality reduction
    • Tenenbaum, J.B., de Silva, V. and Langford, J.C. (2000), A global geometric framework for nonlinear dimensionality reduction, Science, 290, 2319-2323
    • (2000) Science , vol.290 , pp. 2319-2323
    • Tenenbaum, J.B.1    de Silva, V.2    Langford, J.C.3
  • 93
    • 0028385414 scopus 로고
    • Fuzzy logic, neural networks, and soft computing
    • L. A. Zadeh, "Fuzzy logic, neural networks, and soft computing," Communications of the ACM, vol. 37, pp. 77-84, 1994.
    • (1994) Communications of the ACM , vol.37 , pp. 77-84
    • Zadeh, L.A.1
  • 98
    • 0016458950 scopus 로고
    • The concept of a linguistic variable and its application to approximate reasoning: Part 1, 2, and 3
    • 301-357, 43-80
    • L. A. Zadeh, "The concept of a linguistic variable and its application to approximate reasoning: Part 1, 2, and 3," Information Sciences, vol. 8, 8, 9, pp. 199-249, 301-357, 43-80, 1975.
    • (1975) Information Sciences , vol.8 , Issue.8-9 , pp. 199-249
    • Zadeh, L.A.1
  • 99
    • 49349133217 scopus 로고
    • Fuzzy sets as a basis for a theory of possibility
    • L. A. Zadeh, "Fuzzy sets as a basis for a theory of possibility," Fuzzy Sets and Systems, vol. 1, pp. 3-28, 1978.
    • (1978) Fuzzy Sets and Systems , vol.1 , pp. 3-28
    • Zadeh, L.A.1
  • 100
    • 0020843799 scopus 로고
    • The role of fuzzy logic in the management of uncertainty in expert systems
    • L. A. Zadeh, "The role of fuzzy logic in the management of uncertainty in expert systems," Fuzzy Sets and Systems, vol. 11, pp. 199-227, 1983.
    • (1983) Fuzzy Sets and Systems , vol.11 , pp. 199-227
    • Zadeh, L.A.1
  • 103
  • 104
    • 0021892282 scopus 로고
    • Fuzzy identification of systems and its application to modeling and control
    • T. Takagi and M. Sugeno, "Fuzzy identification of systems and its application to modeling and control," IEEE Transactions on Systems, Man, and Cybernetics, vol. 15, pp. 116-132, 1985.
    • (1985) IEEE Transactions on Systems, Man, and Cybernetics , vol.15 , pp. 116-132
    • Takagi, T.1    Sugeno, M.2
  • 113
    • 51249194645 scopus 로고
    • A logical calculus of the idea immanent in nervous activity
    • W. S. McCulloch and W. Pitts, "A logical calculus of the idea immanent in nervous activity," Bulletin of Mathematical Biophysics, vol. 5, pp. 115-133, 1943.
    • (1943) Bulletin of Mathematical Biophysics , vol.5 , pp. 115-133
    • McCulloch, W.S.1    Pitts, W.2
  • 114
    • 0032208720 scopus 로고    scopus 로고
    • The truth will come to light: Directions and challenges in extracting the knowledge embedded within trained artificial neural networks
    • A. B. Tickle, R. Andrews, M. Golea, and J. Diederich, "The truth will come to light: Directions and challenges in extracting the knowledge embedded within trained artificial neural networks," IEEE Transactions on Neural Networks, vol. 9, pp. 1057-1068, 1998.
    • (1998) IEEE Transactions on Neural Networks , vol.9 , pp. 1057-1068
    • Tickle, A.B.1    Andrews, R.2    Golea, M.3    Diederich, J.4
  • 115
    • 0034187785 scopus 로고    scopus 로고
    • Neuro-fuzzy rule generation: Survey in soft computing framework
    • S.Mitra and Y. Hayashi, "Neuro-fuzzy rule generation: Survey in soft computing framework," IEEE Transactions on Neural Networks, vol. 11, pp. 748-768, 2000.
    • (2000) IEEE Transactions on Neural Networks , vol.11 , pp. 748-768
    • Mitra, S.1    Hayashi, Y.2
  • 116
    • 0027245159 scopus 로고
    • Knowledge-based connectionism for revising domain theories
    • L. M. Fu, "Knowledge-based connectionism for revising domain theories," IEEE Transactions on Systems, Man, and Cybernetics, vol. 23, pp. 173-182, 1993.
    • (1993) IEEE Transactions on Systems, Man, and Cybernetics , vol.23 , pp. 173-182
    • Fu, L.M.1
  • 117
    • 0028529307 scopus 로고
    • Knowledge-based artificial neural networks
    • G. G. Towell and J. W. Shavlik, "Knowledge-based artificial neural networks," Artificial Intelligence, vol. 70, pp. 119-165, 1994.
    • (1994) Artificial Intelligence , vol.70 , pp. 119-165
    • Towell, G.G.1    Shavlik, J.W.2
  • 118
    • 11144273669 scopus 로고
    • The perceptron: A probabilistic model for information storage and organization in the brain
    • F. Rosenblatt, "The perceptron: A probabilistic model for information storage and organization in the brain," Psychological Review, vol. 65, pp. 386-408, 1958.
    • (1958) Psychological Review , vol.65 , pp. 386-408
    • Rosenblatt, F.1
  • 121
    • 0000672424 scopus 로고
    • Fast learning in networks of locally-tuned processing units
    • J. Moody and C. J. Darken, "Fast learning in networks of locally-tuned processing units," Neural Computation, vol. 1, pp. 281-294, 1989.
    • (1989) Neural Computation , vol.1 , pp. 281-294
    • Moody, J.1    Darken, C.J.2
  • 131
    • 0141561662 scopus 로고
    • Finding minimal reducts using genetic algorithms
    • Warsaw Institute of Technology - Institute of Computer Science, Poland
    • J. Wroblewski, "Finding minimal reducts using genetic algorithms," Tech. Rep. 16/95, Warsaw Institute of Technology - Institute of Computer Science, Poland, 1995.
    • (1995) Tech. Rep. , vol.16 , Issue.95
    • Wroblewski, J.1
  • 135
    • 0027266182 scopus 로고
    • Functional equivalence between radial basis function networks and fuzzy inference systems
    • J. S. R. Jang and C. T. Sun, "Functional equivalence between radial basis function networks and fuzzy inference systems," IEEE Transactions on Neural Networks, vol. 4, pp. 156-159, 1993.
    • (1993) IEEE Transactions on Neural Networks , vol.4 , pp. 156-159
    • Jang, J.S.R.1    Sun, C.T.2
  • 137
    • 0026927426 scopus 로고
    • Multi-layer perceptron, fuzzy sets and classification
    • S. K. Pal and S. Mitra, "Multi-layer perceptron, fuzzy sets and classification," IEEE Transactions on Neural Networks, vol. 3, pp. 683-697, 1992.
    • (1992) IEEE Transactions on Neural Networks , vol.3 , pp. 683-697
    • Pal, S.K.1    Mitra, S.2
  • 139
    • 0026626684 scopus 로고
    • Neural network implementation of fuzzy logic
    • J. M. Keller, R. R. Yager, and H. Tahani, "Neural network implementation of fuzzy logic," Fuzzy Sets and Systems, vol. 45, pp. 1-12, 1992.
    • (1992) Fuzzy Sets and Systems , vol.45 , pp. 1-12
    • Keller, J.M.1    Yager, R.R.2    Tahani, H.3
  • 141
    • 0028481609 scopus 로고
    • Fuzzy MLP based expert system for medical diagnosis
    • S. Mitra, "Fuzzy MLP based expert system for medical diagnosis," Fuzzy Sets and Systems, vol. 65, pp. 285-296, 1994.
    • (1994) Fuzzy Sets and Systems , vol.65 , pp. 285-296
    • Mitra, S.1
  • 144
    • 0028192731 scopus 로고
    • Logical operation based fuzzy MLP for classification and rule generation
    • S. Mitra and S. K. Pal, "Logical operation based fuzzy MLP for classification and rule generation," Neural Networks, vol. 7, pp. 353-373, 1994.
    • (1994) Neural Networks , vol.7 , pp. 353-373
    • Mitra, S.1    Pal, S.K.2
  • 145
    • 0026923589 scopus 로고
    • Fuzzy ARTMAP: a neural network architecture for incremental supervised learning of analog multidimensional maps
    • G. A. Carpenter, S. Grossberg, N. Markuzon, J. H. Reynolds, and D. B. Rosen, "Fuzzy ARTMAP: a neural network architecture for incremental supervised learning of analog multidimensional maps," IEEE Transactions on Neural Networks, vol. 3, pp. 698-713, 1992.
    • (1992) IEEE Transactions on Neural Networks , vol.3 , pp. 698-713
    • Carpenter, G.A.1    Grossberg, S.2    Markuzon, N.3    Reynolds, J.H.4    Rosen, D.B.5
  • 146
    • 0027539801 scopus 로고
    • Self-organization for object extraction using multilayer neural network and fuzziness measures
    • A. Ghosh, N. R. Pal, and S. K. Pal, "Self-organization for object extraction using multilayer neural network and fuzziness measures," IEEE Transactions on Fuzzy Systems, vol. 1, pp. 54-68, 1993.
    • (1993) IEEE Transactions on Fuzzy Systems , vol.1 , pp. 54-68
    • Ghosh, A.1    Pal, N.R.2    Pal, S.K.3
  • 148
    • 0027574256 scopus 로고
    • A review of evolutionary artificial neural networks
    • X. Yao, "A review of evolutionary artificial neural networks," International Journal of Intelligent Systems, vol. 8, pp. 539-567, 1993.
    • (1993) International Journal of Intelligent Systems , vol.8 , pp. 539-567
    • Yao, X.1
  • 149
    • 0025477971 scopus 로고
    • Limitations of multi-layer perceptron networks - step towards genetic neural networks
    • H. Muhlenbein, "Limitations of multi-layer perceptron networks - step towards genetic neural networks," Parallel Computing, vol. 14, pp. 249-260, 1990.
    • (1990) Parallel Computing , vol.14 , pp. 249-260
    • Muhlenbein, H.1
  • 150
    • 0026711747 scopus 로고
    • General asymmetric neural networks and structure design by genetic algorithms
    • S. Bornholdt and D. Graudenz, "General asymmetric neural networks and structure design by genetic algorithms," Neural Networks, vol. 5, pp. 327-334, 1992.
    • (1992) Neural Networks , vol.5 , pp. 327-334
    • Bornholdt, S.1    Graudenz, D.2
  • 151
    • 0028336556 scopus 로고
    • Genetic evolution of the topology and weight distribution of neural networks
    • V. Maniezzo, "Genetic evolution of the topology and weight distribution of neural networks," IEEE Transactions on Neural Networks, vol. 5, pp. 39-53, 1994.
    • (1994) IEEE Transactions on Neural Networks , vol.5 , pp. 39-53
    • Maniezzo, V.1
  • 152
    • 0030197198 scopus 로고    scopus 로고
    • Cooperative-Competitive genetic evolution of radial basis function centers and widths for time series prediction
    • B. A.Whitehead and T. D. Choate, "Cooperative-Competitive genetic evolution of radial basis function centers and widths for time series prediction," IEEE Transactions on Neural Networks, vol. 7, pp. 869-880, 1996.
    • (1996) IEEE Transactions on Neural Networks , vol.7 , pp. 869-880
    • Whitehead, B.A.1    Choate, T.D.2
  • 153
    • 0028482532 scopus 로고
    • Genetic algorithms with fuzzy fitness function for object extraction using cellular neural networks
    • S. K. Pal and D. Bhandari, "Genetic algorithms with fuzzy fitness function for object extraction using cellular neural networks," Fuzzy Sets and Systems, vol. 65, pp. 129-139, 1994.
    • (1994) Fuzzy Sets and Systems , vol.65 , pp. 129-139
    • Pal, S.K.1    Bhandari, D.2
  • 154
    • 0030650646 scopus 로고    scopus 로고
    • Linguistic rule extraction from neural networks and genetic-algorithm-based rule selection
    • (Houston, USA)
    • H. Ishibuchi, M. Nii, and T. Murata, "Linguistic rule extraction from neural networks and genetic-algorithm-based rule selection," in Proceedings of IEEE International Conference on Neural Networks, (Houston, USA), pp. 2390-2395, 1997.
    • (1997) Proceedings of IEEE International Conference on Neural Networks , pp. 2390-2395
    • Ishibuchi, H.1    Nii, M.2    Murata, T.3
  • 158
    • 0032357372 scopus 로고    scopus 로고
    • Rough knowledge-based network, fuzziness and classification
    • S. Mitra, M. Banerjee, and S. K. Pal, "Rough knowledge-based network, fuzziness and classification," Neural Computing and Applications, vol. 7, pp. 17-25, 1998.
    • (1998) Neural Computing and Applications , vol.7 , pp. 17-25
    • Mitra, S.1    Banerjee, M.2    Pal, S.K.3
  • 160
    • 0034492516 scopus 로고    scopus 로고
    • Evolutionary modular design of rough knowledge-based network using fuzzy attributes
    • S. Mitra, P. Mitra, and S. K. Pal, "Evolutionary modular design of rough knowledge-based network using fuzzy attributes," Neurocomputing, vol. 36, pp. 45-66, 2001.
    • (2001) Neurocomputing , vol.36 , pp. 45-66
    • Mitra, S.1    Mitra, P.2    Pal, S.K.3
  • 166
    • 0031854546 scopus 로고    scopus 로고
    • Transcription regulatory region analysis using signal detection and fuzzy clustering
    • L. Pickert, I. Reuter, F. Klawonn, and E. Wingender, "Transcription regulatory region analysis using signal detection and fuzzy clustering," Bioinformatics, vol. 14, pp. 244-251, 1998.
    • (1998) Bioinformatics , vol.14 , pp. 244-251
    • Pickert, L.1    Reuter, I.2    Klawonn, F.3    Wingender, E.4
  • 167
    • 0026736363 scopus 로고
    • Determination of eukaryotic protein coding regions using neural networks and information theory
    • R. Farber, A. Lapedes, and K. Sirotkin, "Determination of eukaryotic protein coding regions using neural networks and information theory," Journal of Molecular Biology, vol. 226, pp. 471-479, 1992.
    • (1992) Journal of Molecular Biology , vol.226 , pp. 471-479
    • Farber, R.1    Lapedes, A.2    Sirotkin, K.3
  • 168
    • 0027234320 scopus 로고
    • Analysis of cleavage-site patterns in protein precursor sequences with a perceptron-type neural network
    • G. Schneider, S. Rohlk, and P. Wrede, "Analysis of cleavage-site patterns in protein precursor sequences with a perceptron-type neural network," Biochem Biophys Res Commun, vol. 194, pp. 951-959, 1993.
    • (1993) Biochem Biophys Res Commun , vol.194 , pp. 951-959
    • Schneider, G.1    Rohlk, S.2    Wrede, P.3
  • 169
    • 0029922511 scopus 로고    scopus 로고
    • Discovering and understfinding genes in human DNA sequence using GRAIL
    • E. C. Uberbacher, Y. Xu, and R. J. Mural, "Discovering and understfinding genes in human DNA sequence using GRAIL," Methods Enzymol, vol. 266, pp. 259-281, 1996.
    • (1996) Methods Enzymol , vol.266 , pp. 259-281
    • Uberbacher, E.C.1    Xu, Y.2    Mural, R.J.3
  • 170
    • 0025744474 scopus 로고
    • Prediction of human mRNA donor and acceptor sites from the DNA sequence
    • S. Brunak, J. Engelbrecht, and S. Knudsen, "Prediction of human mRNA donor and acceptor sites from the DNA sequence," Journal of Molecular Biology, vol. 220, pp. 49-65, 1991.
    • (1991) Journal of Molecular Biology , vol.220 , pp. 49-65
    • Brunak, S.1    Engelbrecht, J.2    Knudsen, S.3
  • 171
    • 0028932291 scopus 로고
    • Analysis of eukaryotic promoter sequences reveals a systematically occurring CT-signal
    • N. I. Larsen, J. Engelbrecht, and S. Brunak, "Analysis of eukaryotic promoter sequences reveals a systematically occurring CT-signal," Nucleic Acids Res, vol. 23, pp. 1223-1230, 1995.
