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Computerized Implementation of Biomedical Theory Structures: an Artificial Intelligence Approach

Published online by Cambridge University Press:  28 February 2022

Kenneth F. Schaffner*
Affiliation:
University of Pittsburgh

Extract

At a recent conference I attended involving physicists, biologists, historians, and sociologists, a question about the development of theory in biology in comparison with theory in physics arose, with special interest in the nature of the theorists in the two domains and where they ranked in prestige. The biologists, primarily biochemists, maintained that “theory had a bad name in contemporary biology.” As they saw it from the perspective of biochemists and bench scientists, experimental work was much more highly regarded than theoretical work in biology, in interesting contrast to physics.

Certainly not all biologists are theory averse. In the preface to the first of three volumes edited by C.H. Waddington, the late distinguished geneticist wrote in 1968 that he felt” …that the time is ripe to formulate some skeleton of concepts and methods around which Theoretical Biology can grow….

Type
Part II. Biology and Medicine
Copyright
Copyright © 1987 by the Philosophy of Science Association

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Footnotes

1

Grateful acknowledgement is made both to the National Science Foundation and the National Endowment for the Humanities for support of my research on theory structure in the biomedical sciences. I also want to thank Professors Harry Pople, Clark Glymour, and Herbert Simon for stimulating discussions about the application of artificial intelligence techniques to knowledge representation in biology and medicine.

