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Living is Information Processing: From Molecules to Global Systems

Abstract

We extend the concept that life is an informational phenomenon, at every level of organisation, from molecules to the global ecological system. According to this thesis: (a) living is information processing, in which memory is maintained by both molecular states and ecological states as well as the more obvious nucleic acid coding; (b) this information processing has one overall function—to perpetuate itself; and (c) the processing method is filtration (cognition) of, and synthesis of, information at lower levels to appear at higher levels in complex systems (emergence). We show how information patterns, are united by the creation of mutual context, generating persistent consequences, to result in ‘functional information’. This constructive process forms arbitrarily large complexes of information, the combined effects of which include the functions of life. Molecules and simple organisms have already been measured in terms of functional information content; we show how quantification may be extended to each level of organisation up to the ecological. In terms of a computer analogy, life is both the data and the program and its biochemical structure is the way the information is embodied. This idea supports the seamless integration of life at all scales with the physical universe. The innovation reported here is essentially to integrate these ideas, basing information on the ‘general definition’ of information, rather than simply the statistics of information, thereby explaining how functional information operates throughout life.

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Notes

  1. Though some biologists may include viruses.

References

  • Adami C, Ofria C, Collier TC (2000) Evolution of biological complexity. Proc Natl Acad Sci USA 97(9):4463–4468

    Article  Google Scholar 

  • Annila A, Annila E (2008) Why did life emerge. Int J Astrobiol 7(3–4):293–300

    Article  Google Scholar 

  • Annila A, Kuismanen E (2009) Natural hierarchy emerges from energy dispersal. Biosystems 95(3):227–233

    Article  Google Scholar 

  • Balleza E, Alvarez-Buylla ER, Chaos A, Kauffman S, Shmulevich I, Aldana M (2008) Critical dynamics in genetic regulatory networks: examples from four kingdoms. Plos One 3(6):e2456. doi:10.1371/journal.pone.0002456

  • Bates M (2005) Information and knowledge: an evolutionary framework for information science. Inf Res 10(4):paper 239. Accessed from http://InformationR.net/ir/10-4/paper239.html Oct 2012

  • Bateson G (1972) Form, substance, and difference. In: Bateson G (ed) Steps to an ecology of mind. University of Chicago Press, Chicago, pp 448–466

    Google Scholar 

  • Bitbol M, Luisi P (2004) Autopoiesis with or without cognition: defining life at its edge. J R Soc Interface 1(1):99–107

    Article  Google Scholar 

  • Bowen N, Jordan I (2002) Transposable elements and the evolution of eukaryotic complexity. Curr Issues Mol Biol 4:65–76

    Google Scholar 

  • Bray D (1995) Protein molecules as computational elements in living cells. Nature 376(6538):307–312

    Article  Google Scholar 

  • Bray D (2009) Wetware: a computer in every living cell. Yale University Press, New Haven, CT

    Google Scholar 

  • Butler MH, Paton RC, Leng PH (1998) Information processing in tissues and cells, chapter Information processing in computational tissues. Plenum Press, New York, pp 177–184

    Book  Google Scholar 

  • Cairns J, Overbaugh J, Miller S (1988) The origin of mutants. Nature 335:142–145

    Article  Google Scholar 

  • Camazine S, Deneubourg JL, Franks N, Sneyd J, Theraulaz G, Bonabeau E (2001) Self-organization in biological systems. Princeton University Press, Princeton, NJ

    Google Scholar 

  • Carroll S (2001) Chance and necessity: the evolution of morphological complexity and diversity. Nature 409(6823):1102–1109

    Article  Google Scholar 

  • Chaitin G (1990) Information, randomness and incompleteness. Papers on algorithmic information theory, volume 8 of series in computer science, 2nd edn. World Scientific, Singapore

    Google Scholar 

  • ConantR Ashby W (1970) Every good regulator of a system must be a model of that system. Int J Syst Sci 1(2):89–97

    Article  Google Scholar 

  • Cowling R, Knight A, Faith D, Ferrier S, Lombard A, Driver A, Rouget M, Maze K, Desmet P (2004) Nature conservation requires more than a passion for species. Conserv Biol 18(6):1674–1676

    Article  Google Scholar 

  • Cummins R (1975) Functional analysis. J Philos 72(20):741–765

    Article  Google Scholar 

  • Curtis T, Sloan W, Scannell J (2002) Estimating prokaryotic diversity and its limits. Proc Natl Acad Sci USA 99(16):10494–10499

    Article  Google Scholar 

  • Davidson EH (2001) Genomic regulatory systems: development and evolution. Academic Press, San Diego, USA

    Google Scholar 

  • Davidson EH, Levin M (2005) Gene regulatory networks. Proc Nat Acad Sci USA 102(14):4935

    Article  Google Scholar 

  • Denning PJ (2007) Computing is a natural science. Commun ACM 50(7):13–18

    Article  Google Scholar 

  • Dunne J, Williams R, Martinez N (2002) Food-web structure and network theory: the role of connectance and size. Proc Natl Acad Sci USA 99(20):12917–12922