    • (1995) Nucleic Acids Res , vol.23 , pp. 1223-1230
    • Larsen, N.I.1    Engelbrecht, J.2    Brunak, S.3
  • 172
    • 0030627982 scopus 로고    scopus 로고
    • Neural network prediction of translation initiation sites in eukaryotes: Perspectives for EST and genome analysis
    • A. G. Pedersen and H. Nielsen, "Neural network prediction of translation initiation sites in eukaryotes: Perspectives for EST and genome analysis," ISMB, vol. 5, pp. 226-233, 1997.
    • (1997) ISMB , vol.5 , pp. 226-233
    • Pedersen, A.G.1    Nielsen, H.2
  • 173
    • 0029387830 scopus 로고
    • Neural networks for full-scale protein sequence classification: Sequence encoding with singular value decomposition
    • C. H. Wu, M. Berry, S. Shivakumar, and J. McLarty, "Neural networks for full-scale protein sequence classification: Sequence encoding with singular value decomposition," Machine Learning, vol. 21, pp. 177-193, 1995.
    • (1995) Machine Learning , vol.21 , pp. 177-193
    • Wu, C.H.1    Berry, M.2    Shivakumar, S.3    McLarty, J.4
  • 174
    • 1542576024 scopus 로고    scopus 로고
    • Biological data mining with neural networks: Implementation and application of a fflexible decision tree extraction algorithm to genomic profilem domains
    • A. Browne, B. D. Hudson, D. C.Whitley, M. G. Ford, and P. Picton, "Biological data mining with neural networks: Implementation and application of a fflexible decision tree extraction algorithm to genomic profilem domains," Neurocomputing, vol. 57, pp. 275-293, 2004.
    • (2004) Neurocomputing , vol.57 , pp. 275-293
    • Browne, A.1    Hudson, B.D.2    Whitley, D.C.3    Ford, M.G.4    Picton, P.5
  • 175
    • 0030631792 scopus 로고    scopus 로고
    • Extracting rules from neural networks by pruning and hidden-unit splfitting
    • R. Setiono, "Extracting rules from neural networks by pruning and hidden-unit splfitting," Neural Computation, vol. 9, pp. 205-225, 1997.
    • (1997) Neural Computation , vol.9 , pp. 205-225
    • Setiono, R.1
  • 176
    • 0030449297 scopus 로고    scopus 로고
    • Kohonen map as a visualization tool for the analysis of protein sequences: Multiple alignments, domains and segments of secondary structures
    • J. Hanke and J. G. Reich, "Kohonen map as a visualization tool for the analysis of protein sequences: Multiple alignments, domains and segments of secondary structures," Comput Applic Biosci, vol. 6, pp. 447-454, 1996.
    • (1996) Comput Applic Biosci , vol.6 , pp. 447-454
    • Hanke, J.1    Reich, J.G.2
  • 177
    • 0031762518 scopus 로고    scopus 로고
    • Artificial neural network method for predicting HIV protease cleavage sites in protein
    • Y. D. Cai, H. Yu, and K. C. Chou, "Artificial neural network method for predicting HIV protease cleavage sites in protein," J. Protein Chem, vol. 17, pp. 607-615, 1998.
    • (1998) J. Protein Chem , vol.17 , pp. 607-615
    • Cai, Y.D.1    Yu, H.2    Chou, K.C.3
  • 178
    • 0031777347 scopus 로고    scopus 로고
    • Prediction of beta-turns
    • Y. D. Cai, H. Yu, and K. C. Chou, "Prediction of beta-turns," J. Protein Chem, vol. 17, pp. 363-376, 1998.
    • (1998) J. Protein Chem , vol.17 , pp. 363-376
    • Cai, Y.D.1    Yu, H.2    Chou, K.C.3
  • 179
    • 0029860175 scopus 로고    scopus 로고
    • Local structural motifs of protein backbones are classified by self-organizing neural networks
    • J. Schuchhardt, G. Schneider, J. Reichelt, D. Schomberg, and P. Wrede, "Local structural motifs of protein backbones are classified by self-organizing neural networks," Protein Eng, vol. 9, pp. 833-842, 1996.
    • (1996) Protein Eng , vol.9 , pp. 833-842
    • Schuchhardt, J.1    Schneider, G.2    Reichelt, J.3    Schomberg, D.4    Wrede, P.5
  • 180
    • 0025814729 scopus 로고
    • Identification of a new motif on nucleic acid sequence data using Kohonen's self organizing map
    • P. Arrigo, F. Giuliano, F. Scalia, A. Rapallo, and G. Damiani, "Identification of a new motif on nucleic acid sequence data using Kohonen's self organizing map," Comput Appl Biosci, vol. 7, pp. 353-357, 1991.
    • (1991) Comput Appl Biosci , vol.7 , pp. 353-357
    • Arrigo, P.1    Giuliano, F.2    Scalia, F.3    Rapallo, A.4    Damiani, G.5
  • 181
    • 0028279918 scopus 로고
    • Self-organized neural maps of human protein sequences
    • E. A. Ferran, B. Pflugfelder, and P. Ferrara, "Self-organized neural maps of human protein sequences," Protein Sci, vol. 3, pp. 507-521, 1994.
    • (1994) Protein Sci , vol.3 , pp. 507-521
    • Ferran, E.A.1    Pflugfelder, B.2    Ferrara, P.3
  • 182
    • 0031703681 scopus 로고    scopus 로고
    • Self-organizing tree-growing network for the classification of protein sequences
    • H. C. Wang, J. Dopazo, L. G. de la Fraga, Y. P. Zhu, and J. M. Carazo, "Self-organizing tree-growing network for the classification of protein sequences," Protein Sci, vol. 7, pp. 2613-2622, 1998.
    • (1998) Protein Sci , vol.7 , pp. 2613-2622
    • Wang, H.C.1    Dopazo, J.2    de la Fraga, L.G.3    Zhu, Y.P.4    Carazo, J.M.5
  • 183
    • 0031595301 scopus 로고    scopus 로고
    • Self-organizing tree-growing network for classifying amino acids
    • H. C.Wang, J. Dopazo, and J. M. Carazo, "Self-organizing tree-growing network for classifying amino acids," Bioinformatics, vol. 14, pp. 376-377, 1998.
    • (1998) Bioinformatics , vol.14 , pp. 376-377
    • Wang, H.C.1    Dopazo, J.2    Carazo, J.M.3
  • 184
    • 0031042985 scopus 로고    scopus 로고
    • Phylogenetic reconstruction using an unsupervised growing neural network that adopts the topology of a phylogenetic tree
    • J. Dopazo and J. M. Carazo, "Phylogenetic reconstruction using an unsupervised growing neural network that adopts the topology of a phylogenetic tree," Journal of Molecular Evolution, vol. 44, pp. 226-233, 1997.
    • (1997) Journal of Molecular Evolution , vol.44 , pp. 226-233
    • Dopazo, J.1    Carazo, J.M.2
  • 185
    • 0141506120 scopus 로고    scopus 로고
    • Characterizing proteolytic cleavage site activity using bio-basis function neural networks
    • R. Thomson, T. C. Hodgman, Z. R. Yang, and A. K. Doyle, "Characterizing proteolytic cleavage site activity using bio-basis function neural networks," Bioinformatics, vol. 19, pp. 1741-1747, 2003.
    • (2003) Bioinformatics , vol.19 , pp. 1741-1747
    • Thomson, R.1    Hodgman, T.C.2    Yang, Z.R.3    Doyle, A.K.4
  • 186
    • 0028715882 scopus 로고
    • DNA sequence analysis using hierarchical ART-based classification networks
    • C. LeBlanc, C. R. Katholi, T. R. Unnasch, and S. I. Hruska, "DNA sequence analysis using hierarchical ART-based classification networks," ISMB, vol. 2, pp. 253-260, 1994.
    • (1994) ISMB , vol.2 , pp. 253-260
    • LeBlanc, C.1    Katholi, C.R.2    Unnasch, T.R.3    Hruska, S.I.4
  • 187
    • 0030779390 scopus 로고    scopus 로고
    • Counter-propagation neural networks for molecular sequence classification: Supervised LVQ and dynamic node allocation
    • C. H. Wu, H. L. Chen, and S. C. Chen, "Counter-propagation neural networks for molecular sequence classification: Supervised LVQ and dynamic node allocation," Applied Intelligence, vol. 7, pp. 27-38, 1997.
    • (1997) Applied Intelligence , vol.7 , pp. 27-38
    • Wu, C.H.1    Chen, H.L.2    Chen, S.C.3
  • 188
    • 0028965444 scopus 로고
    • Identification of protein coding regions in genomic DNA
    • E. E. Snyder and G. D. Stormo, "Identification of protein coding regions in genomic DNA," Journal of Molecular Biology, vol. 248, pp. 1-18, 1995.
    • (1995) Journal of Molecular Biology , vol.248 , pp. 1-18
    • Snyder, E.E.1    Stormo, G.D.2
  • 190
    • 0029872694 scopus 로고    scopus 로고
    • SAGA: Sequence alignment by genetic algorithm
    • C. Notredame and D. G. Higgins, "SAGA: Sequence alignment by genetic algorithm," Nucleic Acids Research, vol. 24, pp. 1515-1524, 1996.
    • (1996) Nucleic Acids Research , vol.24 , pp. 1515-1524
    • Notredame, C.1    Higgins, D.G.2
  • 191
    • 0031829993 scopus 로고    scopus 로고
    • COFFEE: An objective function for multiple sequence alignments
    • C. Notredame, L. Holm, and D. G. Higgins, "COFFEE: An objective function for multiple sequence alignments," Bioinformatics, vol. 14, pp. 407-422, 1998.
    • (1998) Bioinformatics , vol.14 , pp. 407-422
    • Notredame, C.1    Holm, L.2    Higgins, D.G.3
  • 192
    • 0031892789 scopus 로고    scopus 로고
    • A genetic algorithm for maximum-likelihood phylogeny inference using nucleotide sequence data
    • P. O. Lewis, "A genetic algorithm for maximum-likelihood phylogeny inference using nucleotide sequence data," Molecular Biology and Evolution, vol. 15, pp. 277-283, 1998.
    • (1998) Molecular Biology and Evolution , vol.15 , pp. 277-283
    • Lewis, P.O.1
  • 194
    • 0345724915 scopus 로고    scopus 로고
    • Evolutionary computation method for pattern recognition of cis-acting sites
    • D. Howard and K. Benson, "Evolutionary computation method for pattern recognition of cis-acting sites," BioSystems, vol. 72, pp. 19-27, 2003.
    • (2003) BioSystems , vol.72 , pp. 19-27
    • Howard, D.1    Benson, K.2
  • 195
    • 0036677667 scopus 로고    scopus 로고
    • Protein motif extraction with neuro-fuzzy optimization
    • B. C. H. Chang and S. K. Halgamuge, "Protein motif extraction with neuro-fuzzy optimization," Bioinformatics, vol. 18, pp. 1084-1090, 2002.
    • (2002) Bioinformatics , vol.18 , pp. 1084-1090
    • Chang, B.C.H.1    Halgamuge, S.K.2
  • 198
    • 0018110116 scopus 로고
    • Prediction of the secondary structure of proteins from their amino acid sequence
    • P. Chou and G. Fasmann, "Prediction of the secondary structure of proteins from their amino acid sequence," Advances in Enzymology, vol. 47, pp. 45-148, 1978.
    • (1978) Advances in Enzymology , vol.47 , pp. 45-148
    • Chou, P.1    Fasmann, G.2
  • 199
    • 0023803244 scopus 로고
    • Predicting the secondary structure of globular proteins using neural network models
    • N. Qian and T. Sejnowski, "Predicting the secondary structure of globular proteins using neural network models," Journal of Molecular Biology, vol. 202, pp. 865-884, 1988.
    • (1988) Journal of Molecular Biology , vol.202 , pp. 865-884
    • Qian, N.1    Sejnowski, T.2
  • 200
    • 0027291015 scopus 로고
    • Prediction of protein secondary structure at better than 70% accuracy
    • B. Rost and C. Sander, "Prediction of protein secondary structure at better than 70% accuracy," Journal of Molecular Biology, vol. 232, pp. 584-599, 1993.
    • (1993) Journal of Molecular Biology , vol.232 , pp. 584-599
    • Rost, B.1    Sander, C.2
  • 201
    • 0029889988 scopus 로고    scopus 로고
    • PHD: Predicting one-dimensional protein structure by profile-based neural networks
    • B. Rost, "PHD: Predicting one-dimensional protein structure by profile-based neural networks," Methods in Enzymology, vol. 266, pp. 525-539, 1996.
    • (1996) Methods in Enzymology , vol.266 , pp. 525-539
    • Rost, B.1
  • 202
    • 0030810006 scopus 로고    scopus 로고
    • Prediction of protein supersecondary structures based on the artificial neural network method
    • Z. Sun, X. Rao, L. Peng, and D. Xu, "Prediction of protein supersecondary structures based on the artificial neural network method," Protein Eng, vol. 10, pp. 763-769, 1997.
    • (1997) Protein Eng , vol.10 , pp. 763-769
    • Sun, Z.1    Rao, X.2    Peng, L.3    Xu, D.4
  • 203
    • 0025155981 scopus 로고
    • A novel approach to prediction of the 3-dimensional structures of protein backbones by neural networks
    • H. Bohr, J. Bohr, S. Brunak, R. M. J. Cotterill, and H. Fredholm, "A novel approach to prediction of the 3-dimensional structures of protein backbones by neural networks," FEBS Letters, vol. 261, pp. 43-46, 1990.
    • (1990) FEBS Letters , vol.261 , pp. 43-46
    • Bohr, H.1    Bohr, J.2    Brunak, S.3    Cotterill, R.M.J.4    Fredholm, H.5
  • 204
    • 2542428612 scopus 로고
    • Neural network analysis of protein tertiary structure
    • G. L. Wilcox, M. O. Poliac, and M. N. Liebman, "Neural network analysis of protein tertiary structure," Tetrahedron Comp Meth, vol. 3, pp. 191-211, 1991.
    • (1991) Tetrahedron Comp Meth , vol.3 , pp. 191-211
    • Wilcox, G.L.1    Poliac, M.O.2    Liebman, M.N.3
  • 205
    • 0031406438 scopus 로고    scopus 로고
    • Protein distance constraints predicted by neural networks and probability distance functions
    • O. Lund, K. Frimand, J. Gorodkin, H. Bohr, J. Bohr, J. Hansen, and S. Brunak, "Protein distance constraints predicted by neural networks and probability distance functions," Protein Eng, vol. 10, pp. 1241-1248, 1997.
    • (1997) Protein Eng , vol.10 , pp. 1241-1248
    • Lund, O.1    Frimand, K.2    Gorodkin, J.3    Bohr, H.4    Bohr, J.5    Hansen, J.6    Brunak, S.7
  • 206
    • 0029040771 scopus 로고
    • Neural network system for the evaluation of side-chain packing in protein structures
    • M. Milik, A. Kolinski, and J. Skolnick, "Neural network system for the evaluation of side-chain packing in protein structures," Protein Eng, vol. 8, pp. 225-236, 1995.
    • (1995) Protein Eng , vol.8 , pp. 225-236
    • Milik, M.1    Kolinski, A.2    Skolnick, J.3
  • 207
    • 0028906598 scopus 로고
    • Neural networks for secondary structure and structural class predictions
    • J. M. Chandonia and M. Karplus, "Neural networks for secondary structure and structural class predictions," Protein Sci, vol. 4, pp. 275-285, 1995.
    • (1995) Protein Sci , vol.4 , pp. 275-285
    • Chandonia, J.M.1    Karplus, M.2
  • 209
    • 0042674397 scopus 로고    scopus 로고
    • Using a neural network and spatial clustering to predict the location of active sites in enzymes
    • A. Gutteridge, G. J. Bartlett, and J. M. Thornton, "Using a neural network and spatial clustering to predict the location of active sites in enzymes," Journal of Molecular Biology, vol. 330, pp. 719-734, 2003.
