Biology & Philosophy

, Volume 26, Issue 2, pp 159–176 | Cite as

The transmission sense of information

Article

Abstract

Biologists rely heavily on the language of information, coding, and transmission that is commonplace in the field of information theory developed by Claude Shannon, but there is open debate about whether such language is anything more than facile metaphor. Philosophers of biology have argued that when biologists talk about information in genes and in evolution, they are not talking about the sort of information that Shannon’s theory addresses. First, philosophers have suggested that Shannon’s theory is only useful for developing a shallow notion of correlation, the so-called “causal sense” of information. Second, they typically argue that in genetics and evolutionary biology, information language is used in a “semantic sense,” whereas semantics are deliberately omitted from Shannon’s theory. Neither critique is well-founded. Here we propose an alternative to the causal and semantic senses of information: a transmission sense of information, in which an object X conveys information if the function of X is to reduce, by virtue of its sequence properties, uncertainty on the part of an agent who observes X. The transmission sense not only captures much of what biologists intend when they talk about information in genes, but also brings Shannon’s theory back to the fore. By taking the viewpoint of a communications engineer and focusing on the decision problem of how information is to be packaged for transport, this approach resolves several problems that have plagued the information concept in biology, and highlights a number of important features of the way that information is encoded, stored, and transmitted as genetic sequence.

Keywords

Information Evolution Shannon theory Natural selection Entropy Mutual information 

