References
- Agrawal, R., et al. (1995). Fast discovery of association rules. In Proceedings of the 1st International Conference on Knowledge Discovery and Data Mining. (AAAI Press), 3-8
- Ai, C.S., Blower, P.E., and Ledwith, R.H. (1991). Extracting reaction information from chemical databases. In PiatetskyShapiro, G. and W. J. Frawley ,eds. Knowledge Discovery in Databases, (Cambridge, MA:AAAI/MIT Press), 367-381
- Bahler, D. and Bristol, D.W. (1993). The induction of rules for predicting chemical carcinogenesis in rodents. Proceedings of the First International Conference on Intelligent Systems for Molecular Biology (Menlo Park, CA:AAAI Press), 29-37
- Banfield, J. and Raftery, A. (1993). Model-based Gaussian and non-Gaussian Clustering. Biometrics. 49, 803-821 https://doi.org/10.2307/2532201
- Beer, D. et al. (2002). Gene-expression profiles predict survival of patients with lung adenocarcinoma. Nature Medicine. 8, 816-824
- Breiman, L., Friedman, J., Olshen, R., and Stone, C.J. CART:Classification and Regression Trees.(Belmont, CA:Wadsworth Press)
- Breiman, L., Friedman, J., Olshen, R., and Stone, C.J. CART:Classification and Regression Trees.(Belmont, CA:Wadsworth Press)
- Burr, T., Gattiker, J.R., and LaBerge, G.S. (2001). Genetic Subtyping using Cluster Analysis. SIGKDD Explorations. 3, 33-42 https://doi.org/10.1145/507533.507539
- Chatfield, C. (1995). Model uncertainty, data mining, and statistical inference. J. R. Statist. Soc. (A).158, 419-466 https://doi.org/10.2307/2983440
- Cook, D.J. and Holder, L. (1994). Substructure discovery using minimum description length and background knowledge. Journal of Artificial Intelligence Research. 1, 231-255
- Decker, K.M. and Foccardi, S. (1995). Technology overview: a report on data mining. Technical Report CSCS TR-95-02. (Swiss Scientific Computing Center, Manno, Switwerland)
- Elder, J. and Pregibon, D. (1996). A statistical perspective on KDD, Advances in Knowledge Discovery and DataMining. U. Fayyad, et al eds. (Cambridge, MA:AAAI/MIT Press), 83-114
- Engels, M.F.M., Knapen, K., and Tollenaere, J.P. (2001). Approaches for Mining High-throughput Screening Data Sets. Paper presented on the 13th European Symposium on Quantitative Structure-Activity Relationships, Dusseldorf, Germany
- Fayyad, U.M., Piatetsky-Shapiro,G., Smyth, P., and Uthurasamy, R. (1996). Advances in KnOWledge Discovery and Data Mining. (Cambridge, MA: AAAI/MIT Press)
- Fayyad, U.M., Haussler, D., and Stolorz, P. (1996). KDD for science dataanalysis: issues andexamples. InProceedings of the 2nd International Conference on Knowledge Discovery and Data Mining. E. Simoudis and J. Han eds. (Menlo Park,CA:AAAI Press), 50-56
- Friedman, H.P. and Goldberg, J.D. (2000). Knowledge Discovery from Databases and Data Mining: New Paradigms for Statistics and Data Analysis? pharmaceutical Report.8(2), Biopharmaceutical Section, American Statistical Association
- Glymour, C., Madigan, D., Pregibon, D., and Smyth, P. (1996). Data mining and statistics Communications of the ACM. 39, 35-41
- Hastie, T., Tibshirani, R., Eisen, M., Alizadeh, A., Levy, R., Staut, L., Botstein, D., and Brown, P. (2000). Identifying distinct set of genes with similar expression patterns via gene Genome Biology.shaving. Genome Biology. 1, 1-21
- Heckerman, D. (1996). Bayesian networks for knowledge discovery. In Advanced in Knowledge Discovery and Data Mining, U. Fayyad et al. eds. (AAAI/MIT Press), 273-305