    • (2003) Journal of Molecular Biology , vol.330 , pp. 719-734
    • Gutteridge, A.1    Bartlett, G.J.2    Thornton, J.M.3
  • 211
    • 0029984070 scopus 로고    scopus 로고
    • Improving prediction of protein secondary structure using structured neural networks and multiple sequence alignments
    • S. K. Riis and A. Krogh, "Improving prediction of protein secondary structure using structured neural networks and multiple sequence alignments," Journal of Computational Biology, vol. 3, pp. 163-183, 1996.
    • (1996) Journal of Computational Biology , vol.3 , pp. 163-183
    • Riis, S.K.1    Krogh, A.2
  • 212
    • 0033578684 scopus 로고    scopus 로고
    • Protein secondary structure prediction based on position-specific scoring matrices
    • D. T. Jones, "Protein secondary structure prediction based on position-specific scoring matrices," Journal of Molecular Biology, vol. 292, pp. 195-202, 1999.
    • (1999) Journal of Molecular Biology , vol.292 , pp. 195-202
    • Jones, D.T.1
  • 213
    • 1842828899 scopus 로고    scopus 로고
    • Role of evolutionary information in prediction of aromatic-backbone NH interactions in proteins
    • H. Kaur and G. P. S. Raghava, "Role of evolutionary information in prediction of aromatic-backbone NH interactions in proteins," FEBS Letters, vol. 564, pp. 47-57, 2004.
    • (2004) FEBS Letters , vol.564 , pp. 47-57
    • Kaur, H.1    Raghava, G.P.S.2
  • 214
    • 0036568279 scopus 로고    scopus 로고
    • Improving the prediction of protein secondary structure in three and eight classes using recurrent neural networks and profiles
    • G. Pollastri, D. Przybylski, B. Rost, and P. Baldi, "Improving the prediction of protein secondary structure in three and eight classes using recurrent neural networks and profiles," Proteins: Structure, Function, and Genetics, vol. 47, pp. 228-235, 2002.
    • (2002) Proteins: Structure, Function, and Genetics , vol.47 , pp. 228-235
    • Pollastri, G.1    Przybylski, D.2    Rost, B.3    Baldi, P.4
  • 215
    • 0033369033 scopus 로고    scopus 로고
    • Exploiting the past and the future in protein secondary structure prediction
    • P. Baldi, S. Brunak, P. Frasconi, G. Pollastri, and G. Soda, "Exploiting the past and the future in protein secondary structure prediction," Bioinformatics, vol. 15, pp. 937-946, 1999.
    • (1999) Bioinformatics , vol.15 , pp. 937-946
    • Baldi, P.1    Brunak, S.2    Frasconi, P.3    Pollastri, G.4    Soda, G.5
  • 216
    • 0033997724 scopus 로고    scopus 로고
    • Protein structure alignment using a genetic algorithm
    • J. D. Szustakowski and Z. Weng, "Protein structure alignment using a genetic algorithm," Proteins, vol. 38, pp. 428-440, 2000.
    • (2000) Proteins , vol.38 , pp. 428-440
    • Szustakowski, J.D.1    Weng, Z.2
  • 217
    • 0004043766 scopus 로고
    • Genetic algorithms for protein tertiary structure prediction
    • (R. Manner and B. Manderick, eds.), Amsterdam: North Holland
    • S. Schulze-Kremer, "Genetic algorithms for protein tertiary structure prediction," in Parallel Problem Solving from Nature II (R. Manner and B. Manderick, eds.), pp. 391-400, Amsterdam: North Holland, 1992.
    • (1992) Parallel Problem Solving from Nature II , pp. 391-400
    • Schulze-Kremer, S.1
  • 218
    • 0142045029 scopus 로고    scopus 로고
    • Improving genetic algorithms for protein folding simulations by systematic crossover
    • R. Konig and T. Dandekar, "Improving genetic algorithms for protein folding simulations by systematic crossover," BioSystems, vol. 50, pp. 17-25, 1999.
    • (1999) BioSystems , vol.50 , pp. 17-25
    • Konig, R.1    Dandekar, T.2
  • 219
    • 0031556019 scopus 로고    scopus 로고
    • Protein folding simulations with genetic algorithms and a detailed molecular description
    • J. Pedersen and J. Moult, "Protein folding simulations with genetic algorithms and a detailed molecular description," Journal of Molecular Biology, vol. 269, pp. 240-259, 1997.
    • (1997) Journal of Molecular Biology , vol.269 , pp. 240-259
    • Pedersen, J.1    Moult, J.2
  • 223
    • 0031592453 scopus 로고    scopus 로고
    • Predicting conserved water-mediated and polar ligand interactions in proteins using a k-nearest neighbors genetic algorithm
    • M. Raymer, P. Sanschagrin, W. Punch, S. Venkataraman, E. Goodman, and L. Kuhn, "Predicting conserved water-mediated and polar ligand interactions in proteins using a k-nearest neighbors genetic algorithm," Journal of Molecular Biology, vol. 265, pp. 445-464, 1997.
    • (1997) Journal of Molecular Biology , vol.265 , pp. 445-464
    • Raymer, M.1    Sanschagrin, P.2    Punch, W.3    Venkataraman, S.4    Goodman, E.5    Kuhn, L.6
  • 224
    • 0028858499 scopus 로고
    • De novo design of the hydrophobic cores of proteins
    • J. Desjarlais and T. Handel, "De novo design of the hydrophobic cores of proteins," Protein Sci, vol. 4, pp. 2006-2018, 1995.
    • (1995) Protein Sci , vol.4 , pp. 2006-2018
    • Desjarlais, J.1    Handel, T.2
  • 226
    • 0027596624 scopus 로고
    • Using knowledge-based neural network to improve algorithms: Refining Chou-Fasman algorithm for protein folding
    • R. Maclin and J. W. Shavlik, "Using knowledge-based neural network to improve algorithms: Refining Chou-Fasman algorithm for protein folding," Machine Learning, vol. 11, pp. 195-215, 1993.
    • (1993) Machine Learning , vol.11 , pp. 195-215
    • Maclin, R.1    Shavlik, J.W.2
  • 227
    • 0029029127 scopus 로고
    • LGANN: A parallel system combining a local genetic algorithm and neural networks for the prediction of secondary structure of proteins
    • F. Vivarelli, G. Giusti, M. Villani, R. Campanini, P. Fariselli, M. Compiani, and R. Casadio, "LGANN: A parallel system combining a local genetic algorithm and neural networks for the prediction of secondary structure of proteins," Comput Appl Biosci, vol. 11, pp. 253-260, 1995.
    • (1995) Comput Appl Biosci , vol.11 , pp. 253-260
    • Vivarelli, F.1    Giusti, G.2    Villani, M.3    Campanini, R.4    Fariselli, P.5    Compiani, M.6    Casadio, R.7
  • 229
    • 0034782618 scopus 로고    scopus 로고
    • Model based clustering and data transformations for gene expression data
    • K. Y. Yeung, C. Fraley, A. Murua, A. E. Raftery, and W. L. Ruzzo, "Model based clustering and data transformations for gene expression data," Bioinformatics, vol. 17, pp. 977-987, 2001.
    • (2001) Bioinformatics , vol.17 , pp. 977-987
    • Yeung, K.Y.1    Fraley, C.2    Murua, A.3    Raftery, A.E.4    Ruzzo, W.L.5
  • 231
    • 17944394324 scopus 로고    scopus 로고
    • Fuzzy c-means method for clustering microarray data
    • D. Dembele and P. Kastner, "Fuzzy c-means method for clustering microarray data," Bioinformatics, vol. 19, pp. 973-980, 2003.
    • (2003) Bioinformatics , vol.19 , pp. 973-980
    • Dembele, D.1    Kastner, P.2
  • 232
    • 0037057374 scopus 로고    scopus 로고
    • Exploring the conditional coregulation of yeast gene expression through fuzzy k-means clustering
    • research0059.1-0059.22
    • A. P. Gasch and M. B. Eisen, "Exploring the conditional coregulation of yeast gene expression through fuzzy k-means clustering," Genome Biology, vol. 3, pp. research0059.1-0059.22, 2002.
    • (2002) Genome Biology , vol.3
    • Gasch, A.P.1    Eisen, M.B.2
  • 237
    • 0042863923 scopus 로고    scopus 로고
    • Analysis of gene expression data using self-organizing maps
    • P. Toronen, M. Kolehmainen, G. Wong, and E. Castŕen, "Analysis of gene expression data using self-organizing maps," FEBS Letters, vol. 451, pp. 142-146, 1999.
    • (1999) FEBS Letters , vol.451 , pp. 142-146
    • Toronen, P.1    Kolehmainen, M.2    Wong, G.3    Castŕen, E.4
  • 238
    • 0035108235 scopus 로고    scopus 로고
    • A hierarchical unsupervised growing neural network for clustering gene expression patterns
    • J. Herrero, A. Valencia, and J. Dopazo, "A hierarchical unsupervised growing neural network for clustering gene expression patterns," Bioinformatics, vol. 17, pp. 126-136, 2001.
    • (2001) Bioinformatics , vol.17 , pp. 126-136
    • Herrero, J.1    Valencia, A.2    Dopazo, J.3
  • 239
    • 0012321068 scopus 로고    scopus 로고
    • Binary tree-structured vector quantization approach to clustering and visualizing microarray data
    • M. Sultan, D. A. Wigle, C. A. Cumbaa, M. Maziarz, J. Glasgow, M. S. Tsao, and I. Jurisica, "Binary tree-structured vector quantization approach to clustering and visualizing microarray data," Bioinformatics, vol. 18 Suppl. 1, pp. S111-S119, 2002.
    • (2002) Bioinformatics , vol.18 , pp. S111-S119
    • Sultan, M.1    Wigle, D.A.2    Cumbaa, C.A.3    Maziarz, M.4    Glasgow, J.5    Tsao, M.S.6    Jurisica, I.7
  • 240
    • 0141686299 scopus 로고    scopus 로고
    • Classifying gene expression data of cancer using classifier ensemble with mutually exclusive features
    • S. B. Cho and J. Ryu, "Classifying gene expression data of cancer using classifier ensemble with mutually exclusive features," Proceedings of the IEEE, vol. 90, pp. 1744-1753, 2002.
    • (2002) Proceedings of the IEEE , vol.90 , pp. 1744-1753
    • Cho, S.B.1    Ryu, J.2
  • 241
    • 12244256070 scopus 로고    scopus 로고
    • Pattern identification and classification in gene expression data using an autoassociative neural network model
    • S. Bicciato, M. Pandin, G. Didon` e, and C. Di Bello, "Pattern identification and classification in gene expression data using an autoassociative neural network model," Biotechnology and Bioengineering, vol. 81, pp. 594-606, 2003.
    • (2003) Biotechnology and Bioengineering , vol.81 , pp. 594-606
    • Bicciato, S.1    Pandin, M.2    G.3    Didon4    Di Bello, C.6
  • 243
    • 0345724886 scopus 로고    scopus 로고
    • Reliable classification of two-class cancer data using evolutionary algorithms
    • K. Deb and A. Raji Reddy, "Reliable classification of two-class cancer data using evolutionary algorithms," BioSystems, vol. 72, pp. 111-129, 2003.
    • (2003) BioSystems , vol.72 , pp. 111-129
    • Deb, K.1    Raji Reddy, A.2
  • 245
    • 0037255041 scopus 로고    scopus 로고
    • Evolutionary algorithms for finding optimal gene sets in microarray prediction
    • J. M. Deutsch, "Evolutionary algorithms for finding optimal gene sets in microarray prediction," Bioinformatics, vol. 19, pp. 45-52, 2003.
    • (2003) Bioinformatics , vol.19 , pp. 45-52
    • Deutsch, J.M.1
  • 246
    • 26444479778 scopus 로고
    • Optimization by simulated annealing
    • S. Kirkpatrick, C. D. Gelatt Jr., and M. P. Vecchi, "Optimization by simulated annealing," Science, vol. 220, pp. 671-680, 1983.
    • (1983) Science , vol.220 , pp. 671-680
    • Kirkpatrick, S.1    Gelatt, C.D.2    Vecchi, M.P.3
  • 247
    • 0035014159 scopus 로고    scopus 로고
    • Analysis of temporal gene expression profiles: Clustering by simulated annealing and determining the optimal number of clusters
    • A. V. Lukashin and R. Fuchs, "Analysis of temporal gene expression profiles: Clustering by simulated annealing and determining the optimal number of clusters," Bioinformatics, vol. 17, pp. 405-414, 2001.
    • (2001) Bioinformatics , vol.17 , pp. 405-414
    • Lukashin, A.V.1    Fuchs, R.2
  • 249
    • 33748417841 scopus 로고    scopus 로고
    • Multi-objective evolutionary biclustering of gene expression data
    • S. Mitra and H. Banka, "Multi-objective evolutionary biclustering of gene expression data," Pattern Recognition, 2006.
    • (2006) Pattern Recognition
    • Mitra, S.1    Banka, H.2
  • 252
    • 77957922440 scopus 로고    scopus 로고
    • Classification of gene expression data in an ontology
    • Berlin: Springer-Verlag
    • H. Midelfart, A. Lægreid, and J. Komorowski, Classification of gene expression data in an ontology, vol. 2199 of Lecture Notes in Computer Science, pp. 186-194. Berlin: Springer-Verlag, 2001.
    • (2001) Lecture Notes in Computer Science , vol.2199 , pp. 186-194
    • Midelfart, H.1    Lægreid, A.2    Komorowski, J.3
  • 253
    • 0026408256 scopus 로고
    • Fuzzy ART: fast stable learning and categorization of analog patterns by an adaptive resonance system
    • G. A. Carpenter, S. Grossberg, and D. B. Rosen, "Fuzzy ART: fast stable learning and categorization of analog patterns by an adaptive resonance system," Neural Networks, vol. 4, pp. 759-771, 1991.
    • (1991) Neural Networks , vol.4 , pp. 759-771
    • Carpenter, G.A.1    Grossberg, S.2    Rosen, D.B.3
  • 254
    • 0036678783 scopus 로고    scopus 로고
    • Analysis of expression profile using fuzzy adaptive resonance theory
    • S. Tomida, T. Hanai, H. Honda, and T. Kobayashi, "Analysis of expression profile using fuzzy adaptive resonance theory," Bioinformatics, vol. 18, pp. 1073-1083, 2002.
    • (2002) Bioinformatics , vol.18 , pp. 1073-1083
    • Tomida, S.1    Hanai, T.2    Honda, H.3    Kobayashi, T.4
  • 255
    • 0042168791 scopus 로고    scopus 로고
    • Evolving connectionist systems for knowledge discovery from gene expression data of cancer tissue
    • M. E. Futschik, A. Reeve, and N. Kasabov, "Evolving connectionist systems for knowledge discovery from gene expression data of cancer tissue," Artificial Intelligence in Medicine, vol. 28, pp. 165-189, 2003.
    • (2003) Artificial Intelligence in Medicine , vol.28 , pp. 165-189
    • Futschik, M.E.1    Reeve, A.2    Kasabov, N.3
  • 258
    • 4544248169 scopus 로고    scopus 로고
    • Interval set clustering of Web users with rough k-means
    • Dept. of Mathematics and Computer Science, St. Mary's University, Halifax, Canada
    • P. Lingras and C. West, "Interval set clustering of Web users with rough k-means," Technical Report No. 2002-002, Dept. of Mathematics and Computer Science, St. Mary's University, Halifax, Canada, 2002.
    • (2002) Technical Report No. 2002-002
    • Lingras, P.1    West, C.2
  • 259
    • 4544352979 scopus 로고    scopus 로고
    • An evolutionary rough partitive clustering
    • S. Mitra, "An evolutionary rough partitive clustering," Pattern Recognition Letters, vol. 25, pp. 1439-1449, 2004.
    • (2004) Pattern Recognition Letters , vol.25 , pp. 1439-1449
    • Mitra, S.1
  • 261
    • 0035082045 scopus 로고    scopus 로고
    • Neural network model of gene expression
    • J. Vohradsky, "Neural network model of gene expression," FASEB Journal, vol. 15, pp. 846-854, 2001.