References

AAAI-86 (1986) Proceedings AAAI-86: Fifth National Conference on Artificial Intelligence. Los Altos, CA: Morgan Kaufman.Google Scholar
Beckwith, J. and Zipser, D. (eds.) (1970) The Lactose Operon Cold Spring Harbor, N.Y: Cold Spring Harbor Laboratory.Google Scholar
Brachman, R. (1985) ‘“I Lied about the Trees’ or Defaults and Definitions in Knowledge Representation,” AI Magazine 6, No. 3: 80-93.Google Scholar
Burstein, M.H. (1986) “Concept Formation by Incremental Analogical Reasoning and Debugging.” In Michalski, R., Carbonell, J. and Mitchell, T. (1986) (eds.) Machine Learning Vol. II. Los Altos, CA: Morgan Kaufmann. Pp. 351-369.Google Scholar
Carbonell, J. (1986) “Derivational Analogy.” In Michalski, R., Carbonell, J. and Mitchell, T. (1986) (eds.) Machine Learning Vol. II. Los Altos, CA: Morgan Kaufmann. Pp. 371-392.Google Scholar
Charniak, E. and McDermott, D. (1985) An Introduction to Artificial Intelligence. Reading, MA: Addison-Wesley.Google Scholar
Cohen, B. and Murphy, G.L. (1984) “Models of Concepts.” Cognitive Science 8: 27-58.CrossRefGoogle Scholar
Cohen, B. (1982) Understanding Natural Kinds.” Unpublished Ph.D. Dissertation, Stanford University.Google Scholar
Darden, L. and Rada, R. (1986) “Hypothesis Formation via Interrelations.” To appear in Proceedings of Analogica ‘85. Rutgers University Computer Science Department.Google Scholar
Etherington, D. and Reiter, R. (1983) “On Inheritance Hierarchies with Exceptions,” Proceedings of AAAI-83, Washington, D.C. pp. 104-108.Google Scholar
Fahlman, S. (1979) NETL: A System for Representing and Using Real World Knowledge. Cambridge: MIT Press.CrossRefGoogle Scholar
Fikes, R. and Kehler, T. (1985) “The Role of Frame-Based Representation in Reasoning,” Communications of the ACM 28, No. 9: 904-920.CrossRefGoogle Scholar
Forbus, K.D. and Gentner, D. (1986) “Learning Physical Domains: Toward a Theoretical Framework.” In Michalski, R., Carbonell, J. and Mitchell, T. (1986) (eds.) Machine Learning Vol. II. Los Altos, CA: Morgan Kaufmann. Pp. 311-348.Google Scholar
Friedland, P. and Kedes, L. (1985) “Discovering the Secrets of DNA” Computer, Nov. 1985: 49-69.CrossRefGoogle Scholar
Grene, M. (1978). “Individuals and Their Kinds: Aristotelian Foundations of Biology,” in S. Spicker (ed.) Organism, Medicine, and Metaphysics Dordrecht, Reidel. Pp. 121-36.CrossRefGoogle Scholar
Hanks, S. and McDermott, D. (1986) “Default Reasoning, Nonmonotonic Logics, and the Frame Problem,” in Proceedings of the AAAI, Vol. 1. Los Altos: Morgan Kaufmann. Pp. 328-333.Google Scholar
Hull, D. (1974) Philosophy of Biological Science. Englewood-Cliffs, N.J.: Prentice- Hall.Google Scholar
Jacquard, A. (1974) The Genetic Structure of Populations. New York: Springer-Verlag.CrossRefGoogle Scholar
Jacob, F. and Monod, J. (1961) “Genetic Regulatory Mechanisms in the Synthesis of Proteins,” Journal of Molecular Biology 3: 318.Google Scholar
Kuhn, T. (1970) The Structure of Scientific Revolutions. (2nd edition.) Chicago: University of Chicago Press.Google Scholar
Lewin, B. (1985) Genes II (Second Edition). New York: John Wiley.Google Scholar
McDermott, D. and Doyle, J. (1980) “Non-monotonic Logics,” Artificial Intelligence 13: 41-72.CrossRefGoogle Scholar
Miller, J. and Reznikoff, W. (eds.). (1978) The Operon Cold Spring Harbor, N.Y.: Cold Spring Harbor Laboratory.Google Scholar
Minsky, M. (1975). “A Framework for Representing Knowledge,” in P. Winston (ed.) The Psychology of Computer Vision New York: McGraw-Hill.Google Scholar
Morowitz, H. (1987) [See essay preceeding this one in this volume.]Google Scholar
National Academy of Sciences, (1985) Models for Biomedical Research: A New Perspective. Washington, DC.: National Academy of Sciences Press.Google Scholar
Osherson, D. and Smith, E. (1981) “On the Adequacy of Prototype Theory as a Theory of Concepts,” Cognition 9: 35-58.CrossRefGoogle Scholar
Oster, G.F. and Wilson, E.O. (1978) Caste and Ecology in the Social Insects. Princeton: Princeton University Press.Google ScholarPubMed
Putnam, H. (1975). “The Meaning of ‘Meaning'” in K. Gunderson (ed.) Minnesota Studies in the Philosophy of Science VII. Minneapolis: University of Minnesota Press. Pp. 131-193.Google Scholar
Rosch, E. (1976). “Classification of Real-World Objects: Origins and Representations in Cognition. In Johnsen-Laird, P. N. and Wason, P. C. (eds.) Thinking: Readings in Cognitive Science. Cambridge: Cambridge University Press.Google Scholar
Rosch, E. and Mervis, C. (1975) “Family Resemblances: Studies in the Internal Structure of Categories,” Cognitive Psychology 7: 573-605.CrossRefGoogle Scholar
Rosenberg, A. (1985) The Structure of Biological Science Cambridge: University of Cambridge Press.CrossRefGoogle Scholar
Ruse, M. (1973) Philosophy of Biology London: Hutchinson.Google Scholar
Schaffner, K. (1980) “Theory Structure in the Biomedical Sciences,” Journal of Medicine and Philosophy 5: 57-97.CrossRefGoogle Scholar
Schaffner, K. (1986) “Exemplar Reasoning about Biological Models and Diseases: a Relation between the Philosophy of Medicine and Philosophy of Science” Journal of Medicine and Philosophy, 11 (March, 1986) pp. 63-80.CrossRefGoogle Scholar
Smart, J.J.C. (1968) Between Science and Philosophy New York: Random House.Google Scholar
Smith, T. F. and Sadler, J. R. (1971) “The Nature of Lactose Operator Constitutive Mutations.” Journal of Molecular Biology 59: 273.CrossRefGoogle Scholar
Sober, E. (ed.) (1984) Conceptual Issues in Evolutionary Biology. Cambridge: MIT Press.Google Scholar
Suppe, F. (ed.) (1977) The Structure of Scientific Theories. (Second enlarged edition). Urbana: University of Illinois Press.Google Scholar
Touretzky, D. (1986) The Mathematics of Inheritance Systems Los Altos: Morgan Kaufmann.Google Scholar
Waddington, C.H. (1968) Towards a Theoretical Biology. Vol. I. Chicago: Aldine Press.CrossRefGoogle ScholarPubMed
Williams, M. (1970) “Deducing the Consequences of Evolution: A Mathematical Model.” Journal of Theoretical Biology 29:343-385.CrossRefGoogle Scholar
Winston, P. (1984) Artificial Intelligence. Second edition. Reading MA: Addison Wesley.Google Scholar
Winston, P. (1986) “Learning by Augmenting Rules and Accumulating Censors.” In Michalski, R., Carbonell, J. and Mitchell, T. (1986) (eds.) Machine Learning Vol. II. Los Altos, CA: Morgan Kaufmann. Pp. 45-61.Google Scholar
Winston, P. and Horn, B. (1984) LISP 2nd edition Reading, MA: Addison-Wesley.Google Scholar
Woodger, J. (1937) The Axiomatic Method in Biology Cambridge: Cambridge University Press.Google Scholar
Wright, S. (1931) “Evolution in Mendelian Populations.” Genetics 16: 97-159.CrossRefGoogle Scholar