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Knowledge Discovery in Molecular Databases
December 1993 (vol. 5 no. 6)
pp. 985-987

An approach to knowledge discovery in complex molecular databases is described. The machine learning paradigm used is structured concept formation, in which object's described in terms of components and their interrelationships are clustered and organized in a knowledge base. Symbolic images are used to represent classes of structured objects. A discovered molecular knowledge base is successfully used in the interpretation of a high resolution electron density map.

[1] F. H. Allen et al., "The development of versions 3 and 4 of the Cambridge Structural Database System,"J. Chem. Inf. Comp. Sci., May 1991.
[2] F. C. Bernstein et al., "The protein data bank: A computer-based archival file for macromolecular structures,"J. Mol. Biol., vol. 112, pp. 535-542, 1977.
[3] D. Conklin, S. Fortier, and J. Glasgow, Representation for discovery of protein motifs. In L. Hunter, D. Searls, and J. Shavlik, editors,Proceedings of the First International Conference on Intelligent Systems for Molecular Biology, pp. 101-108. AAAI/MIT Press, 1993.
[4] D. Conklin and J. Glasgow, "Spatial analogy and subsumption," inMachine Learning: Proc. Ninth Int. Conf. (ML92). D. Sleeman and P. Edwards, Eds. Morgan Kaufmann, 1992.
[5] D. Fisher, "Knowledge acquisition via incremental conceptual clustering,"Mach. Learning, vol. 2, pp. 139-172, 1987.
[6] S. Fortier, I. Castleden, J. Glasgow, D. Conklin, C. Walmsley, L. Leherte, and F. Allen, "Molecular scene analysis: The integration of direct methods and artificial intelligence strategies for solving protein crystal structures,"Acta Crystallographica, vol. D1, 1993.
[7] J. Gennari, "Models of Incremental Concept Formation,"Artificial Intelligence, Vol. 40, No. 1-3, 1989, pp. 11-62.
[8] J. I. Glasgow, S. Fortier, and F. H. Allen, "Molecular scene analysis: crystal structure recognition through imagery," inArficial Intell. and Molecular Biol, L. Hunter, Ed. AAAI Press, 1992.
[9] R. M. Haralick and L. G. Shapiro,Computer and Robot VisionReading, MA: Addison-Wesley, vol. II, 1993, pp. 357-361.
[10] T. A. Jones and S. Thirup, "Using known substructures in protein model building and crystallography,"EMBO J., vol. 5, no. 4, pp. 819-822, 1986.
[11] W. Kabsch and C. Sander, "Dictionary of protein secondary structure,"Biopolymers, vol. 22, pp. 2577-2637, 1983.
[12] J. L. Kolodner, "Maintaining organization in a dynamic long-term memory, "Cognitive Sci., vol. 7, pp. 243-280, 1983.
[13] R. S. Michalski and R. E. Stepp, "Learning from observation: conceptual clustering," inMachine Learning, R. Michalski, J. Carbonell, and T. Mitchell, Eds. Tioga, pp. 331-363, 1983.
[14] B. Nebel,Reasoning and Revision in Hybrid Representation Systems. Berlin: Springer-Verlag, 1990.
[15] K. Thompson and P. Langley, "Concept Formation in Structured Domains," inConcept Formation: Knowledge and Experience in Unsupervised Learning, D. Fisher, M. Pazzani, and P. Langley, eds., Morgan Kaufmann, San Mateo, Calif., 1991, pp. 127-164.
[16] J. Wogulis and P. Langley, "Improving efficiency by learning intermediate concepts, " inProc. IJCAI-89. Morgan Kaufmann, 1989, pp. 657-662.

Index Terms:
case-based reasoning; chemical information retrieval; conceptual clustering; description logics; indexing; relational models; scene analysis; spatial concepts; spatial reasoning; structured concept formation; knowledge discovery; molecular databases; machine learning paradigm; knowledge base; symbolic images; molecular knowledge base; high resolution electron density map; case-based reasoning; chemistry computing; deductive databases; factographic databases; learning (artificial intelligence); relational databases; visual databases
Citation:
D. Conklin, S. Fortier, J. Glasgow, "Knowledge Discovery in Molecular Databases," IEEE Transactions on Knowledge and Data Engineering, vol. 5, no. 6, pp. 985-987, Dec. 1993, doi:10.1109/69.250082
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