    • (2001) FASEB Journal , vol.15 , pp. 846-854
    • Vohradsky, J.1
  • 262
    • 0344464762 scopus 로고    scopus 로고
    • Sensitivity and specificity of inferring genetic regulatory interactions from microarray experiments with dynamic bayesian networks
    • D. Husmeier, "Sensitivity and specificity of inferring genetic regulatory interactions from microarray experiments with dynamic bayesian networks," Bioin-formatics, vol. 19, pp. 2271-2282, 2003.
    • (2003) Bioin-formatics , vol.19 , pp. 2271-2282
    • Husmeier, D.1
  • 263
    • 0042627711 scopus 로고    scopus 로고
    • Clustering gene expression data using adaptive double self-organizing map
    • H. Ressom, D. Wang, and P. Natarajan, "Clustering gene expression data using adaptive double self-organizing map," Physiol. Genomics, vol. 14, pp. 35-46, 2003.
    • (2003) Physiol. Genomics , vol.14 , pp. 35-46
    • Ressom, H.1    Wang, D.2    Natarajan, P.3
  • 264
    • 0037461033 scopus 로고    scopus 로고
    • Dynamic modeling of genetic networks using genetic algorithm and S-system
    • S. Kikuchi, D. Tominaga, M. Arita, K. Takahashi, and M. Tomita, "Dynamic modeling of genetic networks using genetic algorithm and S-system," Bioinformatics, vol. 19, pp. 643-650, 2003.
    • (2003) Bioinformatics , vol.19 , pp. 643-650
    • Kikuchi, S.1    Tominaga, D.2    Arita, M.3    Takahashi, K.4    Tomita, M.5
  • 265
    • 1642403354 scopus 로고    scopus 로고
    • Identification of genetic networks
    • M. Xiong, J. Li, and X. Fang, "Identification of genetic networks," Genetics, vol. 166, pp. 1037-1052, 2004.
    • (2004) Genetics , vol.166 , pp. 1037-1052
    • Xiong, M.1    Li, J.2    Fang, X.3
  • 266
    • 0642368712 scopus 로고    scopus 로고
    • Optimization of neural network architecture using genetic programming improves detection and modeling of gene-gene interactions in studies of human diseases
    • M. D. Ritchie, B. C. White, J. S. Parker, L. Hahn, and J. H. Moore, "Optimization of neural network architecture using genetic programming improves detection and modeling of gene-gene interactions in studies of human diseases," BMC Bioinformatics, vol. 4, pp. 28-36, 2003.
    • (2003) BMC Bioinformatics , vol.4 , pp. 28-36
    • Ritchie, M.D.1    White, B.C.2    Parker, J.S.3    Hahn, L.4    Moore, J.H.5
  • 267
    • 15344349017 scopus 로고    scopus 로고
    • A hybrid promoter analysis methodology for prokaryotic genomes
    • V. Cotik, R. Romero Zaliz, and I. Zwir, "A hybrid promoter analysis methodology for prokaryotic genomes," Fuzzy Sets and Systems, vol. 152, pp. 83-102, 2005.
    • (2005) Fuzzy Sets and Systems , vol.152 , pp. 83-102
    • Cotik, V.1    Romero Zaliz, R.2    Zwir, I.3
  • 269
    • 0032616683 scopus 로고    scopus 로고
    • Identification of genetic networks from a small number of gene expression patterns under the boolean network model
    • T. Akutsu, S. Miyano, and S. Kuhara. Identification of genetic networks from a small number of gene expression patterns under the boolean network model. In Proceedings of the Pacific Symposium on Biocomputing, pages 17-28, 1999.
    • (1999) Proceedings of the Pacific Symposium on Biocomputing , pp. 17-28
    • Akutsu, T.1    Miyano, S.2    Kuhara, S.3
  • 270
    • 2942572926 scopus 로고    scopus 로고
    • Quantifying the relationship between co-expression, co-regulation and gene function
    • D. J. Allocco, I. S. Kohane, and A. J. Butte. Quantifying the relationship between co-expression, co-regulation and gene function. BMC Bioinformatics, 5:18, 2007.
    • (2007) BMC Bioinformatics , vol.5 , Issue.18
    • Allocco, D.J.1    Kohane, I.S.2    Butte, A.J.3
  • 271
    • 0002759539 scopus 로고
    • Unsupervised learning of multiple motifs in biopolymers using expectation maximization
    • T. L. Bailey and C. Elkan. Unsupervised learning of multiple motifs in biopolymers using expectation maximization. Machine Learning, 21:51-80, 1995.
    • (1995) Machine Learning , vol.21 , pp. 51-80
    • Bailey, T.L.1    Elkan, C.2
  • 272
    • 0034948896 scopus 로고    scopus 로고
    • A bayesian framework for the analysis of microarray expression data: regularized t -test and statistical inferences of gene changes
    • P. Baldi and A. D. Long. A bayesian framework for the analysis of microarray expression data: regularized t -test and statistical inferences of gene changes. Bioinformatics, 17(6):509-519, 2001.
    • (2001) Bioinformatics , vol.17 , Issue.6 , pp. 509-519
    • Baldi, P.1    Long, A.D.2
  • 275
    • 15944361900 scopus 로고    scopus 로고
    • Informative structure priors: Joint learning of dynamic regulatory networks from multiple types of data
    • A. Bernard and A. J. Hartemink. Informative structure priors: Joint learning of dynamic regulatory networks from multiple types of data. In Pacific Symposium on Biocomputing 10, pages 459-470, 2005.
    • (2005) Pacific Symposium on Biocomputing , vol.10 , pp. 459-470
    • Bernard, A.1    Hartemink, A.J.2
  • 276
    • 0036107903 scopus 로고    scopus 로고
    • Discovery of regulatory elements by a computational method for phylogenetic footprinting
    • M. Blanchette and M. Tompa. Discovery of regulatory elements by a computational method for phylogenetic footprinting. Genome Research, 12(5):739-748, 2002.
    • (2002) Genome Research , vol.12 , Issue.5 , pp. 739-748
    • Blanchette, M.1    Tompa, M.2
  • 277
    • 0037316303 scopus 로고    scopus 로고
    • A comparison of normalization methods for high density oligonucleotide array data based on variance and bias
    • B. M. Bolstad, R. A. Irizarry, M. Astrand, and T. P. Speed. A comparison of normalization methods for high density oligonucleotide array data based on variance and bias. Bioinformatics, 19(2):185-193, 2003.
    • (2003) Bioinformatics , vol.19 , Issue.2 , pp. 185-193
    • Spee, P.1
  • 278
    • 0032413411 scopus 로고    scopus 로고
    • Predicting gene regulatory elements in silico on a genomic scale
    • A. Brazma, I. Jonassen, J. Vilo, and E. Ukkonen. Predicting gene regulatory elements in silico on a genomic scale. Genome Research, 8:1202-1215, 1998.
    • (1998) Genome Research , vol.8 , pp. 1202-1215
    • Brazma, A.1    Jonassen, I.2    Vilo, J.3    Ukkonen, E.4
  • 279
    • 4344571581 scopus 로고    scopus 로고
    • Rank products: a simple, yet powerful, new method to detect differentially regulated genes in replicated microarray experiments
    • R. Breitling, P. Armengaud, A. Amtmann, and P. Herzyk. Rank products: a simple, yet powerful, new method to detect differentially regulated genes in replicated microarray experiments. FEBS Letters, 573(1-3):83-92, 2004.
    • (2004) FEBS Letters , vol.573 , Issue.1-3 , pp. 83-92
    • Breitling, R.1    Armengaud, P.2    Amtmann, A.3    Herzyk, P.4
  • 280
    • 0742306815 scopus 로고    scopus 로고
    • Computational prediction of transcription factor bfinding site locations
    • M. L. Bulyk. Computational prediction of transcription factor bfinding site locations. Genome Biology, 5, 2003.
    • (2003) Genome Biology , vol.5
    • Bulyk, M.L.1
  • 281
    • 0031586003 scopus 로고    scopus 로고
    • Prediction of complete gene structures in human genomic dna
    • C. Burge and S. Karlin. Prediction of complete gene structures in human genomic dna. Journal of Molecular Biology, 268:78-94, 1997.
    • (1997) Journal of Molecular Biology , vol.268 , pp. 78-94
    • Burge, C.1    Karlin, S.2
  • 285
    • 0034069495 scopus 로고    scopus 로고
    • Gene ontology: tool for the unification of biology
    • The Gene Ontology Consortium. Gene ontology: tool for the unification of biology. Nature Genetics, 25:25-29, 2000.
    • (2000) Nature Genetics , vol.25 , pp. 25-29
  • 286
    • 0031585995 scopus 로고    scopus 로고
    • A statistical model for locating regulatory regions in genomic dna
    • E. M. Crowley, K. Roeder, and M. Bina. A statistical model for locating regulatory regions in genomic dna. Journal of Molecular Biology, 268(1):8-14, 1997.
    • (1997) Journal of Molecular Biology , vol.268 , Issue.1 , pp. 8-14
    • Crowley, E.M.1    Roeder, K.2    Bina, M.3
  • 291
    • 0032568590 scopus 로고    scopus 로고
    • Estimation of evolutionary distances under stationary and nonstationary models of nucleotide substitution
    • X. Gu and W.-H. Li. Estimation of evolutionary distances under stationary and nonstationary models of nucleotide substitution. Proceedings of the National Academy of Sciences, 95(11):5899-5905, 1998.
    • (1998) Proceedings of the National Academy of Sciences , vol.95 , Issue.11 , pp. 5899-5905
    • Gu, X.1    Li, W.-H.2
  • 292
    • 0029977162 scopus 로고    scopus 로고
    • Using substitution probabilities to improve position-specific scoring matrices
    • J. G. Henikoff and S. Henikoff. Using substitution probabilities to improve position-specific scoring matrices. CABIOS, 12(2):135-143, 1996.
    • (1996) CABIOS , vol.12 , Issue.2 , pp. 135-143
    • Henikoff, J.G.1    Henikoff, S.2
  • 293
    • 0024234855 scopus 로고
    • Clustal: a package for performing multiple sequence alignment on a microcomputer
    • D. G. Higgins and P. M. Sharp. Clustal: a package for performing multiple sequence alignment on a microcomputer. Gene, 73:237-244, 1988.
    • (1988) Gene , vol.73 , pp. 237-244
    • Higgins, D.G.1    Sharp, P.M.2
  • 294
    • 0026775123 scopus 로고
    • An assessment of neural network and statistical approaches for prediction of E. coli promoter sites
    • P. B. Horton and M. Kanehisa. An assessment of neural network and statistical approaches for prediction of E. coli promoter sites. Nucleic Acids Research, 20:4331-4338, 1992.
    • (1992) Nucleic Acids Research , vol.20 , pp. 4331-4338
    • Horton, P.B.1    Kanehisa, M.2
  • 297
    • 36249026435 scopus 로고    scopus 로고
    • Reverse engineering discrete dynamical systems from data sets with random input vectors
    • W. Just. Reverse engineering discrete dynamical systems from data sets with random input vectors. Journal of Computational Biology, 13(8):1435-1456, 2006.
    • (2006) Journal of Computational Biology , vol.13 , Issue.8 , pp. 1435-1456
    • Just, W.1
  • 299
    • 24644470505 scopus 로고    scopus 로고
    • Ontological analysis of gene expression data: current tools, limitations and open profilems
    • P. Khatri and S. Draghici. Ontological analysis of gene expression data: current tools, limitations and open profilems. Bioinformatics, 21(18):3587-3595, 2005.
    • (2005) Bioinformatics , vol.21 , Issue.18 , pp. 3587-3595
    • Khatri, P.1    Draghici, S.2
  • 300
    • 0031616241 scopus 로고    scopus 로고
    • REVEAL, a general reverse-engineering algorithm for inference of genetic network architectures
    • S. Liang, S. Fuhrman, and R. Somogyi. REVEAL, a general reverse-engineering algorithm for inference of genetic network architectures. In Proceedings of the Pacific Symposium on Biocomputing, pages 18-29, 1998.
    • (1998) Proceedings of the Pacific Symposium on Biocomputing , pp. 18-29
    • Liang, S.1    Fuhrman, S.2    Somogyi, R.3
  • 301
    • 0036254463 scopus 로고    scopus 로고
    • Modeling stem cell development by retrospective analysis of gene expression profiles in single progenitor-derived colonies
    • N. Madras, A. L. Gibbs, Y. Zhou, P. W. Zandstra, and J. E. Aubin. Modeling stem cell development by retrospective analysis of gene expression profiles in single progenitor-derived colonies. Stem Cells, 20:230-240, 2002.
    • (2002) Stem Cells , vol.20 , pp. 230-240
    • Madras, N.1    Gibbs, A.L.2    Zhou, Y.3    Zandstra, P.W.4    Aubin, J.E.5
  • 303
    • 0004158155 scopus 로고    scopus 로고
    • Modelling gene expression data using dynamic bayesian networks
    • K. Murphy and S.Mian. Modelling gene expression data using dynamic bayesian networks. 1999.
    • (1999)
    • Murphy, K.1    Mian, S.2
  • 305
    • 0014757386 scopus 로고
    • A general method applicable to the search for similarities in the amino acid sequence of two proteins
    • S. Needleman and C. Wunsch. A general method applicable to the search for similarities in the amino acid sequence of two proteins. Journal of Molecular Biology, 48(3):443-53, 1970.
    • (1970) Journal of Molecular Biology , vol.48 , Issue.3 , pp. 443-453
    • Needleman, S.1    Wunsch, C.2
  • 307
    • 33645998778 scopus 로고    scopus 로고
    • Dynamical properties of model gene networks and implications for the inverse profilem
    • T. J. Perkins, M. Hallett, and L. Glass. Dynamical properties of model gene networks and implications for the inverse profilem. BioSystems, 84(2):115-123, 2006.
    • (2006) BioSystems , vol.84 , Issue.2 , pp. 115-123
    • Perkins, T.J.1    Hallett, M.2    Glass, L.3
  • 309
    • 33646901020 scopus 로고    scopus 로고
    • Reverse engineering the gap gene network of Drosophila melanogaster
    • Theodore J. Perkins, Johannes Jaeger, John Reinitz, and Leon Glass. Reverse engineering the gap gene network of Drosophila melanogaster. PLoS Computational Biology, 2(5):e51, 2006.
    • (2006) PLoS Computational Biology , vol.2 , Issue.5
    • Perkins, T.J.1    Jaeger, J.2    Reinitz, J.3    Glass, L.4
  • 310
    • 33646338193 scopus 로고    scopus 로고
    • MinReg: A scalable algorithm for learning parsimonious regulatory networks in yeast and mammals
    • D. Peer, A. Tanay, and A. Regev. MinReg: A scalable algorithm for learning parsimonious regulatory networks in yeast and mammals. Journal of Machine Learning Research, 7:167-189, 2006.
    • (2006) Journal of Machine Learning Research , vol.7 , pp. 167-189
    • Peer, D.1    Tanay, A.2    Regev, A.3
  • 311
    • 15944418607 scopus 로고    scopus 로고
    • Random forest similarity for protein-protein interaction prediction from multiple sources
    • Y. Qi, J. Klein-Seetharaman, and Z. Bar-Joseph. Random forest similarity for protein-protein interaction prediction from multiple sources. In Pacific Symposium on Biocomputing 10, pages 531-542, 2005.
    • (2005) Pacific Symposium on Biocomputing , vol.10 , pp. 531-542
    • Qi, Y.1    Klein-Seetharaman, J.2    Bar-Joseph, Z.3
  • 313
    • 0031684427 scopus 로고    scopus 로고
    • Combinatorial pattern discovery in biological sequences: the teiresias algorithm
    • I. RIgoutsos and A. Floratos. Combinatorial pattern discovery in biological sequences: the teiresias algorithm. Bioinformatics, 14(1):55-67, 1998.
