Acta Biotheoretica

, Volume 45, Issue 1, pp 1–15 | Cite as

Glue, Verb and Text Metaphors in Biology

  • Ray Paton


Metaphor influences the construction of biological models and theories and the analysis of its use can reveal important tools of thought. Some aspects of biological organisation are investigated through the analysis of metaphors associated with treating biosystems as a kind of text. In particular, the use of glue and verbs is considered. Some of the reasons why glue is important in the construction of hierarchies are pursued in the light of specific examples, and some of the conceptual links between glue in biology and other domains is discussed. Verbs are shown to be important in the construction of networks. Some of the relations between glue, verb and text are considered and the text metaphor is placed within a much broader context of ideas associated with form, relation and system. The paper concludes with comments on the nature of biological information and the need for extending or better understanding the verbal vocabulary.


Broad Context Biological Information Biological Model Biological Organisation Conceptual Link 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. Albrecht-Buchler, G. (1990). In defense of ‘nonmolecular’ biology. International Review of Cytology 120: 191–241.Google Scholar
  2. Barwise, J. (1985). The Situation in Logic-III: Situations, Sets and Axiom of Foundation. Stanford, CA, CSLI Report 85–26, Stanford University.Google Scholar
  3. Barwise, J. and J. Perry (1983). Situations and Attitudes. Cambridge MA, MIT Press.Google Scholar
  4. Brandon, R. (1990). Adaptation and Environment. Princeton NJ, Princeton University Press.Google Scholar
  5. Bruner, J. (1990). Acts of Meaning. Cambridge MA, Harvard University Press.Google Scholar
  6. Clarke, A.G. and R.K. Koehn (1992). Enzymes and adaptation. In: R.J. Berry, T.J. Crawford and G.M. Hewitt, eds., Genes in Ecology, pp. 193–228. Oxford, Blackwell.Google Scholar
  7. Conrad, M. (1989). Physics and biology: Towards a unified approach. Applied Maths and Computation 32: 75–102.Google Scholar
  8. Darden, L. (1991). Theory Change in Science Strategies from Mendelian Genetics. New York, Oxford University Press.Google Scholar
  9. Eldredge, N. (1985). Unfinished Synthesis, Biological Hierarchies and Modern Evolutionary Thought. Oxford, University Press.Google Scholar
  10. Érdi, P. (1993). Neurodynamic system theory: Scope and limits. Theoretical Medicine 14: 137–152.Google Scholar
  11. Feibleman, J.K. (1954). Theory of integrative levels. British Journal for the Philosophy of Science 5: 59–66.Google Scholar
  12. Fellbaum, C. (1990). English verbs as a semantic net. International Journal of Lexicography 3(4): 278–301.Google Scholar
  13. Fillmore, C.J. (1968). The case for case. In: E. Bach E. and R.T. Harms, eds., Universals in Linguistic Theory, pp 1–88. New York, Holt, Rinehart & Winston.Google Scholar
  14. Goodwin, B. C. & Saunders, P.T. (1989) (eds). Theoretical Biology Epigenetic and Evolutionary Order from Complex Systems.-Edinburgh, University Press.Google Scholar
  15. Harré, R. (1970). The Principles of Scientific Thinking. London, Macmillan.Google Scholar
  16. Harré, R. (1986). Varieties of Realism. Oxford, Basil Blackwell.Google Scholar
  17. Hesse, M. (1963). Models and Analogies in Science. London, Sheed and Ward.Google Scholar
  18. Hunt, E.B. (1979). Chapter 1 In: J.W. and R.L. Klatsky, eds., Cotton. Semantic Factors in Cognition. New Jersey, Lawrence ErlbaumGoogle Scholar
  19. Kampis, G. (1991). Self-modifying Systems in Biology and Cognitive Science. Oxford, Pergamon Press.Google Scholar
  20. Kampis, G. (1994). Life-like computing: Beyond the machine metaphor. In: R.C. Paton, R.C., ed., Computing with Biological Metaphors, pp. 393–413. London, Chapman and Hall.Google Scholar
  21. Keil, F. (1989). Concepts, Kinds and Cognitive Development. London, MIT Press.Google Scholar
  22. Kelly, K. (1994). Out of Control The New Biology of Machines. London, Fourth Estate.Google Scholar
  23. Kincaid, H. (1990). Molecular biology and the unity of science.-Philosophy of Science 57: 575–593.Google Scholar
  24. Levins, R. (1984). The strategy of model building in population biology. In: E. Sober, ed., Conceptual Issues in Evolutionary Biology, pp. 18–27. Cambridge MA, Bradford/MIT.Google Scholar
  25. Marijuan, P.C. (1991). Enzymes and theoretical biology: Sketch of an informational perspective of the cell. BioSystems 25: 259–273.Google Scholar
  26. Markman, E.M., M.S. Horton, and A.G. McLanahan (1980). Classes and collections: Principles of organisation in the learning of hierarchical relations. Cognition 8: 227–241.Google Scholar
