Skip to main content

Semiotic Explanation in the Biological Sciences

  • Chapter
  • First Online:
Explanation in the Special Sciences

Part of the book series: Synthese Library ((SYLI,volume 367))

  • 1045 Accesses

Abstract

Many biological explanations are given in terms of transduced signals and of stored and transferred information. In the following, I call such information-theoretical explanations “semiotic explanations.” Semiotic explanation was hardly ever discussed as a distinct type of explanation. Instead, philosophers looked at information transfer as a somewhat unusual subject of mechanistic explanation and consequently attempted to frame biological information as being observable within physicochemical mechanisms. However, information-theoretical terms never occur in isolation or as a plug-in in mechanistic models but always in the context of information-theoretical models like the semiotic model of protein biosynthesis. This chapter proposes that “information” enters the game as a theoretical term of semiotic models rather than as an observable and that semiotic models have explanatory value by explaining molecular mechanisms in functional rather than in mechanistic terms.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    In Krohs (2009a, 2011), I deal with the first kind of explanation.

  2. 2.

    For a detailed outline of the debate, see Godfrey-Smith (2007).

  3. 3.

    Glennan’s (1996, 2002) approach is similar, except not counting the interactions among the constituents of a mechanism.

  4. 4.

    We must abstain here from phenomena such as symmetry breaking at the level of elementary particles that are not yet understood satisfactorily.

  5. 5.

    Dowe (1992) and Salmon (1994) correctly identified conservation laws as being at the core of modern physics. The link that these authors draw between conservativity and causality, however, can hardly be justified. In contrast to their proposal, conservativity may neither count as a necessary, nor as a sufficient condition for causality: neither is each conservative process causal (e.g., radioactive decay, tunneling, quantum transitions), nor are all causal processes conservative (e.g., semiotic processes; see Sect. 4.3).

  6. 6.

    Herbert Simon calls any technical information processing system a physical symbol system (Simon 1996, p. 21, pp. 187–188).

  7. 7.

    Here the concept of function is taken in the sense of a causal role function (Cummins 1975), which nevertheless allows for judgment about malfunction. To allow for this normativity of the concept, a modification needs to be introduced into Cummins’s account, e.g., by reference to fixed types of function bearers (Krohs 2009a, 2011).

  8. 8.

    A further question is whether nonconservativity of functional models holds in general. This seems to be the case (Krohs 2004). The function of a screw (or of any other mechanical device) of being a stop for a lever can simply be lost under certain circumstances, e.g., if the lever is bent. There is no necessity of the function being transformed into anything else according to any conservation law.

  9. 9.

    Only theory reduction is at stake here. Ontological reducibility may be presupposed, be the semiotic model reducible to the physicalistic one or not.

  10. 10.

    Darden and Craver (2002, p. 5) ascribe work on information flow to molecular biologists and work on the flow of matter and energy to biochemists. While this might be considered a somewhat artificial attribution of different research topics to disciplines, it clearly emphasizes that physicochemical and semiotic analyses are categorically different and thus should indeed give rise to models of different kind.

  11. 11.

    Nevertheless, one needs not subscribe to structural realism, neither in its epistemic (Maxwell 1970; Worrall 1989, 1994) nor in its ontic variant (Ladyman 1998; French and Ladyman 2003), to accept the explanatory power of the structure of a model.

  12. 12.

    In so far, the realist interpretation of semiotic terms in molecular biology by some biosemioticians is misguided.

  13. 13.

    Since the physicalistic model carries the realist burden, the correlated semiotic model even must not be interpreted in a realist way. I see no reason for going as far as postulating an informational ontology (Floridi 2008, 2009).

References

  • Alberts, B., Johnson, A., Lewis, J., Raff, M., Roberts, K., & Walter, P. (2002). Molecular biology of the cell (4th ed.). New York: Garland.

    Google Scholar 

  • Bechtel, W., & Abrahamsen, A. (2005). Explanation: A mechanist alternative. Studies in History and Philosophy of Biological and Biomedical Sciences, 33(2), 421–441.

    Article  Google Scholar 

  • Carrier, M. (2000). Multiplicity and heterogeneity: On the relations between functions and their realizations. Studies in History and Philosophy of Biological and Biomedical Sciences, Part C, 31(1), 179–191.

    Article  Google Scholar 

  • Craver, C. F. (2001). Role functions, mechanisms, and hierarchy. Philosophy of Science, 68(1), 53–74.

    Article  Google Scholar 

  • Cummins, R. (1975). Functional analysis. The Journal of Philosophy, 72, 741–765.

    Article  Google Scholar 

  • Darden, L., & Craver, C. F. (2002). Strategies in the interfield discovery of the mechanism of protein synthesis. Studies in History and Philosophy of Biological and Biomedical Sciences, Part C, 33(1), 1–28.

    Article  Google Scholar 

  • Dowe, P. (1992). Wesley Salmon’s process theory of causality and the conserved quantity theory. Philosophy of Science, 59(2), 195–216.

    Article  Google Scholar 

  • Floridi, L. (2008). A defence of informational structural realism. Synthese, 161(2), 219–253.

    Article  Google Scholar 

  • Floridi, L. (2009). Against digital ontology. Synthese, 168(1), 151–178.