    • (1998) Bioinformatics , vol.14 , Issue.1 , pp. 55-67
    • RIgoutsos, I.1    Floratos, A.2
  • 314
    • 0031787969 scopus 로고    scopus 로고
    • Finding dna regulatory motifs within unaligned noncoding sequences clustered by whole-genome mrna quantitation
    • F. P. Roth, J. D. Hughes, P. W. Estep, and G. M. Church. Finding dna regulatory motifs within unaligned noncoding sequences clustered by whole-genome mrna quantitation. Nature Biotechnology, 16:939-945, 1998.
    • (1998) Nature Biotechnology , vol.16 , pp. 939-945
    • Roth, F.P.1    Hughes, J.D.2    Estep, P.W.3    Church, G.M.4
  • 315
    • 0034065724 scopus 로고    scopus 로고
    • Ab initio gene finding in Drosophila genomic dna
    • A. A. Salamov and V. V. Solovyev. Ab initio gene finding in Drosophila genomic dna. Genome Research, 10:516-522, 2000.
    • (2000) Genome Research , vol.10 , pp. 516-522
    • Salamov, A.A.1    Solovyev, V.V.2
  • 317
    • 0037941585 scopus 로고    scopus 로고
    • Module networks: identifying regulatory modules and their condition-specific regulators from gene expression data
    • E. Segal, M. Shapira, A. Regev, D. Peer, D. Botstein, D. Koller, and N. Friedman. Module networks: identifying regulatory modules and their condition-specific regulators from gene expression data. Nature Genetics, 34(2):166-76, 2003.
    • (2003) Nature Genetics , vol.34 , Issue.2 , pp. 166-176
    • Segal, E.1    Shapira, M.2    Regev, A.3    Peer, D.4    Botstein, D.5    Koller, D.6    Friedman, N.7
  • 318
    • 0842309161 scopus 로고    scopus 로고
    • Discovering molecular pathways from protein interaction and gene expression data
    • E. Segal, H.Wang, and D. Koller. Discovering molecular pathways from protein interaction and gene expression data. Bioinformatics, 19(1):i264-i272, 2003.
    • (2003) Bioinformatics , vol.19 , Issue.1 , pp. 1264-1272
    • Segal, E.1    Wang, H.2    Koller, D.3
  • 319
    • 0019887799 scopus 로고
    • Identification of common molecular subsequences
    • T. F. Smith and M. S. Waterman. Identification of common molecular subsequences. Journal of Molecular Biology, 147:195-197, 1981.
    • (1981) Journal of Molecular Biology , vol.147 , pp. 195-197
    • Smith, T.F.1    Waterman, M.S.2
  • 321
    • 0034072450 scopus 로고    scopus 로고
    • Dna bfinding sites: representation and discovery
    • G. D. Stormo. Dna bfinding sites: representation and discovery. Bioinformatics, 16(1):16-23, 2000.
    • (2000) Bioinformatics , vol.16 , Issue.1 , pp. 16-23
    • Stormo, G.D.1
  • 322
    • 0023057575 scopus 로고
    • Quantitative analysis of the relationship between nucleotide sequence and functional activity
    • G. D. Stormo, T. D. Schneider, and L. Gold. Quantitative analysis of the relationship between nucleotide sequence and functional activity. Nucleic acids research, 14:6661-6679, 1986.
    • (1986) Nucleic acids research , vol.14 , pp. 6661-6679
    • Stormo, G.D.1    Schneider, T.D.2    Gold, L.3
  • 324
    • 0027968068 scopus 로고
    • Clustal w: Improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice
    • J. D. Thompson, D. G. Higgins, and T. J. Gibson. Clustal w: Improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice. Nucleic Acids Research, 22:4673-4680, 1994.
    • (1994) Nucleic Acids Research , vol.22 , pp. 4673-4680
    • Thompson, J.D.1    Higgins, D.G.2    Gibson, T.J.3
  • 326
    • 0028679709 scopus 로고
    • On the complexity of multiple sequence alignment
    • L. Wang and T. Jiang. On the complexity of multiple sequence alignment. Journal of Computational Biology, 1:337-348, 1994.
    • (1994) Journal of Computational Biology , vol.1 , pp. 337-348
    • Wang, L.1    Jiang, T.2
  • 327
    • 0032848435 scopus 로고    scopus 로고
    • Candidate regulatory sequence elements for cell cycle-dependent transcription in Saccharomyces cerevisia
    • T. G.Wolfsberg, A. E. Gabrielian, M. J. Campbell, R. J. Cho, J. L. Spouge, and D. Landsman. Candidate regulatory sequence elements for cell cycle-dependent transcription in Saccharomyces cerevisia. Genome research, 9(8):775-792, 1999.
    • (1999) Genome research , vol.9 , Issue.8 , pp. 775-792
    • Wolfsberg, T.G.1    Gabrielian, A.E.2    Campbell, M.J.3    Cho, R.J.4    Spouge, J.L.5    Landsman, D.6
  • 330
    • 3543140009 scopus 로고
    • Prediction of protein secondary structure at better than 70% accuracy
    • J Mol Biol.
    • B. Rost and C. Sander (1993). Prediction of protein secondary structure at better than 70% accuracy. J Mol Biol.
    • (1993)
    • Rost, B.1    Sander, C.2
  • 335
    • 0000127585 scopus 로고
    • Automated refinement of protein models
    • V. Lamzin and K. Wilson (1993). Automated refinement of protein models. Acta Cryst.
    • (1993) Acta Cryst.
    • Lamzin, V.1    Wilson, K.2
  • 336
    • 0030809260 scopus 로고    scopus 로고
    • wARP: Improvement and extension of crystallographic phases by weighted averaging of multiple refined dummy atomic models
    • A. Perrakis, T. Sixma, K. Wilson, and V. Lamzin (1997). wARP: Improvement and extension of crystallographic phases by weighted averaging of multiple refined dummy atomic models. Acta Cryst.
    • (1997) Acta Cryst.
    • Perrakis, A.1    Sixma, T.2    Wilson, K.3    Lamzin, V.4
  • 337
    • 0036077402 scopus 로고    scopus 로고
    • ARP/wARP's model-building algorithms: the main chain
    • R. Morris, A. Perrakis, and V. Lamzin (2002). ARP/wARP's model-building algorithms: the main chain. Acta Cryst.
    • (2002) Acta Cryst.
    • Morris, R.1    Perrakis, A.2    Lamzin, V.3
  • 338
    • 0015956607 scopus 로고
    • Three-dimensional pattern recognition
    • J. Greer (1974). Three-dimensional pattern recognition. J Mol Biol.
    • (1974) J Mol Biol.
    • Greer, J.1
  • 340
    • 0035788111 scopus 로고    scopus 로고
    • Fast Fourier feature recognition
    • K. Cowtan (2001). Fast Fourier feature recognition. Acta Cryst.
    • (2001) Acta Cryst.
    • Cowtan, K.1
  • 341
    • 0035177219 scopus 로고    scopus 로고
    • A number of real-space torsion-angle refinement techniques for proteins, nucleic acids, ligands and solvent
    • T. Oldfield (2001). A number of real-space torsion-angle refinement techniques for proteins, nucleic acids, ligands and solvent. Acta Cryst.
    • (2001) Acta Cryst.
    • Oldfield, T.1
  • 342
    • 0346349900 scopus 로고    scopus 로고
    • Automated main-chain model-building by template-matching and iterative fragment extension
    • T. Terwilliger (2002). Automated main-chain model-building by template-matching and iterative fragment extension. Acta Cryst.
    • (2002) Acta Cryst.
    • Terwilliger, T.1
  • 343
    • 0346349900 scopus 로고    scopus 로고
    • Automated side-chain model-building and sequence assignment by template-matching
    • T. Terwilliger (2002). Automated side-chain model-building and sequence assignment by template-matching. Acta Cryst.
    • (2002) Acta Cryst.
    • Terwilliger, T.1
  • 344
    • 0034929414 scopus 로고    scopus 로고
    • A new software routine that automates the fitting of protein X-ray crystallographic electron density maps
    • D. Levitt (2001). A new software routine that automates the fitting of protein X-ray crystallographic electron density maps. Acta Cryst.
    • (2001) Acta Cryst.
    • Levitt, D.1
  • 345
    • 0033291887 scopus 로고    scopus 로고
    • TEXTAL: A pattern recognition system for interpreting electron density maps
    • T. Ioerger, T. Holton, J. Christopher, and J. Sacchettini (1999). TEXTAL: A pattern recognition system for interpreting electron density maps. Proc ISMB.
    • (1999) Proc ISMB.
    • Ioerger, T.1    Holton, T.2    Christopher, J.3    Sacchettini, J.4
  • 346
    • 0036898446 scopus 로고    scopus 로고
    • Automatic modeling of protein backbones in electron density maps via prediction of C-alpha coordinates
    • T. Ioerger and J. Sacchettini (2002). Automatic modeling of protein backbones in electron density maps via prediction of C-alpha coordinates. Acta Cryst.
    • (2002) Acta Cryst.
    • Ioerger, T.1    Sacchettini, J.2
  • 348
    • 34748835615 scopus 로고    scopus 로고
    • A probabilistic approach to protein backbone tracing in electron density maps
    • F. DiMaio, J. Shavlik, and G. Phillips (2006). A probabilistic approach to protein backbone tracing in electron density maps. Proc ISMB.
    • (2006) Proc ISMB.
    • DiMaio, F.1    Shavlik, J.2    Phillips, G.3
  • 349
    • 14044272805 scopus 로고    scopus 로고
    • Weighting features to recognize 3D patterns of electron density in X-ray protein crystallography
    • K. Gopal, T. Romo, J. Sacchettini, and T. Ioerger (2004). Weighting features to recognize 3D patterns of electron density in X-ray protein crystallography. Proc CSB.
    • (2004) Proc CSB.
    • Gopal, K.1    Romo, T.2    Sacchettini, J.3    Ioerger, T.4
  • 351
    • 0002425879 scopus 로고    scopus 로고
    • Loopy belief propagation for approximate inference: An empirical study
    • K. Murphy, Y. Weiss, and M. Jordan (1999). Loopy belief propagation for approximate inference: An empirical study. Proc. UAI.
    • (1999) Proc. UAI.
    • Murphy, K.1    Weiss, Y.2    Jordan, M.3
  • 352
    • 33748433501 scopus 로고    scopus 로고
    • Special Issue on Bioinformatics
    • "Special Issue on Bioinformatics," Pattern Recognition, vol. 39, 2006.
    • (2006) Pattern Recognition , vol.39
  • 359
    • 14644416505 scopus 로고    scopus 로고
    • Identifying time-lagged gene clusters using gene expression data
    • L. Ji and K. L. Tan, "Identifying time-lagged gene clusters using gene expression data," Bioinformatics, vol. 21, pp. 509-516, 2005.
    • (2005) Bioinformatics , vol.21 , pp. 509-516
    • Ji, L.1    Tan, K.L.2
  • 364
    • 0141998079 scopus 로고    scopus 로고
    • The maximum edge biclique profilem is NP-Complete
    • R. Peeters, "The maximum edge biclique profilem is NP-Complete," Discrete Applied Mathematics, vol. 131, pp. 651-654, 2003.
    • (2003) Discrete Applied Mathematics , vol.131 , pp. 651-654
    • Peeters, R.1
  • 366
    • 33748417841 scopus 로고    scopus 로고
    • Multi-objective evolutionary biclustering in gene expression data
    • S. Mitra and H. Banka, "Multi-objective evolutionary biclustering in gene expression data," Pattern Recognition, 2006, vol. 39, pp. 2464-2477, 2006.
    • (2006) Pattern Recognition, 2006 , vol.39 , pp. 2464-2477
    • Mitra, S.1    Banka, H.2
  • 368
    • 0038109937 scopus 로고    scopus 로고
    • Coupled two way clustering analysis of breast cancer and colon cancer gene expression data
    • G. Getz, H. Gal, I. Kela, D. A. Notterman, and E. Domany, "Coupled two way clustering analysis of breast cancer and colon cancer gene expression data," Bioinformatics, vol. 19, pp. 1079-1089, 2003.
    • (2003) Bioinformatics , vol.19 , pp. 1079-1089
    • Getz, G.1    Gal, H.2    Kela, I.3    Notterman, D.A.4    Domany, E.5
  • 371
    • 11244306358 scopus 로고    scopus 로고
    • Discovering statistically significant biclusters in gene expression data
    • A. Tanay, R. Sharan, and R. Shamir, "Discovering statistically significant biclusters in gene expression data," Bioinformatics, vol. 18, pp. S136-S144, 2002.
    • (2002) Bioinformatics , vol.18 , pp. S136-S144
    • Tanay, A.1    Sharan, R.2    Shamir, R.3
  • 372
    • 0036012349 scopus 로고    scopus 로고
    • Plaid models for gene expression data
    • L. Lazzeroni and A. Owen, "Plaid models for gene expression data," Statistica Sinica, vol. 12, pp. 61-86, 2002.
    • (2002) Statistica Sinica , vol.12 , pp. 61-86
    • Lazzeroni, L.1    Owen, A.2
  • 373
    • 33645118580 scopus 로고    scopus 로고
    • An improved biclustering algorithm and its application to gene expression spectrum analysis
    • H. Qu, L.-P. Wang, Y.-C. Liang, et al., "An improved biclustering algorithm and its application to gene expression spectrum analysis," Genomics, Proteomics and Bioinformatics, vol. 3, pp. 189-193, 2005.
    • (2005) Genomics, Proteomics and Bioinformatics , vol.3 , pp. 189-193
    • Qu, H.1    Wang, L.-P.2    Liang, Y.-C.3
  • 377
    • 57249097446 scopus 로고    scopus 로고
    • Analysis of biclusters with applications to gene expression data
    • (C. Martnez, ed.), Theoretical Computer Science Proceedings AD
    • G. Park and W. Szpankowski, "Analysis of biclusters with applications to gene expression data," in International Conference on Analysis of Algorithms (C. Martnez, ed.), Theoretical Computer Science Proceedings AD, pp. 267-274, 2005.
    • (2005) International Conference on Analysis of Algorithms , pp. 267-274
    • Park, G.1    Szpankowski, W.2
  • 378
    • 0037399130 scopus 로고    scopus 로고
    • Spectral biclustering of microarray data: Coclustering genes and conditions
    • Y. Kluger, R. Basri, J. T. Chang, and M. Gerstein, "Spectral biclustering of microarray data: Coclustering genes and conditions," Genome Reaserch, vol. 13, pp. 703-716, 2003.
    • (2003) Genome Reaserch , vol.13 , pp. 703-716
    • Kluger, Y.1    Basri, R.2    Chang, J.T.3    Gerstein, M.4
  • 380
    • 33646780247 scopus 로고    scopus 로고
    • Biclustering of DNA microarray data with early pruning
    • A. H. Tewfik and A. B. Tchagang, "Biclustering of DNA microarray data with early pruning," in Proceedings of ICASSP 2005, pp. V773-V776, 2005.
    • (2005) Proceedings of ICASSP 2005 , pp. V773-V776
    • Tewfik, A.H.1    Tchagang, A.B.2
  • 385
    • 8844277626 scopus 로고    scopus 로고
    • Analysing time series gene expression data
    • Z. B. Joseph, "Analysing time series gene expression data," Bioinformatics, vol. 20, pp. 2493-2503, 2004.
    • (2004) Bioinformatics , vol.20 , pp. 2493-2503
    • Joseph, Z.B.1
  • 387
    • 33746901275 scopus 로고    scopus 로고
    • DNA microarray data analysis: A novel biclustering algorithm approach
    • A. B. Tchagang and A. H. Tewfik, "DNA microarray data analysis: A novel biclustering algorithm approach," Journal on Applied Signal Processing (EURASIP), vol. Article ID 59809, pp. 1-12, 2006.
    • (2006) Journal on Applied Signal Processing (EURASIP) , pp. 1-12
    • Tchagang, A.B.1    Tewfik, A.H.2
  • 388
    • 33646191891 scopus 로고    scopus 로고
    • A linear time biclustering algorithm for time series gene expression data
    • (R. Casadio and G. Myers, eds.), Berlin: Springer-Verlag
    • S. C. Madeira and A. L. Oliveira, "A linear time biclustering algorithm for time series gene expression data," in WABI 2005, LNBI 3692 (R. Casadio and G. Myers, eds.), pp. 39-52, Berlin: Springer-Verlag, 2005.
