In proceedings of the 18th national conference on

Info iconThis preview shows page 1. Sign up to view the full content.

View Full Document Right Arrow Icon
This is the end of the preview. Sign up to access the rest of the document.

Unformatted text preview: holm, Sweden, 1999. P roceedings of the Sixteenth International Joint Conference on Artificial I ntelligence (IJCAI99). [ BBF+99b] P. Baldi, S. Brunak, P. Frasconi, G. Pollastri, and G. Soda. Exploiting the p ast and the future in protein secondary structure prediction. Bioinformatics, 1 5:937-946, 1999. [ BdLBF60] E.R. Blout, C. de Lozé, S.M. Bloom, and G.D. Pasman. Dependence of the conformation of synthetic polypeptides on amino acid composition. J. Am. Chem. Soc, 8 2:3787-3789, 1960. [Bel95] T.C. Belding. The distributed genetic algorithm revisited. In Proceedings of the Sixth International Conference on Genetic Algorithms, p ages 1 14-121, 1 995. 180 Clasificación Supervisada Basada en RRBB. Aplicación en Biología Computacional [Ben02] E. Bengoetxea. Inexact Graph Matching using Estimation of Distribution Algorithms. P hD thesis, Escuela Nacional de Telecomunicaciones, París, Octubre 2002. [BFOS84] L. Breiman, J.H. Friedman, R.A. Olshen, and C.J. Stone. Classification and Regression Trees. W adsworth International Group, 1984. [BGL"'"88] V. Biou, J.F. Gibrat, J.M. Levin, B. Robson, and J. Garnier. Secondary structure prediction: combination of three diíferent methods. Protein Engineering, 2 :185-191, 1988. [Bis95] C. Bishop. Neural Networks for Pattem Recognition. C larendon Press, Oxford, 1 995. [Blo62] E.R. Blout. The dependence of the conformation of polypetides and pro- teins upen amino acid composition. pages 275-279. Univ. of Wisconsin Press, M adison, 1962. [Bre94] L. Breiman. Baggings predictors. Technical report, Technical Report Statistic Department, University of California at Berkeley, 1994. [BS88] B. Buchanan and R. Smith. Fundamentáis of expert systems. Annual Review of Computer Science, 3 :23-58, 1988. [BT88] G. Barton and W.R. Taylor. Prediction of protein secondary structure and a ctive sites using the aligmnent of homologous sequences. Journal of Molecular Biology, 195:957-961, 1988. [Bun91] W. Buntine. Classifiers: a theoretical and empirical study. In Proceedings of the IJCAI, p ages 638-655, 1991. [BvH87] O. G. Berg and P.H. von Hippel. Selection of dna binding sites by regulatory proteins. Journal of Molecular Biology, 193:723-750, 1987. [BW03] P. E. Bourne and H. Weissig, editors. Structural Bioinformatics. John Wiley & S ons, Inc., 2 003. [ BWF+00] H.M. Hermán, J. Westbrook, Z. Feng, G. Gilliand, T.N. Bhat, H. Weissig, I.N. S hindyalov, and P.E. Bourne. The protein data bank. Nucleid Acid Research, 2 8:235-242, 2000. [CB99] J.A. Cuff and G.J. Barton. Evaluation and improvement of múltiple sequence m ethods for protein secondary structure prediction. Proteins, 3 4:508-519, 1999. [CCS+98] J.A. Cuff, M.E. Clamp, A.S. Siddiqui, M. Finlay, and G.J. Barton. JPRED: A c onsensus secondary structure prediction server. Bioinformatics, 1 998. [Ces90] 1 4:892-893, B. Cestnik. Estimating probabilities: a crucial task in machine learning. In Proceedings of the European Conference on Artificial Intelligence, p ages 147149, 1990. BIBLIOGRAFÍA 181 [CF74] P.Y. Chou and U.D. Fasman. Prediction of protein conformation. try, 1 3:222-245, 1974. Biochemis- [CG83] P. Cohén and M. Grinberg. A framework for heuristic reasoning about uncertainty. In Proceedings of the 8th International Joint Conference on Artificial Intelligence (IJCAI-83)^ p ages 355-357, Karlsruhe, Germany, 1983. [CG99] J. Cheng and R. Greiner. Comparing Bayesian network classifiers. In Proceedings of the 15th Conference on Uncertainty in Artificial Intelligence, p ages 1 01-107, 1999. [CGH97] E. Castillo, J.M. Gutiérrez, and A.S. Hadi. Expert Systems and Probabilistic Network Modela. S pringer, 1997. [ CGK+02] J. Cheng, R. Greiner, J. Kelly, D.A. Bell, and W. Liu. Learning Bayesian n etworks from data: an information-theory based approach. Artificial Intelligence, 1 37:43-90, 2002. [CK89] F.E. Cohén and I.D. Kuntz. Tertiary structure prediction. In G.D. Fasman, e ditor, In Prediction of Protein Structure and the Principies of Protein Conformation, p ages 647-706. Plenum Press, New York, London, 1989. [CK95] J.-M. Chandonia and M. Karplus. Neural networks for secondary structure a nd structural class predictions. Prot. Sai., 4 :275-285, 1995. [CKB87] B. Cestnik, I. Kononenko, and I. Bratko. ASSISTANT-86: a knowledge elicitation tool for sophisticated users. In I. Bratko and N. Lavrac, editors, Progress in Machine Learning. S igma Press, 1987. [CL68] C. Chow and C. Liu. Approximating discreta probability distributions with d ependence trees. IEEE Transactions on Information Theory, 1 4:462-467, 1968. [CN89] P. Clark and T.Ñiblett. The CN2 induction algorithm. Machine 3 :261-283, 1989. [Coh95] W.W. Cohén. Fast eíFective rule induction. In Machine Learning: Proceedings of the Twentieth International Conference, L ake Tahoe, California, 1995. [CowOl] R. Cowell. On searching for optimal classifiers among Bayesian networks. In T . Jaakkola and T. Richardson, editors, Proceedings of the 8th International Conference on Art...
View Full Document

This note was uploaded on 02/01/2012 for the course . . taught by Professor . during the Spring '11 term at Pontificia Universidad Católica de Chile.

Ask a homework question - tutors are online