    Article  Google Scholar 

  • French, S., & Ladyman, J. (2003). Remodelling structural realism: Quantum mechanics and the metaphysics of structure. Synthese, 136(1), 31–56.

    Article  Google Scholar 

  • Giere, R. N. (2004). How models are used to represent reality. Philosophy of Science, 71(5), 742–752.

    Article  Google Scholar 

  • Glennan, S. (1996). Mechanisms and the nature of causation. Erkenntnis, 44(1), 49–71.

    Article  Google Scholar 

  • Glennan, S. (2002). Rethinking mechanistic explanation. Philosophy of Science, 69(3), 342–353.

    Article  Google Scholar 

  • Godfrey-Smith, P. (1999). Genes and codes: Lessons from the philosophy of mind? In V. G. Hardcastle (Ed.), Where biology meets psychology: Philosophical essays (pp. 305–331). Cambridge: MIT Press.

    Google Scholar 

  • Godfrey-Smith, P. (2000). On the theoretical role of ‘genetic coding’. Philosophy of Science, 67(1), 26–44.

    Article  Google Scholar 

  • Godfrey-Smith, P. (2007). Information in biology. In D. L. Hull & M. Ruse (Eds.), The Cambridge companion to the philosophy of biology (pp. 103–119). Cambridge: Cambridge University Press.

    Chapter  Google Scholar 

  • Griffiths, P. E. (2001). Genetic information: A metaphor in search of a theory. Philosophy of Science, 68(3), 394–412.

    Article  Google Scholar 

  • Hempel, C. G. (1980). Comments on Goodman’s ways of worldmaking. Synthese, 45(2), 193–199.

    Article  Google Scholar 

  • Jablonka, E. (2002). Information: Its interpretation, its inheritance, and its sharing. Philosophy of Science, 69(4), 578–605.

    Article  Google Scholar 

  • Kay, L. E. (2000). Who wrote the book of life? A history of the genetic code. Stanford: Stanford University Press.

    Google Scholar 

  • Krohs, U. (2004). Eine Theorie biologischer Theorien. Berlin: Springer.

    Book  Google Scholar 

  • Krohs, U. (2009a). Functions as based on a concept of general design. Synthese, 166(1), 69–89.

    Article  Google Scholar 

  • Krohs, U. (2009b). Structure and coherence of two-model-descriptions of technical artefacts. Techné: Research in Philosophy and Technology, 13(2), 150–161.

    Google Scholar 

  • Krohs, U. (2011). Functions and fixed types: Biological functions in the post-adaptationist era. Applied Ontology, 6(2), 125–139.

    Article  Google Scholar 

  • Ladyman, J. (1998). What is structural realism. Studies in History and Philosophy of Science, Part A, 29(3), 409–424.

    Article  Google Scholar 

  • Machamer, P., Darden, L., & Craver, C. F. (2000). Thinking about mechanisms. Philosophy of Science, 67(1), 1–25.

    Article  Google Scholar 

  • Maxwell, G. (1970). Structural realism and the meaning of theoretical terms. In M. Radner & S. Winokur (Eds.), Analyses of theories and methods of physics and psychology (Minnesota studies in the philosophy of science, Vol. 4, pp. 181–192). Minneapolis: University of Minnesota Press.

    Google Scholar 

  • Maynard Smith, J. (2000). The concept of information in biology. Philosophy of Science, 67(2), 177–194.

    Article  Google Scholar 

  • Morgan, M. S., & Morrison, M. (Eds.). (1999). Models as mediators. Cambridge: Cambridge University Press.

    Google Scholar 

  • Moss, L. (2003). What genes can’t do. Cambridge: MIT Press.

    Google Scholar 

  • Salmon, W. C. (1994). Causality without counterfactuals. Philosophy of Science, 61(2), 297–312.

    Article  Google Scholar 

  • Sarkar, S. (1998). Genetics and reductionism. Cambridge: Cambridge University Press.

    Book  Google Scholar 

  • Sarkar, S. (2005). Molecular models of life: Philosophical papers on molecular biology. Cambridge: MIT Press.

    Google Scholar 

  • Simon, H. A. (1996). The sciences of the artificial (3rd ed.). Cambridge: MIT Press.

    Google Scholar 

  • Stegmann, U. (2005). Genetic information as instructional content. Philosophy of Science, 72(3), 425–443.

    Article  Google Scholar 

  • Sterelny, K., Smith, K., & Dickison, M. (1996). The extended replicator. Biology and Philosophy, 11(3), 377–403.

    Article  Google Scholar 

  • Tipler, P. A., & Mosca, G. (2007). Physics for scientists and engineers, extended version (6th ed.). New York: Freeman.

    Google Scholar 

  • Worrall, J. (1989). Structural realism: The best of both worlds? Dialectica, 43(1–2), 99–124.

    Article  Google Scholar 

  • Worrall, J. (1994). How to remain (reasonably) optimistic: Scientific realism and the ‘Luminiferous Ether’. PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association, 1, 334–342.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Ulrich Krohs .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer Science+Business Media Dordrecht

About this chapter

Cite this chapter

Krohs, U. (2014). Semiotic Explanation in the Biological Sciences. In: Kaiser, M.I., Scholz, O.R., Plenge, D., Hüttemann, A. (eds) Explanation in the Special Sciences. Synthese Library, vol 367. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-7563-3_4

Download citation

Publish with us

Policies and ethics