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Biology Needs Information Theory

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Abstract

Communication is an important feature of the living world that mainstream biology fails to adequately deal with. Applying two main disciplines can be contemplated to fill in this gap: semiotics and information theory. Semiotics is a philosophical discipline mainly concerned with meaning; applying it to life already originated in biosemiotics. Information theory is a mathematical discipline coming from engineering which has literal communication as purpose. Biosemiotics and information theory are thus concerned with distinct and complementary possible meanings of the word ‘communication’. Since literal communication needs to be secured so as to enable semantics being communicated, information theory is a necessary prerequisite to biosemiotics. Moreover, heredity is a purely literal communication process of capital importance fully relevant to literal communication, hence to information theory. A short introduction to discrete information theory is proposed, which is centred on the concept of redundancy and its use in order to make sequences resilient to errors. Information theory has been an extremely active and fruitful domain of researches and the motor of the tremendous progress of communication engineering in the last decades. Its possible connections with semantics and linguistics are briefly considered. Its applications to biology are suggested especially as regards error-correcting codes which are mandatory for securing the conservation of genomes. Biology needs information theory so biologists and communication engineers should closely collaborate.

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Notes

  1. This seminal two-part paper has been reprinted in Shannon and Weaver (1949) and Sloane and Wyner (1993).

  2. This encoder is referred to as ‘convolutional recursive systematic’; when combined with an interleaver, two such encoders generate a turbocode like that which first succeeded in closely approaching the channel capacity (Berrou et al. 1993; Berrou and Glavieux 1996; Guizzo 2004).

  3. In engineering words, ignoring a symbol is referred to as its ‘erasure’: when the receiver cannot take any decision about a symbol, it does not take it into account. An erasure must be distinguished from an error which consists of taking a wrong decision.

  4. This result theoretically extends to regular enough codes. Actually correcting up to n − k erased bits within an n-bit word requires a specific algorithm possibly complicated or even unknown.

  5. Notice that we refer here to an information, not to information in general.

  6. ‘Channel’ is currently used to designate a means for communicating over space, but we extend here its meaning to communication over time, as a synonymous of ‘memory’ or ‘register’.

  7. By a remarkable coincidence, researches on semi-conductors and on information theory started at the same time, 1948, and the same place, the Bell Telephone Laboratories.

  8. For the anecdote, Shannon was a great tinkerer.

  9. Shannon’s random coding alluded to In Section “Any Constraints on Sequences Define Error-Correcting Codes” may to some extent have been inspired by Darwin.

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  1. La Chanatte, Le Guimand, 26120, Chabeuil, France

    Gérard Battail

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  1. Gérard Battail
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Battail, G. Biology Needs Information Theory. Biosemiotics 6, 77–103 (2013). https://doi.org/10.1007/s12304-012-9152-6

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