    • (2005) WABI 2005, LNBI 3692 , pp. 39-52
    • Madeira, S.C.1    Oliveira, A.L.2
  • 394
    • 24644481999 scopus 로고    scopus 로고
    • Order preserving clustering over multiple time course experiments
    • (F. Rothlauf et al., ed.), Berlin: Springer-Verlag
    • S. Bleuler and E. Zitzler, "Order preserving clustering over multiple time course experiments," in EvoWorkshops 2005, LNCS 3449 (F. Rothlauf et al., ed.), pp. 33-43, Berlin: Springer-Verlag, 2005.
    • (2005) EvoWorkshops 2005, LNCS 3449 , pp. 33-43
    • Bleuler, S.1    Zitzler, E.2
  • 398
    • 0030214781 scopus 로고    scopus 로고
    • The possibilistic c-means algorithm: in sights and recommendations
    • R. Krishnapuram and J. M. Keller, "The possibilistic c-means algorithm: in sights and recommendations," IEEE Transactions on Fuzzy Systems, vol. 4, pp. 385-393, 1996.
    • (1996) IEEE Transactions on Fuzzy Systems , vol.4 , pp. 385-393
    • Krishnapuram, R.1    Keller, J.M.2
  • 400
    • 0032932780 scopus 로고    scopus 로고
    • A fuzzy clustering based segmentation system as support to diagnosis in medical imaging
    • F. Masulli and A. Schenone, "A fuzzy clustering based segmentation system as support to diagnosis in medical imaging," Artificial Intelligence in Medicine, vol. 16, pp. 129-147, 1999.
    • (1999) Artificial Intelligence in Medicine , vol.16 , pp. 129-147
    • Masulli, F.1    Schenone, A.2
  • 404
    • 84916537550 scopus 로고
    • Bayesian analysis of binary and polychotomous response data
    • Albert, J. and Chib, S. (1993) Bayesian analysis of binary and polychotomous response data. J. Am. Statist. Ass., 88, 669-679.
    • (1993) J. Am. Statist. Ass. , vol.88 , pp. 669-679
    • Albert, J.1    Chib, S.2
  • 405
    • 0033536012 scopus 로고    scopus 로고
    • Broad patterns of gene expression revealed by clustering analysis of tumor and normal colon tissues probed by oligonucleotide arrays
    • Alon, U., Barkai, N., Notterman, D.A., Gish, K., Ybarra, S., Mack, D., and Levine, A.J. (1999) Broad patterns of gene expression revealed by clustering analysis of tumor and normal colon tissues probed by oligonucleotide arrays. Proc. Nat. Acad. Sci., 96, 6745-6750.
    • (1999) Proc. Nat. Acad. Sci. , vol.96 , pp. 6745-6750
    • Alon, U.1    Barkai, N.2    Notterman, D.A.3    Gish, K.4    Ybarra, S.5    Mack, D.6    Levine, A.J.7
  • 406
    • 5844297152 scopus 로고
    • Theory of reproducing kernels
    • Aronszajn, N. (1950) Theory of reproducing kernels. Trans. Am. Math. Soc., 68, 337-404.
    • (1950) Trans. Am. Math. Soc. , vol.68 , pp. 337-404
    • Aronszajn, N.1
  • 407
    • 0000626524 scopus 로고
    • Expected information as expected utility
    • Bernardo, J.M. (1979) Expected information as expected utility. Ann. Statist, 7, 686-690.
    • (1979) Ann. Statist , vol.7 , pp. 686-690
    • Bernardo, J.M.1
  • 413
    • 0030669030 scopus 로고    scopus 로고
    • Exploring the metabolic and genetic control of gene expression on a genomic scale
    • DeRisi, J.L., Iyer, V.R., and Brown, P.O. (1997) Exploring the metabolic and genetic control of gene expression on a genomic scale. Science, 278, 680-685.
    • (1997) Science , vol.278 , pp. 680-685
    • DeRisi, J.L.1    Iyer, V.R.2    Brown, P.O.3
  • 414
    • 0036489046 scopus 로고    scopus 로고
    • Comparison of discrimination methods for the classification of tumors using gene expression data
    • Dudoit, S., Fridlyand, J., and Speed, T.P. (2002) Comparison of discrimination methods for the classification of tumors using gene expression data. J. Am. Statist. Ass., 97, 77-87.
    • (2002) J. Am. Statist. Ass. , vol.97 , pp. 77-87
    • Dudoit, S.1    Fridlyand, J.2    Speed, T.P.3
  • 415
    • 1542784653 scopus 로고    scopus 로고
    • Empirical Bayes Analysis of a Microarray Experiment
    • Efron, B., Tibshirani, R, Storey, J.D. and Tusher, V. (2001) Empirical Bayes Analysis of a Microarray Experiment. J. Am. Statist. Ass., 96(456), 1151-1161.
    • (2001) J. Am. Statist. Ass. , vol.96 , Issue.456 , pp. 1151-1161
    • Efron, B.1    Tibshirani, R.2    Storey, J.D.3    Tusher, V.4
  • 416
    • 4544258714 scopus 로고    scopus 로고
    • Adaptive sparseness using Jeffreys prior
    • (eds T. Dietterich, S. Becker, and Z. Ghahramani). Cambridge, MA: MIT Press.
    • Figueiredo, M. (2002) Adaptive sparseness using Jeffreys prior. In Neural Information Processing Systems 14 (eds T. Dietterich, S. Becker, and Z. Ghahramani), pp. 697 - 704. Cambridge, MA: MIT Press.
    • (2002) Neural Information Processing Systems , vol.14 , pp. 697-704
    • Figueiredo, M.1
  • 418
    • 84950453304 scopus 로고
    • Sampling-based approaches to calculating marginal densities
    • Gelfand, A. and Smith, A. F. M. (1990) Sampling-based approaches to calculating marginal densities. J. Am. Statist. Ass., 85, 398-409.
    • (1990) J. Am. Statist. Ass. , vol.85 , pp. 398-409
    • Gelfand, A.1    Smith, M.A.F.2
  • 419
    • 0001803816 scopus 로고    scopus 로고
    • Model determination using sampling-based methods
    • (eds W. Gilks, S. Richardson, and D. J. Spiegelhalter). London: Chapman and Hall.
    • Gelfand, A. (1996) Model determination using sampling-based methods. In Markov Chain Monte Carlo in Practice (eds W. Gilks, S. Richardson, and D. J. Spiegelhalter), pp. 145-158. London: Chapman and Hall.
    • (1996) Markov Chain Monte Carlo in Practice , pp. 145-158
    • Gelfand, A.1
  • 420
    • 0001582213 scopus 로고    scopus 로고
    • Inference and monitoring convergence
    • (eds W. Gilks, S. Richardson, and D. J. Spiegelhalter). London: Chapman and Hall.
    • Gelman, A. (1996) Inference and monitoring convergence. In Markov Chain Monte Carlo in Practice (eds W. Gilks, S. Richardson, and D. J. Spiegelhalter), pp. 131-140. London: Chapman and Hall.
    • (1996) Markov Chain Monte Carlo in Practice , pp. 131-140
    • Gelman, A.1
  • 427
    • 0036489048 scopus 로고    scopus 로고
    • Bayesian Models for Gene Expression with DNA Microarray Data
    • Ibrahim, J.G., Chen, M.H. and Gray, R.J. (2002) Bayesian Models for Gene Expression with DNA Microarray Data. J. Am. Statist. Ass., 97(457), 88-100.
    • (2002) J. Am. Statist. Ass. , vol.97 , Issue.457 , pp. 88-100
    • Ibrahim, J.G.1    Chen, M.H.2    Gray, R.J.3
  • 428
    • 0015000439 scopus 로고
    • Some results on Tchebycheffian spline functions
    • Kimeldorf, G. and Wahba, G. (1971) Some results on Tchebycheffian spline functions. J. Math. Anal. Applic., 33, 82-95.
    • (1971) J. Math. Anal. Applic. , vol.33 , pp. 82-95
    • Kimeldorf, G.1    Wahba, G.2
  • 430
    • 0034343415 scopus 로고    scopus 로고
    • Smoothing spline ANOVA models for large data sets with Bernoulli observations and the randomized GACV
    • Lin, X.,Wahba, G., Xiang, D., Gao, F., Klein, R., and Klein, B. (2000) Smoothing spline ANOVA models for large data sets with Bernoulli observations and the randomized GACV. Ann. Statist., 28, 1570-1600.
    • (2000) Ann. Statist. , vol.28 , pp. 1570-1600
    • Lin, X.1    Wahba, G.2    Xiang, D.3    Gao, F.4    Klein, R.5    Klein, B.6
  • 431
    • 0036258405 scopus 로고    scopus 로고
    • Support vector machines and the Bayes rule in classification
    • Lin, Y. (2002) Support vector machines and the Bayes rule in classification. Data Mining and Knowledge Discovery, 6, 259-275.,
    • (2002) Data Mining and Knowledge Discovery , vol.6 , pp. 259-275
    • Lin, Y.1
  • 432
    • 0007826152 scopus 로고    scopus 로고
    • Bayesian non-linear modelling for the 1993 energy prediction competition
    • (ed G. Heidbreder). Dordrecht: Kluwer Academic Press.
    • MacKay, D. (1996) Bayesian non-linear modelling for the 1993 energy prediction competition. In Maximum Entropy and Bayesian Methods (ed G. Heidbreder), pp. 221-234. Dordrecht: Kluwer Academic Press.
    • (1996) Maximum Entropy and Bayesian Methods , pp. 221-234
    • MacKay, D.1
  • 434
    • 0347079826 scopus 로고    scopus 로고
    • Analysis of molecular profile data using generative and discriminative methods
    • Moler, E. J., Chow, M. L., and Mian, I. S. (2000) Analysis of molecular profile data using generative and discriminative methods. Physiological Genetics, 4, 109-126.
    • (2000) Physiological Genetics , vol.4 , pp. 109-126
    • Moler, E.J.1    Chow, M.L.2    Mian, S.I.3
  • 436
    • 0005043637 scopus 로고
    • Statistical inference on time series by rkhs methods
    • (ed. R. Pyke). Canadian Mathematical Congress: Montreal.
    • Parzen, E. (1970) Statistical inference on time series by rkhs methods. In Proc. 12th Biennial seminar (ed. R. Pyke), pp. 1-37. Canadian Mathematical Congress: Montreal.
    • (1970) Proc. 12th Biennial seminar , pp. 1-37
    • Parzen, E.1
  • 441
    • 0028806048 scopus 로고
    • Quantitative monitoring of gene expression patterns with a complementary DNA microarray
    • Schena, M., Shalon, D., Davis, R., and Brown, P. (1995) Quantitative monitoring of gene expression patterns with a complementary DNA microarray. Science, 270, 467-470.
    • (1995) Science , vol.270 , pp. 467-470
    • Schena, M.1    Shalon, D.2    Davis, R.3    Brown, P.4
  • 443
    • 0036163572 scopus 로고    scopus 로고
    • Bayesian methods for support vector machines: evidence and predictive class probabilities
    • Sollich, P. (2001) Bayesian methods for support vector machines: evidence and predictive class probabilities. Machine Learning, 46, 21-52.
    • (2001) Machine Learning , vol.46 , pp. 21-52
    • Sollich, P.1
  • 444
    • 0025206332 scopus 로고
    • Probabilistic neural networks
    • Specht, D. F. (1990) Probabilistic neural networks. Neural Networks, 3, 109-118.
    • (1990) Neural Networks , vol.3 , pp. 109-118
    • Specht, F.D.1
  • 445
    • 84899032239 scopus 로고    scopus 로고
    • The relevance vector machine
    • (eds S. Solla, T. Leen, and K. Muller). Cambridge, MA: MIT Press.
    • Tipping, M. (2000) The relevance vector machine. In Neural Information Processing Systems 12 (eds S. Solla, T. Leen, and K. Muller), pp. 652-658. Cambridge, MA: MIT Press.
    • (2000) Neural Information Processing Systems , vol.12 , pp. 652-658
    • Tipping, M.1
  • 446
    • 0001224048 scopus 로고    scopus 로고
    • Sparse Bayesian learning and the relevance vector machine
    • Tipping, M. (2001) Sparse Bayesian learning and the relevance vector machine. J. Mach. Learn. Res., 1, 211-244.
    • (2001) J. Mach. Learn. Res. , vol.1 , pp. 211-244
    • Tipping, M.1
  • 447
    • 0035875553 scopus 로고    scopus 로고
    • Issues in cDNA microarray analysis: quality filtering, channel normalization, models of variations and assessment of gene effects
    • Tseng, G.C., Oh, M.K., Rohlin, L., Liao, J.C., and Wong, W.H. (2001) Issues in cDNA microarray analysis: quality filtering, channel normalization, models of variations and assessment of gene effects. Nucleic Acids Res., 29, 2549-2557.
    • (2001) Nucleic Acids Res. , vol.29 , pp. 2549-2557
    • Tseng, G.C.1    Oh, M.K.2    Rohlin, L.3    Liao, J.C.4    Wong, W.H.5
  • 450
    • 0001873883 scopus 로고    scopus 로고
    • Support vector machines, reproducing kernel hilbert spaces and the randomized GACV
    • (eds B. Scholkopf, C. Burges, and A. Smola). Cambridge, MA: MIT Press.
    • Wahba, G. (1999) Support vector machines, reproducing kernel hilbert spaces and the randomized GACV. In Advances in Kernel Methods (eds B. Scholkopf, C. Burges, and A. Smola), pp. 69-88. Cambridge, MA: MIT Press.
    • (1999) Advances in Kernel Methods , pp. 69-88
    • Wahba, G.1
  • 451
    • 2142670018 scopus 로고    scopus 로고
    • Optimal properties and adaptive tuning of standard and nonstandard support vector machines
    • (eds D. Denison, M. Hansen, C. Holmes, B. Mallick, and B. Yu). New York: Springer.
    • Wahba, G., Lin, Y., Lee, Y., and Zhang, H. (2002) Optimal properties and adaptive tuning of standard and nonstandard support vector machines. In Nonlinear Estimation and Classification (eds D. Denison, M. Hansen, C. Holmes, B. Mallick, and B. Yu), pp. 125 - 143. New York: Springer.
    • (2002) Nonlinear Estimation and Classification , pp. 125-143
    • Wahba, G.1    Lin, Y.2    Lee, Y.3    Zhang, H.4
  • 455
    • 0034533063 scopus 로고    scopus 로고
    • Tumor classification using gene expression profiles
    • Xiong, M.M., Jin, L., Li, W. and Boerwinkle, E. (2000) Tumor classification using gene expression profiles. Biotechiques, 29, 1264-1270.
    • (2000) Biotechiques , vol.29 , pp. 1264-1270
    • Xiong, M.M.1    Jin, L.2    Li, W.3    Boerwinkle, E.4
  • 456
    • 1342294092 scopus 로고    scopus 로고
    • Normalization for cDNA microarray data: a robust composite method addressing single and multiple slide systematic variation
    • Yang, Y.H., Dudoit, S., Luu, P., Lin, D.M., Peng, V., Ngai, J. and Speed, T.P. (2002) Normalization for cDNA microarray data: a robust composite method addressing single and multiple slide systematic variation. Nucleic Acids Res. 30(4), e15.
    • (2002) Nucleic Acids Res , vol.30 , Issue.4
    • Yang, Y.H.1    Dudoit, S.2    Luu, P.3    Lin, D.M.4    Peng, V.5    Ngai, J.6    Speed, T.P.7
  • 457
    • 84898974832 scopus 로고    scopus 로고
    • Kernel logistic regression and the import vector machine
    • (eds T. Dietterich, S. Becker, and Z. Ghahramani). Cambridge, MA: MIT Press.
    • Zhu, J. and Hastie, T. (2002) Kernel logistic regression and the import vector machine. In Neural Information Processing Systems 14 (eds T. Dietterich, S. Becker, and Z. Ghahramani), pp. 1081-1088. Cambridge, MA: MIT Press.