- Hennessy, D. et al. (1995). Induction of rules for biological macromolecule cystanization. Proceedings of the Third International Conference on Intelligent Systems for Molecular Biology. (Menlo Park, CA:AAAI Press), 179-187
- Jain, A. N., et al. (1994). Compass: a shape-based machine learning too for drug design. Journal of Computer-Aided Molecular Design. 8, 635-652 https://doi.org/10.1007/BF00124012
- Lee, K.R., Lin, X., Park, D.C., Eslava S. (2003). Megavariate data analysis of mass spectrometric proteomics data using latent variable projection method. Proteomics. 3, 1680-1686 https://doi.org/10.1002/pmic.200300515
- Lee, K.R., Lydick, E., Park, D.C., Lin, X. (2001). Exploratory Data Analysis of Irregular Patterns of Longitudinal Laboratory Data from Clinical Trials - A case study of liver function test. Proceedings of 10th World Congress on Medical Informatics, London, UK.873
- Lin,X., Park, D.C., Eslava, S., Lee,K.R., Lam, L.H., and Zhu LA (2003). Making Sense of Human Lung Carcinomas Gene Expression Data: Integration and Analysis of Two Affymetrix Platform Experiments. Proceedings of Critical Assessment of Microarray Data Analysis (CAMDA03), Durham, NC, USA, 2327
- Mannila, H. (1996). Data mining: machine learning, statistics, and databases. Proceedings of the 19961ntemational Conference on Machine Learning, (San Mateo, CA: Morgan Kaufmann Publishers), also available on the Web at http://www.cs.helsinki.fi/-mannila
- Mannila, H. and Toivonen, H. (1996). Discovering generalized episodes using minimal occurences. Proceedings of the 2nd International Conference on Knowledge Discovery and Data Mining(AAAI Press), 146-151
- Moore, J.S., Parker J.S., Olsen, N.S., and Aune, T.M. (2002). Symbolic discriminant analysis of microarray data in automimmune disease. Genetic Epidemiology. 23,57-69 https://doi.org/10.1002/gepi.1117
- Muggleton, S., King, R., and Sternberg, M. (1992). Protein secondary structure prediction using logic. Protein Engineering. 5,647-657 https://doi.org/10.1093/protein/5.7.647
- Michie, D., Spiegelhalter, D.J., and Taylor, C.C. (1994). Machine Leaming, Neural and Statistical Classification. (New York: Ellis Horwood)
- Olaleye, D. and Tardiff, B.E. (2001). Practical Issues in and Applications of Clinical Data Mining. DrugInformation Journal. 35,791-808
- Piatetsky-Shapiro, G. and Frawley, W.J. (1991). Knowledge Discovery in Databases. (Cambridge, MA:AAAIIMIT Press)
- Quinlan, J.R. (1993). C4.5: Programs for Machine Learning, San Mateo. (CA: Morgan Kaufmann)
- Smyth, P. and Goodman, R.M. (1992). An information theoretic approach to rule induction from databases. IEEE Transactions on Knowledge and Data Engineering. 4, 301-316 https://doi.org/10.1109/69.149926
- Smyth, P. (1996). Clustering using Monte Carlo cross-validation. Proceedings of the 2nd International Conference on Knowledge Discovery andData Mining. (AAAI Press) 126-133
- Smyth, P., Heckerman, D., andJordan, M.I. (1997). Probabilistic independence networks for hidden Markov probability models. Neural Computation. 9, 227-269 https://doi.org/10.1162/neco.1997.9.2.227
- Tibshirani, R., Hastie, T., Botstein, D., and Brown, P. (2001). Supervised harvesting of expression trees. Genome Biology 2, 1-12
- Vohradsky, J. and Thompson, C.J. (1997). Identification of procaryotic developmental stages by statistical analyzes of two-dimensional gelpatterns. Electrophoresis 18,1418-1428 https://doi.org/10.1002/elps.1150180817