References

  1. Adami C (2002) What is complexity? BioEssays 24:1085–1094CrossRefGoogle Scholar
  2. Bennetzen J, Hall B (1982) Codon selection in yeast. J Biol Chem 257:3026–3031Google Scholar
  3. Bulmer M (1987) Coevolution of codon usage and transfer RNA abundance. Nature 325:728–730Google Scholar
  4. Cipra BA (1993) The ubiquitous reed-solomon codes. SIAM News 26, No. 1Google Scholar
  5. Cover TM, Thomas JA (2006) Elements of information theory, 2nd edn. Wiley, New YorkGoogle Scholar
  6. Crick FHC (1970) The central dogma of molecular biology. Nature 227:561–563CrossRefGoogle Scholar
  7. Crick FHC, Griffith JS, Orgel LE (1957) Codes without commas. Proc Natl Acad Sci USA 43:416–421CrossRefGoogle Scholar
  8. de Ruyter van Steveninck RR, Lewen GD, Strong SP, Koberle R, Bialek W (1997) Reproducibility and variability in neural spike trains. Science 275:1805–1808CrossRefGoogle Scholar
  9. Dretske FI (1983) Knowledge and the flow of information. MIT, CambridgeGoogle Scholar
  10. Felsenstein J (1971) On the biological significance of the cost of gene substitution. Am Nat 105:1–11CrossRefGoogle Scholar
  11. Freeland SJ, Hurst LD (1998) The genetic code is one in a million. J Mol Evol 47:238–248CrossRefGoogle Scholar
  12. Godfrey-Smith P (1999) Genes and codes: lessons from the philosophy of mind. In: Hardcastle V (ed) Where biology meets psychology: philosophical essays. MIT, Cambridge, pp 305–331Google Scholar
  13. Godfrey-Smith P (2000a) On the theoretical role of “genetic coding”. Philos Sci 67:26–44CrossRefGoogle Scholar
  14. Godfrey-Smith P (2000b) Information, arbitrariness, and selection: comments on maynard smith. Philos Sci 67:202–207. ISSN 00318248Google Scholar
  15. Godfrey-Smith P (2007) Biological information. In: Zalta EN (ed) Stanford encyclopedia of philosophy. Center for the Study of Language and Information, Stanford UniversityGoogle Scholar
  16. Godfrey-Smith P (2008) Information in biology. In: Hull DL, Ruse M (eds) The philosophy of biology, chap 6. Cambridge University Press, Cambridge, pp 103–119Google Scholar
  17. Grice HP (1957) Meaning. Philos Rev 66:377–388CrossRefGoogle Scholar
  18. Griesemer JR (2005) The informational gene and the substantial body: on the generalization of evolutionary theory by abstraction. In: Jones MR, Cartwright N (eds) Idealization XII: correcting the model, idealization and abstraction in the sciences. Rodopi, Amsterdam, pp 59–115Google Scholar
  19. Griffiths PE (2001) Genetic information: a metaphor in search of a theory. Philos Sci 68:394–412CrossRefGoogle Scholar
  20. Griffiths PE, Gray RD (1994) Developmental systems and evolutionary explanation. J Philos XCI:277–304CrossRefGoogle Scholar
  21. Griffiths PE, Knight RD (1998) What is the developmentalist challenge? Philos Sci 65:276–288CrossRefGoogle Scholar
  22. Haig D, Hurst LD (1991) A quantitative measure of error minimization in the genetic code. J Mol Evol 37:412–417CrossRefGoogle Scholar
  23. Ikemura T (1981) Correlation between the abundance of Escherichia coli transfer RNAs and the occurrence of the respective codons in its protein genes: a proposal for a synonymous codon choice that is optimal for the E. coli translational system. J Mol Biol 151:389–409CrossRefGoogle Scholar
  24. Itzkovitz S, Alon U (2007) The genetic code is nearly optimal for allowing additional information within protein-coding sequences. Genome Res 17:405–412CrossRefGoogle Scholar
  25. Kimura M (1961) Natural selection as the process of accumulation of genetic information in adaptive evolution. Genet Res 2:127–140CrossRefGoogle Scholar
  26. Knight R, Freeland S, Landweber L (2001) A simple model based on mutation and selection explains trends in codon and amino-acid usage and GC composition within and across genomes. Genome Biol 2:r0010.1–r0010.13Google Scholar
  27. Lewontin RC (1992) The dream of the human genome. N Y Rev Books 39Google Scholar
  28. Lloyd S, Penfield P (2003) Information and entropy: mit open coursewareGoogle Scholar
  29. Maynard Smith J (2000) The concept of information in biology. Philos Sci 67:177–194. ISSN 00318248Google Scholar
  30. Mitarai N, Sneppen K, Pedersen S (2008) Ribosome collisions and translation efficiency: optimization by codon usage and mRNA destabilization. J Mol Biol 382:236–245Google Scholar
  31. Monod J (1971) Chance and necessity. Collins, LondonGoogle Scholar
  32. Odling-Smee FJ, Leland KN, Feldman MW (2003) Niche construction. Princeton University Press, New JerseyGoogle Scholar
  33. Pierce JR (1980) An introduction to information theory. Dover, New YorkGoogle Scholar
  34. Seligmann H, Pollock D (2004) The ambush hypothesis: hidden stop codons prevent off-frame gene reading. DNA Cell Biol 23:701–705CrossRefGoogle Scholar
  35. Shannon CE (1948) A mathematical theory of communication. Bell Syst Tech J 27:379–423Google Scholar
  36. Shannon CE (1950) Prediction and entropy of printed English. Bell Syst Tech J 30:50–64Google Scholar
  37. Shannon CE (1956) The bandwagon. IEEE Trans Inf Theory 2, No. 3Google Scholar
  38. Shannon CE, Weaver W (1949) The mathematical theory of communication. University of Illinois Press, UrbanaGoogle Scholar
  39. Sharp P, Li W (1987) The codon adaptation index—a measure of directional synonymous codon usage bias, and its potential applications. Nucleic Acids Res 15:1281–1295CrossRefGoogle Scholar
  40. Shea N (2007) Representation in the genome and in other inheritance systems. Biol Philos 22:313CrossRefGoogle Scholar
  41. Sonneborn TM (1965) Degeneracy of the genetic code: extent, nature and genetic implications. In: Bryson V, Vogel JH (eds) Evolving genes and proteins. Academic Press, New York, pp 377–397Google Scholar
  42. Sørensen M, Pedersen S (1991) Absolute in vivo translation rates of individual codons in Escherichia coli. The two glutamic acid codons GAA and GAG are translated with a threefold difference in rate. J Mol Biol 222:265–280CrossRefGoogle Scholar
  43. Stegmann UE (2004) The arbitrariness of the genetic code. Biol Philos 19:205–222CrossRefGoogle Scholar
  44. Stegmann UE (2005) Genetic information as instructional content. Philos Sci 72:425–443CrossRefGoogle Scholar
  45. Sterelny K (2001) The “genetic program” program: a commentary on Maynard Smith on information in biology. Philos Sci 67:195–201CrossRefGoogle Scholar
  46. Sterelny K, Griffiths PE (1999) Sex and death: an introduction to philosophy of biology. University of Chicago Press, ChicagoGoogle Scholar
  47. Sterelny K, Smith KC, Dickison M (1996) The extended replicator. Biol Philos 11:377–403CrossRefGoogle Scholar
  48. Szathmary E, Maynard Smith J (1995) The major evolutionary transitions. Nature 374:227–232CrossRefGoogle Scholar
  49. Voight BF, Kudaravalli S, Wen X, Pritchard JK (2006) A map of recent positive selection in the human genome. PLoS Biol 4:446–458CrossRefGoogle Scholar
  50. Woese CR (1965) On the evolution of the genetic code. Proc Natl Acad Sci USA 54:1546–1552CrossRefGoogle Scholar
  51. Yeung RW (2002) A first course in information theory. Springer, New YorkGoogle Scholar

Copyright information

© US Government 2009

Authors and Affiliations

  1. 1.Department of BiologyUniversity of WashingtonSeattleUSA
  2. 2.Santa Fe InstituteSanta FeUSA

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