    • (2002) Neural Information Processing Systems , vol.14 , pp. 1081-1088
    • Zhu, J.1    Hastie, T.2
  • 459
    • 0037435030 scopus 로고    scopus 로고
    • Mass spectrometry based proteomics
    • Aebersold, R. andMann, M. (2003) Mass spectrometry based proteomics. Nature, 422, 198-207.
    • (2003) Nature , vol.422 , pp. 198-207
    • Aebersold, R.1    Mann, M.2
  • 460
    • 33748535101 scopus 로고    scopus 로고
    • Shotgun proteomics using the iTRAQ isobaric tags
    • Aggarwal, K., Choe, L.H., and Lee, K.H. (2006) Shotgun proteomics using the iTRAQ isobaric tags. Proteomics, 5, 2297.
    • (2006) Proteomics , vol.5 , pp. 2297
    • Aggarwal, K.1    Choe, L.H.2    Lee, K.H.3
  • 462
    • 35648942133 scopus 로고    scopus 로고
    • 8-Plex quantitation of changes in cerebrospinal fluid protein expression in subjects undergoing intravenous immunoglobulin treatment for Alzheimer's disease
    • Choe, L., D'Ascenzo, M., Relkin, N.R., Pappin, D., Ross, P., Williamson, B., Guertin, S., Pribil, P. and Lee, K.H. (2007) 8-Plex quantitation of changes in cerebrospinal fluid protein expression in subjects undergoing intravenous immunoglobulin treatment for Alzheimer's disease. Proteomics, 7, 3651-3660.
    • (2007) Proteomics , vol.7 , pp. 3651-3660
    • Choe, L.1    D'Ascenzo, M.2    Relkin, N.R.3    Pappin, D.4    Ross, P.5    Williamson, B.6    Guertin, S.7    Pribil, P.8    Lee, K.H.9
  • 463
    • 34547693897 scopus 로고    scopus 로고
    • Proteomic analyses to identify novel therapeutic targets for the treatment of advanced prostate cancer
    • Comuzzi, B. and Sadar, M.D. (2006) Proteomic analyses to identify novel therapeutic targets for the treatment of advanced prostate cancer. Cell Sci, 3, 61-81.
    • (2006) Cell Sci , vol.3 , pp. 61-81
    • Comuzzi, B.1    Sadar, M.D.2
  • 464
    • 34247341829 scopus 로고    scopus 로고
    • Proteomics discovery of metalloproteinase substrates in the cellular context by iTRAQ labeling reveals a diverse MMP-2 substrate degradome
    • Dean, R.A. and Overall, C.M. (2007) Proteomics discovery of metalloproteinase substrates in the cellular context by iTRAQ labeling reveals a diverse MMP-2 substrate degradome. Mol. Cell. Prot. 6, 611-623.
    • (2007) Mol. Cell. Prot. , vol.6 , pp. 611-623
    • Dean, R.A.1    Overall, C.M.2
  • 465
    • 34547131803 scopus 로고    scopus 로고
    • Endometrial carcinoma biomarker discovery and verification using differentially tagged clinical samples with multidimensional lifluid chromatography and tandem mass spectrometry
    • Desouza, L.V., Grigull, J., Ghanny, S., Dube, V., Romaschin, A.D., Colgan, T.J. and Siu, K.W. (2007) Endometrial carcinoma biomarker discovery and verification using differentially tagged clinical samples with multidimensional lifluid chromatography and tandem mass spectrometry. Mol. Cell. Prot., 6, 1170.
    • (2007) Mol. Cell. Prot. , vol.6 , pp. 1170
    • Desouza, L.V.1    Grigull, J.2    Ghanny, S.3    Dube, V.4    Romaschin, A.D.5    Colgan, T.J.6    Siu, K.W.7
  • 466
    • 33845428734 scopus 로고    scopus 로고
    • Methodologies for characterizing phospho-proteins by mass spectrometry
    • Gafken, P.R. and Lampe, P.D. (2006) Methodologies for characterizing phospho-proteins by mass spectrometry. Cell Commun. Adhes. 13, 249-262.
    • (2006) Cell Commun. Adhes. , vol.13 , pp. 249-262
    • Gafken, P.R.1    Lampe, P.D.2
  • 468
    • 0032875697 scopus 로고    scopus 로고
    • Quantitative analysis of complex protein mixtures using isotope-coded afinity tags
    • Gygi, S.P., Rist, B., Gerber, S.A., Turecek, F., Gelb, M.H. and Aebersold, R. (1999) Quantitative analysis of complex protein mixtures using isotope-coded afinity tags. Nat. Biotechnol., 17, 994-999.
    • (1999) Nat. Biotechnol. , vol.17 , pp. 994-999
    • Gygi, S.P.1    Rist, B.2    Gerber, S.A.3    Turecek, F.4    Gelb, M.H.5    Aebersold, R.6
  • 469
    • 0001470744 scopus 로고
    • Testing the approximate validity of statistical hypotheses
    • Hodges, J.L. and Lehmann, E.L. (1954) Testing the approximate validity of statistical hypotheses. J. Roy. Stat. Soc. B, 16, 261-268.
    • (1954) J. Roy. Stat. Soc. B , vol.16 , pp. 261-268
    • Hodges, J.L.1    Lehmann, E.L.2
  • 473
    • 34249314688 scopus 로고    scopus 로고
    • Comparative time-dependent analysis of potential inflammation biomarkers in lymphoma-bearing SJL mice
    • Kristiansson, M.H., Bhat, V.B., Babu, I.R., Wishnok, J.S. and Tannenbaum, S.R. (2007) Comparative time-dependent analysis of potential inflammation biomarkers in lymphoma-bearing SJL mice. J. Proteome Res., 4, 1735-1744.
    • (2007) J. Proteome Res. , vol.4 , pp. 1735-1744
    • Kristiansson, M.H.1    Bhat, V.B.2    Babu, I.R.3    Wishnok, J.S.4    Tannenbaum, S.R.5
  • 474
    • 33847371618 scopus 로고    scopus 로고
    • iTRAQ is a useful method to screen for membrane-bound proteins differentially expressed in human natural killer cell types
    • Lund, T.C., Anderson, L.B., McCullar, V., Higgins, L., Yun, G.H., Grzywacz, B., Verneris, M.R. and Miller, J.S. (2007) iTRAQ is a useful method to screen for membrane-bound proteins differentially expressed in human natural killer cell types. J. Proteome Res., 6, 644-653.
    • (2007) J. Proteome Res. , vol.6 , pp. 644-653
    • Lund, T.C.1    Anderson, L.B.2    McCullar, V.3    Higgins, L.4    Yun, G.H.5    Grzywacz, B.6    Verneris, M.R.7    Miller, J.S.8
  • 477
    • 0036583926 scopus 로고    scopus 로고
    • Stable isotope labeling by amino acids in cell culture, SILAC, as a simple and accurate approach to expression proteomics
    • Ong, S.E., Blagoev, B., Kratchmarova, I., Kristensen, D.B., Steen, H., Pandey, A. and Mann, M. (2002) Stable isotope labeling by amino acids in cell culture, SILAC, as a simple and accurate approach to expression proteomics. Mol. Cell. Prot., 1, 376-386.
    • (2002) Mol. Cell. Prot. , vol.1 , pp. 376-386
    • Ong, S.E.1    Blagoev, B.2    Kratchmarova, I.3    Kristensen, D.B.4    Steen, H.5    Pandey, A.6    Mann, M.7
  • 478
    • 34249657818 scopus 로고    scopus 로고
    • Comprehensive survey of p94/calpain 3 substrates by comparative proteomics - Possible regulation of protein synthesis by p94
    • Ono, Y., Hayashi, C., Doi, N., Kitamura, F., Shindo, M., Kudo, K., Tsubata, T., Yanagida, M. and Sorimachi, H. (2007) Comprehensive survey of p94/calpain 3 substrates by comparative proteomics - Possible regulation of protein synthesis by p94. Biotechnol J., 2, 565-576.
    • (2007) Biotechnol J. , vol.2 , pp. 565-576
    • Ono, Y.1    Hayashi, C.2    Doi, N.3    Kitamura, F.4    Shindo, M.5    Kudo, K.6    Tsubata, T.7    Yanagida, M.8    Sorimachi, H.9
  • 479
    • 41949139372 scopus 로고    scopus 로고
    • Quantitative shotgun proteomics of enriched heterocysts from Nostoc sp. PCC 7120 using 8-Plex isobaric peptide tags
    • Ow, S.Y., Cardona, T., Taton, A., Magnuson, A., Lindblad, P., Stensjo, K. and Wright, P.C. (2008) Quantitative shotgun proteomics of enriched heterocysts from Nostoc sp. PCC 7120 using 8-Plex isobaric peptide tags. J. Proteome Res., 7, 1615-1628.
    • (2008) J. Proteome Res. , vol.7 , pp. 1615-1628
    • Ow, S.Y.1    Cardona, T.2    Taton, A.3    Magnuson, A.4    Lindblad, P.5    Stensjo, K.6    Wright, P.C.7
  • 482
    • 33846582052 scopus 로고    scopus 로고
    • Proteome and differential expression analysis of membrane and cytosolic proteins from Mycobacterium avium subsp. paratuberculosis strains K-10 and 187
    • Radosevich, T.J., Reinhardt, T.A., Lippolis, J.D., Bannantine, J.P. and Stabel, J.R. (2007) Proteome and differential expression analysis of membrane and cytosolic proteins from Mycobacterium avium subsp. paratuberculosis strains K-10 and 187. J. Bacteriol., 189, 1109-1117.
    • (2007) J. Bacteriol. , vol.189 , pp. 1109-1117
    • Radosevich, T.J.1    Reinhardt, T.A.2    Lippolis, J.D.3    Bannantine, J.P.4    Stabel, J.R.5
  • 483
    • 46749120270 scopus 로고    scopus 로고
    • Discovery and verification of head-and-neck cancer biomarkers by differential protein expression analysis using iTRAQ-labeling and multidimensional lifluid chromatography and tandem mass spectrometry
    • Ralhan, R., Desouza, L.V., Matta, A., Chandra Tripathi, S., Ghanny, S., Datta Gupta, S., Bahadur, S. and Siu, K.W. (2008) Discovery and verification of head-and-neck cancer biomarkers by differential protein expression analysis using iTRAQ-labeling and multidimensional lifluid chromatography and tandem mass spectrometry. To appear in Mol. Cell. Prot.
    • (2008) Mol. Cell. Prot.
    • Ralhan, R.1    Desouza, L.V.2    Matta, A.3    Chandra Tripathi, S.4    Ghanny, S.5    Datta Gupta, S.6    Bahadur, S.7    Siu, K.W.8
  • 485
    • 33645509355 scopus 로고    scopus 로고
    • Phosphopeptide quantitation using amine-reactive isobaric tagging reagents and tandem mass spectrometry: application to proteins isolated by gel electrophoresis
    • Sachon, E., Mohammed, S., Bache, N. and Jensen, O.N. (2006) Phosphopeptide quantitation using amine-reactive isobaric tagging reagents and tandem mass spectrometry: application to proteins isolated by gel electrophoresis. Rapid Commun. Mass Sp., 20, 1127-1134.
    • (2006) Rapid Commun. Mass Sp. , vol.20 , pp. 1127-1134
    • Sachon, E.1    Mohammed, S.2    Bache, N.3    Jensen, O.N.4
  • 486
    • 33746255981 scopus 로고    scopus 로고
    • Identification of differentiating neural progenitor cell markers using shotgun isobaric tagging mass spectrometry
    • Salim, K., Kehoe, L., Minkoff, M.S., Bilsland, J.G., Munoz-Sanjuan, I. and Guest, P.C. (2006) Identification of differentiating neural progenitor cell markers using shotgun isobaric tagging mass spectrometry. Stem Cells Dev., 15, 461-470.
    • (2006) Stem Cells Dev. , vol.15 , pp. 461-470
    • Salim, K.1    Kehoe, L.2    Minkoff, M.S.3    Bilsland, J.G.4    Munoz-Sanjuan, I.5    Guest, P.C.6
  • 487
    • 33846821908 scopus 로고    scopus 로고
    • Proteomic discovery of protease substrates
    • Schilling, O. and Overall, C.M. (2007) Proteomic discovery of protease substrates. Curr. Opin. Chem. Biol., 11, 36-45.
    • (2007) Curr. Opin. Chem. Biol. , vol.11 , pp. 36-45
    • Schilling, O.1    Overall, C.M.2
  • 490
    • 33749256309 scopus 로고    scopus 로고
    • Methods for proteomics in neuroscience
    • Tannu, N.S. and Hemby, S.E. (2006) Methods for proteomics in neuroscience. Prog. Brain Res., 158, 41-82.
    • (2006) Prog. Brain Res. , vol.158 , pp. 41-82
    • Tannu, N.S.1    Hemby, S.E.2
  • 493
    • 85128439703 scopus 로고    scopus 로고
    • Quantitative proteomic analysis to profile dynamic changes in the spatial distribution of cellular proteins
    • Yan,W., Hwang, D. and Aebersold, R. Quantitative proteomic analysis to profile dynamic changes in the spatial distribution of cellular proteins. Humana Press (2008).
    • (2008) Humana Press
    • Yan, W.1    Hwang, D.2    Aebersold, R.3
  • 495
    • 42549144042 scopus 로고    scopus 로고
    • Protein profile in neuroblastoma cells incubated with S- and R-enantiomers of ibuprofen by iTRAQ-coupled 2-D LC-MS/MS analysis: Possible action of induced proteins on Alzheimer's disease
    • Zhang, J., Sui, J., Ching, C.B. and Chen, W.N. (2008) Protein profile in neuroblastoma cells incubated with S- and R-enantiomers of ibuprofen by iTRAQ-coupled 2-D LC-MS/MS analysis: Possible action of induced proteins on Alzheimer's disease. To appear in Proteomics.
    • (2008) Proteomics
    • Zhang, J.1    Sui, J.2    Ching, C.B.3    Chen, W.N.4
  • 496
    • 26844576371 scopus 로고    scopus 로고
    • Time-resolved mass spectrometry of tyrosine phos-phorylation sites in the epidermal growth factor receptor signaling network reveals dynamic modules
    • Zhang, Y., Wolf-Yadlin, A., Ross, P.L., Pappin, D.J., Rush, J., Lauffenburger, D.A. and White, F.M. (2005) Time-resolved mass spectrometry of tyrosine phos-phorylation sites in the epidermal growth factor receptor signaling network reveals dynamic modules. Mol. Cell. Prot., 4, 1240-1250.
    • (2005) Mol. Cell. Prot. , vol.4 , pp. 1240-1250
    • Zhang, Y.1    Wolf-Yadlin, A.2    Ross, P.L.3    Pappin, D.J.4    Rush, J.5    Lauffenburger, D.A.6    White, F.M.7
  • 497
    • 0035241690 scopus 로고    scopus 로고
    • Mass spectrometry in proteomics
    • Aebersold, R. and Goodlett, D. R. (2001) Mass spectrometry in proteomics. Chem. Rev. 101, 269-95.
    • (2001) Chem. Rev. , vol.101 , pp. 269-295
    • Aebersold, R.1    Goodlett, R.D.2
  • 498
    • 0042972838 scopus 로고    scopus 로고
    • A new algorithm for the evaluation of shotgun peptide sequencing in proteomics: support vector machine classification of peptide MS/MS spectra and SEQUEST scores
    • Anderson, D. C., Li, W., Payan, D. G. and Noble, W. S. (2003) A new algorithm for the evaluation of shotgun peptide sequencing in proteomics: support vector machine classification of peptide MS/MS spectra and SEQUEST scores. J. Proteome Res. 2, 137-46.
    • (2003) J. Proteome Res. , vol.2 , pp. 137-146
    • Anderson, D.C.1    Li, W.2    Payan, D.G.3    Noble, S.W.4
  • 499
    • 0030895921 scopus 로고    scopus 로고
    • A comparison of selected mRNA and protein abundances in human liver
    • Anderson L., Seilhamer J. (1997) A comparison of selected mRNA and protein abundances in human liver. Electrophoresis 18, 533-7.