  27. Medin, D.L. and W.D. Wattenmaker (1987). Category cohesiveness, theories and cognitive archaeology. In: U. Neisser, ed., Concepts and Conceptual Development, pp. 63–100. Cambridge, Cambridge University Press.Google Scholar
  28. Miller, G.A. and C. Fellbaum (1991). Semantic networks in English. Cognition 41: 197–229.Google Scholar
  29. Paton, R.C. (1992). Towards a metaphorical biology. Biology and Philosophy 7: 279–294.Google Scholar
  30. Paton, R.C. (1993a). Some computational models at the cellular level. BioSystems 29: 63–75.Google Scholar
  31. Paton, R.C. (1993b). Understanding biosystem organisation I: Verbal relations. International Journal of Science Education 15(4): 395–410.Google Scholar
  32. Paton, R.C. (1993c). How to build an expert 1: practical applications for rule-based deduction systems. Journal of Biological Education 27(2): 130–138.Google Scholar
  33. Paton, R.C. (1994). Computing with biological metaphors-some conceptual issues. In: R.C. Paton, ed., Computing with Biological Metaphors, pp. 424–437. London, Chapman and Hall.Google Scholar
  34. Paton, R.C., H.S. Nwana, M.J.R. Shave and T.J.M. Bench-Capon (1994). An examination of some metaphorical contexts for biologically motivated computing. British Journal for the Philosophy of Science 45: 505–525.Google Scholar
  35. Paton, R.C., G. Staniford and G. Kendall (1995). Specifying Logical Agents in Cellular Hierarchies. Proceedings of International Workshop on Information Processing in Cells and Tissues-IPCAT '95, Liverpool.Google Scholar
  36. Pattee, H.H. (1977). Dynamic and linguistic modes of complex systems. International Journal of General Systems 3: 259–266.Google Scholar
  37. Polanyi, M. (1968). Life's irreducible structure. Science 160: 1308–1312.Google Scholar
  38. Pollack, R. (1994). Signs of Life The Language and Meanings of DNA. London, Viking.Google Scholar
  39. Rashevsky, N. (1973). The principle of adequate design. In: R. Rosen, ed., Foundations of Mathematical Biology Volume III Supercellular Systems, pp. 145–175. New York, Academic Press.Google Scholar
  40. Roitt, I. (1980). Essential Immunology, 4th Edition. Oxford, Blackwell.Google Scholar
  41. Rosen, R. (1972). Foundations of Mathematical Biology 2: Cellular Systems. New York, Academic Press.Google Scholar
  42. Rosen, R. (1973). Is there a unified mathematical biology? In: R. Rosen, ed., Foundations of Mathematical Biology Volume III Supercellular Systems, pp. 361–393. New York, Academic Press.Google Scholar
  43. Rosen, R. (1986). Causal structures in brains and machines. Int. J. General Systems 12: 107–126.Google Scholar
  44. Rosen, R. (1988). Information and complexity. Journal of Computational and Applied Mathematics 22: 211–218.Google Scholar
  45. Rosen, R. (1991). Life Itself. New York, Columbia University Press.Google Scholar
  46. Salthe, S.N. (1991). Two forms of hierarchy theory in western discourses. Int. J. Gen. Systems 18: 251–264.Google Scholar
  47. Sattler, R. (1986). Biophilosophy. Berlin, Springer-Verlag.Google Scholar
  48. Sattler, R. (1993a). Why do we need a more dynamic study of morphogenesis? Descriptive and Comparative Aspects. In: D. Barabé and R. Brunet, eds), Morphogenese et Dynamique. Paris, Orbis Publishing.Google Scholar
  49. Sattler, R. (1993b). personal communication.Google Scholar
  50. Schrödinger, E. (1992). What is Life? Canto Edition. Cambridge, Cambridge University Press [First published in 1944].Google Scholar
  51. Soskice, J.M. (1985). Metaphor and Religious Language. Oxford, Clarendon Press.Google Scholar
  52. Szontágothai, J. and P. Érdi (1989). Self organisation in the nervous system. Journal of Social and Biological Structures 12: 367–384.Google Scholar
  53. Thom, R. (1975). Structural Stability and Morphogenesis. Reading MA, W.A. Benjamin.Google Scholar
  54. Thompson, D'Arcy W. (1942). On Growth and Form A New Edition. Cambridge, Cambridge University Press.Google Scholar
  55. Varela, F.J. (1979). Principles of Biological Autonomy. New York, NorthHolland.Google Scholar
  56. Welch, G.R. (1994). The computational machinery of the living cell. In: R.C. Paton, ed., Computing with Biological Metaphors, pp. 40–49. London, Chapman and Hall.Google Scholar
  57. Yates, F.E. (1987). Quantumstuff and biostuff. In: F.E. Yates, ed,, Self-organising Systems, pp. 617–644. New York, Plenum.Google Scholar
  58. Yates, F.E. (1993). Self-organising systems. In: C.A.R. Boyd and D. Noble, eds., The Logic of Life, pp. 189–217. University Press, Oxford.Google Scholar
  59. Zylstra, U. (1992). Living things as hierarchically organised structures. Synthese 91: 111–133.Google Scholar

Copyright information

© Kluwer Academic Publishers 1997

Authors and Affiliations

  • Ray Paton
    • 1
  1. 1.The Liverpool Biocomputation Group, Department of Computer ScienceThe University of LiverpoolLiverpoolU.K

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