Analogical reasoning for knowledge discovery in a molecular biology database

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Analogical reasoning for knowledge discovery in a molecular biology database

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Conference on Information and Knowledge Management archive
Proceedings of the second international conference on Information and knowledge management table of contents

Washington, D.C., United States

Pages: 554 - 564

Year of Publication: 1993

ISBN:0-89791-626-3

Authors

Juergen Haas	Department of Genetics, University of Pennsylvania, School of Medicine, Room 475, Clinical Research Building, 422 Curie Boulevard, Philadelphia, PA
Jeffrey S. Aaronson	Department of Genetics, University of Pennsylvania, School of Medicine, Room 475, Clinical Research Building, 422 Curie Boulevard, Philadelphia, PA
G. Christian Overton	Department of Genetics, University of Pennsylvania, School of Medicine, Room 475, Clinical Research Building, 422 Curie Boulevard, Philadelphia, PA

Sponsors

Inst Soc for Comp & Applic : Inst Soc for Comp & Applic
SIGART: ACM Special Interest Group on Artificial Intelligence
SIGIR: ACM Special Interest Group on Information Retrieval

Publisher

ACM New York, NY, USA

Bibliometrics

Downloads (6 Weeks): 1, Downloads (12 Months): 15, Citation Count: 0

Additional Information:

references index terms collaborative colleagues peer to peer

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REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

	1	Jeffery S. Aaronson , Juergen Haas , G. Christian Overton, Knowledge Discovery in GENBANK, Proceedings of the 1st International Conference on Intelligent Systems for Molecular Biology, p.3-11, July 01, 1993
	2	W. C. Barker et al. Protein Sequence Database of the Protein Identification Resource (PIR). CODATA Exchange Format Specification Document CXFSD-0687, 1987
	3	Burks C., Cassidy, M., Cinkosky, M. J., Cumella, K. E., Gilna, P., Hayden, j. E., Keen, G. M., Kelley, T. A., Kelly, M., Kristofferson, D. and Ryals~ J. Gen- Bank. Nucleic Acid Res. 19 (Suppl):2221-2225, 1991.
	4	Thomas G. Dietterich. Machine Learning, volume 4, pages 255-306. Annual Reviews Inc., 4139 E1 Camino Way, P.O. Box 10139, Palo Alto CA 94303-0897, 1990.
	5	J. Doyle. A Truth Maintenance System. Artificial Intelligence, 12(3), 1979.
	6	Haas, J., Aaronson, j. S. and Overton, G. C.(1993). Grammar Induction on Gene Structure Grammars. Technical report, University of Pennsylvania. In preparation.
	7	Hart, K., Searls, D. B., and Overton, G. C. (1993). SORTEZ: A relational translation of NCBI's ASN.1 database. Submitted for publication.
	8	Janet L. Kolodner. Experiential Processes in Natural Problem Solving. Technical Report GIT-ICS-85/23, School of Information and Computer Science, Georgia Institute of Technology, Atlanta, GA 30332, 1985.
	9	Janet L. Kolodner, Robert L. Simpson, Jr., and Katia Sycara-Cyranski. A Process Model of Case-Based Reasoning in Problem Solving. In Proceedings of the N~nth International Joint Conference on Artificial Intelhgence, pages 284-290. Morgan Kaufmann, 1985.
	10	Pat Langely, Machine Learning and Grammar Induction, Machine Learning, v.2 n.1, p.5-8, 1987 [doi>10.1023/A:1022808826027]
	11	Alan S. Lapedes. Applice~tions of Neural Networks and Other Machine Learning Algorithms to DNA Sequence Analysis. In G. Bell and T. Marr, editors, Computers and DNA, Reading, MA, 1990. Santa Fe Institute, Addison-Wesley.
	12	David S. Latchman. Eukaryoi~c Transcription Faclors. Academic Press Inc, San Diego, CA, 92101, 1991.
	13	Michael Lebowitz. Generalization from Natural Language Text. Cognitive Science, 7(1):1-40, 1983.
	14	Overton, G. C., Koile, K., and Pastor, J. A. (1989). GeneSys: A knowledge management system for molecular biology. In Bell, G. and Mart, T., editors, Computers and DNA, pages 213-240, Reading, MA. Addison- Wesley.
	15	Overton, G. C. and Pastor, J. A. (1991). A Platform for Applying Multiple Machine Learning Strategies to the Task of Understanding Gene Structure. In Proceedings of the 7th Conference on Artificial lnt~lhgcnce Applications, volume I:Technical Papers, pages 450-457.
	16	Overton, G. C., Aaronson, J., Haas, J., and Adams, J. (1994). QGB: A System for Querying Sequence Database Fields and Features. To appear in the Journal of Computational Molecular Cell Biology, Vol 1 nool.
	17	Pastor, J. A., Koile, K., and Overton, G. C. (1991). Using analogy to predict functional regions on genes. In Proceedings of the 2dth ttawai~ International Conference on'System Science, volume I, p~ges 615-625.
	18	Pearson, W. R. and Lipman, D. J. (1988). In Proc. Natl. Acad. $ci., volume 85, pages 2444-2448.
	19	Rajasekhar, R. ~nd Overton, G. C. (1993). An Unsupervised Hierarchical Clustering Algorithm for Unequal Length Vectors. Technical report, University of Pennsylvania. In preparation.
	20	Searls, D. B. (1989). Investigating the linguistics of DNA with Definite Clause Grammars. In Lusk, E. and Overbeek, R., editors, Logic Programming: Proceedings of the North American Conference, Vol. 1, volume 1, pages 189-208. MIT Press.
	21	Michael S. Waterman, Mathematical Methods for DNA Sequences, CRC Press, Inc., Boca Raton, FL, 1989
	22	Michael S. Waterman (1989b). Consensus patterns in sequences. In Michael S. Waterman, editor, Mathematical Methods for DNA Sequences, pages 93~115, Boca Raton, FL, 1989. CRC Press.

INDEX TERMS

Primary Classification:
I. Computing Methodologies
I.2 ARTIFICIAL INTELLIGENCE
I.2.6 Learning
Subjects: Analogies

Additional Classification:
H. Information Systems
H.2 DATABASE MANAGEMENT

J. Computer Applications
J.3 LIFE AND MEDICAL SCIENCES
Subjects: Biology and genetics

General Terms:
Design, Human Factors, Management, Measurement, Performance, Theory

Collaborative Colleagues:

Juergen Haas: colleagues

Jeffrey S. Aaronson: colleagues

G. Christian Overton: colleagues

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