    • (1997) Electrophoresis , vol.18 , pp. 533-537
    • Anderson, L.1    Seilhamer, J.2
  • 500
    • 0002451984 scopus 로고    scopus 로고
    • SCOPE: a probabilistic model for scoring tandem mass spectra against a peptide database
    • Bafna V. and Edwards N. (2001) SCOPE: a probabilistic model for scoring tandem mass spectra against a peptide database. Bioinformatics 17, Suppl. 1, S13-21.
    • (2001) Bioinformatics , vol.17 , pp. S13-S21
    • Bafna, V.1    Edwards, N.2
  • 501
    • 19544392545 scopus 로고    scopus 로고
    • Prediction of the phenotypic effects of non-synonymous single nucleotide polymorphisms using structural and evolutionary information
    • Bao L. and Cui Y. (2005) Prediction of the phenotypic effects of non-synonymous single nucleotide polymorphisms using structural and evolutionary information. Bioinformatics 21, 2185-90.
    • (2005) Bioinformatics , vol.21 , pp. 2185-2190
    • Bao, L.1    Cui, Y.2
  • 502
    • 0035478854 scopus 로고    scopus 로고
    • Random Forests
    • Breiman L. (2001) Random Forests. Machine Learning 45, 5-32.
    • (2001) , vol.45 , pp. 5-32
    • Breiman, L.1
  • 504
    • 0033565832 scopus 로고    scopus 로고
    • Role of accurate mass measurement (+/- 10 ppm) in protein identification strategies employing MS or MS/MS and database searching
    • Clauser, K. R., Baker, P. and Burlingame A. L. (1999) Role of accurate mass measurement (+/- 10 ppm) in protein identification strategies employing MS or MS/MS and database searching. Anal. Chem. 71, 2871-82.
    • (1999) Anal. Chem. , vol.71 , pp. 2871-2882
    • Clauser, K.R.1    Baker, P.2    Burlingame, A.L.3
  • 505
    • 3142702204 scopus 로고    scopus 로고
    • TANDEM: matching proteins with tandem mass spectra
    • Craig, R. and Beavis, R. C. (2004), TANDEM: matching proteins with tandem mass spectra. Bioinformatics 20, 1466-7.
    • (2004) Bioinformatics , vol.20 , pp. 1466-1467
    • Craig, R.1    Beavis, C.R.2
  • 507
    • 0000857494 scopus 로고
    • An approach to correlate tandem mass spectral data of peptides with amino acid sequences in a protein database
    • Eng, J., McCormack, A. and Yates, J. (1994) An approach to correlate tandem mass spectral data of peptides with amino acid sequences in a protein database. J. Am. Soc. Mass Spec. 5, 976-989.
    • (1994) J. Am. Soc. Mass Spec. , vol.5 , pp. 976-989
    • Eng, J.1    McCormack, A.2    Yates, J.3
  • 508
    • 1242307292 scopus 로고    scopus 로고
    • Probity: a protein identification algorithm with accurate assignment of the statistical significance of the results
    • Eriksson, J. and Fenyo, D. (2004) Probity: a protein identification algorithm with accurate assignment of the statistical significance of the results. J Proteome Res. 3, 32-6.
    • (2004) J Proteome Res. , vol.3 , pp. 32-36
    • Eriksson, J.1    Fenyo, D.2
  • 509
    • 0037442649 scopus 로고    scopus 로고
    • A method for assessing the statistical significance of mass spectrometry-based protein identifications using general scoring schemes
    • Fenyo, D. and Beavis, R. C. (2003) A method for assessing the statistical significance of mass spectrometry-based protein identifications using general scoring schemes. Anal Chem. 75, 768-74.
    • (2003) Anal Chem. , vol.75 , pp. 768-774
    • Fenyo, D.1    Beavis, C.R.2
  • 511
    • 0033636139 scopus 로고    scopus 로고
    • Support vector machine classification and validation of cancer tissue samples using microarray expression data
    • Furey, T. S., Cristianini, N., Duffy, N., Bednarski, D. W., Schummer, M. and Haussler, D. (2000) Support vector machine classification and validation of cancer tissue samples using microarray expression data. Bioinformatics 16, 906-914.
    • (2000) Bioinformatics , vol.16 , pp. 906-914
    • Furey, T.S.1    Cristianini, N.2    Duffy, N.3    Bednarski, D.W.4    Schummer, M.5    Haussler, D.6
  • 513
    • 0033016717 scopus 로고    scopus 로고
    • Correlation between protein and mRNA abundance in yeast
    • Gygi, S. P., Rochon. Y., Franza, B.R. and Aebersold, R. (1999) Correlation between protein and mRNA abundance in yeast. Mol. Cell Biol. 19, 1720-30.
    • (1999) Mol. Cell Biol. , vol.19 , pp. 1720-1730
    • Gygi, S.P.1    Rochon, Y.2    Franza, B.R.3    Aebersold, R.4
  • 515
    • 0037317111 scopus 로고    scopus 로고
    • Intensity-based statistical scorer for tandem mass spectrometry
    • Havilio, M., Haddad, Y. and Smilansky, Z. (2003) Intensity-based statistical scorer for tandem mass spectrometry. Anal. Chem. 75, 435-44.
    • (2003) Anal. Chem. , vol.75 , pp. 435-444
    • Havilio, M.1    Haddad, Y.2    Smilansky, Z.3
  • 516
    • 0033289037 scopus 로고    scopus 로고
    • Using the Fisher kernel method to detect remote protein homologies
    • AAAI Press, Menlo Park, CA.
    • Jaakkola, T., Diekhans, M. and Haussler, D. (1999) Using the Fisher kernel method to detect remote protein homologies. Proc. Int. Conf. Intell. Syst. Mol. Bio., 149-158. AAAI Press, Menlo Park, CA.
    • (1999) Proc. Int. Conf. Intell. Syst. Mol. Bio. , pp. 149-158
    • Jaakkola, T.1    Diekhans, M.2    Haussler, D.3
  • 517
    • 13844271209 scopus 로고    scopus 로고
    • Informatics for protein identification by mass spectrometry
    • Johnson, R. S., Davis, M. T., Taylor, J. A. and Patterson, S. D. (2005) Informatics for protein identification by mass spectrometry. Methods. 35, 223-236.
    • (2005) Methods , vol.35 , pp. 223-236
    • Johnson, R.S.1    Davis, M.T.2    Taylor, J.A.3    Patterson, D.S.4
  • 518
    • 0242653718 scopus 로고    scopus 로고
    • Mining a tandem mass spectrometry database to determine the trends and global factors influencing peptide fragmentation
    • Kapp, E. A., Schutz, F., Reid, G. E., Eddes, J. S., Moritz, R. L, O'Hair, R. A., Speed, T. P. and Simpson, R. J. (2003) Mining a tandem mass spectrometry database to determine the trends and global factors influencing peptide fragmentation. Anal. Chem. 75, 6251-64.
    • (2003) Anal. Chem. , vol.75 , pp. 6251-6264
    • Kapp, E.A.1    Schutz, F.2    Reid, G.E.3    Eddes, J.S.4    Moritz, L.R.5    O'Hair, R.A.6    Speed, T.P.7    Simpson, J.R.8
  • 519
    • 0037108887 scopus 로고    scopus 로고
    • Empirical statistical model to estimate the accuracy of peptide identifications made by MS/MS and database search
    • Keller, A., Nesvizhskii, A. I., Kolker, E. and Aebersold, R. (2002) Empirical statistical model to estimate the accuracy of peptide identifications made by MS/MS and database search. Anal. Chem. 74, 5383-5392.
    • (2002) Anal. Chem. , vol.74 , pp. 5383-5392
    • Keller, A.1    Nesvizhskii, A.I.2    Kolker, E.3    Aebersold, R.4
  • 520
  • 523
    • 0036828724 scopus 로고    scopus 로고
    • Probability-based validation of protein identifications using a modified SEQUEST algorithm
    • MacCoss, M. J., Wu, C. C. and Yates, J. R. 3rd. (2002) Probability-based validation of protein identifications using a modified SEQUEST algorithm. Anal. Chem. 74, 5593-9.
    • (2002) Anal. Chem. , vol.74 , pp. 5593-5599
    • MacCoss, M.J.1    Wu, C.C.2    Yates, J.R.3
  • 524
    • 0036209134 scopus 로고    scopus 로고
    • Qscore: an algorithm for evaluating SEQUEST database search results
    • Moore, R. E., Young, M. K. and Lee, T. D. (2002) Qscore: an algorithm for evaluating SEQUEST database search results. J. Am. Soc. Mass Spectrom. 13, 378-86.
    • (2002) J. Am. Soc. Mass Spectrom. , vol.13 , pp. 378-386
    • Moore, R.E.1    Young, M.K.2    Lee, D.T.3
  • 525
    • 0042338362 scopus 로고    scopus 로고
    • A statistical model for identifying proteins by tandem mass spectrometry
    • Nesvizhskii, A. I., Keller, A., Kolker, E. and Aebersold, R. (2003) A statistical model for identifying proteins by tandem mass spectrometry. Anal. Chem. 75, 4646-58.
    • (2003) Anal. Chem. , vol.75 , pp. 4646-4658
    • Nesvizhskii, A.I.1    Keller, A.2    Kolker, E.3    Aebersold, R.4
  • 526
    • 0034659815 scopus 로고    scopus 로고
    • Proteomics to study genes and genomes
    • Pandey, A. and Mann, M. (2000) Proteomics to study genes and genomes. Nature 405, 837-46.
    • (2000) Nature , vol.405 , pp. 837-846
    • Pandey, A.1    Mann, M.2
  • 527
    • 0037277179 scopus 로고    scopus 로고
    • Evaluation of multidimensional chromatography coupled with tandem mass spectrometry (LC/LC-MS/MS) for large-scale protein analysis: the yeast proteome
    • Peng, J., Elias, J. E., Thoreen, C. C., Licklider, L. J. and Gygi, S. P. (2003) Evaluation of multidimensional chromatography coupled with tandem mass spectrometry (LC/LC-MS/MS) for large-scale protein analysis: the yeast proteome. J. Proteome Res. 2, 43-50.
    • (2003) J. Proteome Res. , vol.2 , pp. 43-50
    • Peng, J.1    Elias, J.E.2    Thoreen, C.C.3    Licklider, L.J.4    Gygi, P.S.5
  • 528
    • 22344441685 scopus 로고    scopus 로고
    • The role of proteomics in investigating psychiatric disorders
    • Pennington, K., Cotter, D. and Dunn, M. J. (2005) The role of proteomics in investigating psychiatric disorders. Br. J. Psychiatry 187, 4-6.
    • (2005) Br. J. Psychiatry , vol.187 , pp. 4-6
    • Pennington, K.1    Cotter, D.2    Dunn, J.M.3
  • 529
    • 0033434080 scopus 로고    scopus 로고
    • Probability-based protein identification by searching sequence databases using mass-spectromety data
    • Perkins, D., Pappin, D., Creasy, D. and Cottrell, J. (1999) Probability-based protein identification by searching sequence databases using mass-spectromety data. Electorphoresis 20, 3551-3567.
    • (1999) Electorphoresis , vol.20 , pp. 3551-3567
    • Perkins, D.1    Pappin, D.2    Creasy, D.3    Cottrell, J.4
  • 530
    • 0043064042 scopus 로고    scopus 로고
    • A hypergeometric probability model for protein identification and validation using tandem mass spectral data and protein sequence databases
    • Sadygov, R. G. and Yates, J. R. 3rd. (2003) A hypergeometric probability model for protein identification and validation using tandem mass spectral data and protein sequence databases. Anal. Chem. 75, 3792-8. 30
    • (2003) Anal. Chem. , vol.75 , pp. 3792-3798
    • Sadygov, R.G.1    Yates, J.R.2
  • 531
    • 0028806048 scopus 로고
    • Quantitative monitoring of gene expression patterns with a complementary DNA microarray
    • Schena, M., Shalon, D., Davis, R. W. and Brown, P. O. (1995) Quantitative monitoring of gene expression patterns with a complementary DNA microarray. Science 270, 467-470.
    • (1995) Science , vol.270 , pp. 467-470
    • Schena, M.1    Shalon, D.2    Davis, R.W.3    Brown, O.P.4
  • 532
    • 4444335470 scopus 로고    scopus 로고
    • The ABC's (and XYZ's) of peptide sequencing
    • Steen, H. and Mann, M. (2004) The ABC's (and XYZ's) of peptide sequencing. Nat. Rev. Mol. Cell Biol. 5, 699-711.
    • (2004) Nat. Rev. Mol. Cell Biol. , vol.5 , pp. 699-711
    • Steen, H.1    Mann, M.2
  • 533
    • 12744280774 scopus 로고    scopus 로고
    • AMASS: software for automatically validating the quality of MS/MS spectrum from SEQUEST results
    • Sun, W., Li, F., Wang, J., Zheng, D. and Gao, Y. (2004) AMASS: software for automatically validating the quality of MS/MS spectrum from SEQUEST results. Mol. Cell Proteomics. 3, 1194-9.
    • (2004) Mol. Cell Proteomics. , vol.3 , pp. 1194-1199
    • Sun, W.1    Li, F.2    Wang, J.3    Zheng, D.4    Gao, Y.5
  • 534
    • 1442324456 scopus 로고    scopus 로고
    • Influence of basic residue content on fragment ion peak intensities in low-energy collision-induced dissociation spectra of peptides
    • Tabb, D. L., Huang, Y., Wysocki, V. H. and Yates, J. R. 3rd. (2004) Influence of basic residue content on fragment ion peak intensities in low-energy collision-induced dissociation spectra of peptides. Anal. Chem. 76, 1243-8.
    • (2004) Anal. Chem. , vol.76 , pp. 1243-1248
    • Tabb, D.L.1    Huang, Y.2    Wysocki, V.H.3    Yates, J.R.4
  • 535
    • 33645467062 scopus 로고    scopus 로고
    • Improved classification of mass spectrometry database search results using newer machine learning approaches
    • Ulintz, P. J., Zhu J., Qin, Z. S. and Andrews P. C. (2006) Improved classification of mass spectrometry database search results using newer machine learning approaches. Mol. Cell Proteomics 5, 497-509.
    • (2006) Mol. Cell Proteomics , vol.5 , pp. 497-509
    • Ulintz, P.J.1    Zhu, J.2    Qin, Z.S.3    Andrews, P.C.4
  • 537
    • 0035106351 scopus 로고    scopus 로고
    • Large-scale analysis of the yeast proteome by multidimensional protein identification technology
    • Washburn, M. P., Wolters, D. and Yates, J. R. 3rd. (2001) Large-scale analysis of the yeast proteome by multidimensional protein identification technology. Nat. Biotechnol. 19, 242-7.
    • (2001) Nat. Biotechnol , vol.19 , pp. 242-247
    • Washburn, M.P.1    Wolters, D.2    Yates, J.R.3
  • 538
    • 0034501099 scopus 로고    scopus 로고
    • Mobile and localized protons: a framework for understfinding peptide dissociation
    • Wysocki, V. H., Tsaprailis, G., Smith, L. L. and Breci, L.A. (2000) Mobile and localized protons: a framework for understfinding peptide dissociation. J. Mass Spectrom. 35, 1399-406.
    • (2000) J. Mass Spectrom. , vol.35 , pp. 1399-1406
    • Wysocki, V.H.1    Tsaprailis, G.2    Smith, L.L.3    Breci, L.A.4
  • 539
    • 0036808207 scopus 로고    scopus 로고
    • ProbID: a probabilistic algorithm to identify peptides through sequence database searching using tandem mass spectral data
    • Zhang, N., Aebersold, R. and Schwikowski, B. (2002) ProbID: a probabilistic algorithm to identify peptides through sequence database searching using tandem mass spectral data. Proteomics 2, 1406-12.
    • (2002) Proteomics , vol.2 , pp. 1406-1412
    • Zhang, N.1    Aebersold, R.2    Schwikowski, B.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.