    Article  Google Scholar 

  • Faeder JR (2011) Toward a comprehensive language for biological systems. BMC Biol 9:68

    Article  Google Scholar 

  • Farnsworth K, Lyashevska O, Fung T (2012) Functional complexity: the source of value in biodiversity. Ecol Complex 11:46–52

    Article  Google Scholar 

  • Favareau, D (eds) (2009) Essential readings in biosemiotics: anthology and commentary. Springer, Berlin

    Google Scholar 

  • Floridi L (2003) Information. In: Floridi L (ed) The Blackwell guide to the philosophy of computing and information. Blackwell Publishing Ltd, New York, pp 40–61

    Chapter  Google Scholar 

  • Floridi L (2005) Is semantic information meaningful data? Philos Phenomenol Res 70(2):351–370

    Article  Google Scholar 

  • Galtin LL (1972) Information theory and the living system. Columbia University Press, New York

    Google Scholar 

  • Geard N, Wiles J (2005) A gene network model for developing cell lineages. Artif Life 11:249–267

    Article  Google Scholar 

  • Gell-Mann M, Lloyd S (1996) Information measures, effective complexity, and total information. Complexity 2(1):44–52

    Article  Google Scholar 

  • Gell-Mann M, Lloyd S (2003) Effective complexity. In: Gell-Mann M, Tsallis C (eds) Nonextensive entropy—interdisciplinary applications. Oxford University Press, Oxford

    Google Scholar 

  • Gershenson C (2010) Computing networks: a general framework to contrast neural and swarm cognitions. Paladyn J Behav Robot 1(2):147–153

    Article  Google Scholar 

  • Gershenson C, Fernández N (2012) Complexity and information: Measuring emergence, self-organization, and homeostasis at multiple scales. Complexity, Early View

  • Goldman R, Pollack R, Hopkins N (1973) Preservation of normal behavior by enucleated cells in culture. Proc Nat Acad Sci USA 70:750–754

    Article  Google Scholar 

  • Gregory T (2001) Coincidence, coevolution, or causation? DNA content, cell size, and the C-value enigma. Biol Rev 76(1):65–101

    Article  Google Scholar 

  • Griffiths PE (1993) Functional analysis and proper functions. British J Philos Sci 44:409–422

    Article  Google Scholar 

  • Hinegardner R, Engelberg J (1983) Biological complexity. J Theor Biol 104:7–20

    Article  Google Scholar 

  • Hopfield JJ (1994) Physics, computation, and why biology looks so different. J Theor Biol 171:53–60

    Article  Google Scholar 

  • Jiang Y, Xu C (2010) The calculation of information and organismal complexity. Biol Direct 5:59

    Article  Google Scholar 

  • Kaila VRI, Annila A (2008) Natural selection for least action. Proc R Soc A Math Phys Eng Sci 464(2099):3055–3070

    Article  Google Scholar 

  • Karnani M, Annila A (2009) Gaia again. Biosystems 95(1):82–87

    Article  Google Scholar 

  • Kauffman SA (1993) Origins of order: self-organization and selection in evolution. Oxford University Press, Oxford

    Google Scholar 

  • Kohl P, Crampin EJ, Quinn TA, Noble D (2010) Systems biology: an approach. Clin Pharmacol Ther 88(1):25–33

    Article  Google Scholar 

  • Kornberg A (1991) Understanding life as chemistry. Clin Chem 37(11):1895–1899

    Google Scholar 

  • Kravchenko-Balasha N, Levitzki A, Goldstein A, Rotter V, Gross A, Remacle F, Levine RD (2012) On a fundamental structure of gene networks in living cells. Proc Natl Acad Sci USA 109(12):4702–4707

    Article  Google Scholar 

  • Lee K (2004) There is biodiversity and biodiversity. In: Oksanen M, Pietarinen J (eds) Philosophy and biodiversity. Cambridge University Press, Cambridge, pp 152–171

    Chapter  Google Scholar 

  • Lehn J-M (1990) Perspectives in supramolecular chemistry—from molecular recognition towards molecular information processing and self-organization. Angewandte Chem Int Edition English 29(11):1304–1319

    Article  Google Scholar 

  • Lepot K, Benzerara K, Brown G, Philippot P (2008) Microbially influenced formation of 2,724-million-year-old stromatolites. Nat Geosci 1:118–121

    Google Scholar 

  • Li M, Vitányi PMB (2008) An introduction to Kolmogorov complexity and its applications, 3rd edn. Springer, Berlin

  • Lorenz DM, Jeng A, Deem MW (2011) The emergence of modularity in biological systems. Phys Life Rev 8(2):129–160

    Google Scholar 

  • Lovelock JE, Margulis L (1974) Atmospheric homeostasis by and for the biosphere: the Gaia hypothesis. Tellus 26(1):2–10

    Google Scholar 

  • Lyashevska O, Farnsworth KD (2012) How many dimensions of biodiversity do we need. Ecol Ind 18:485–492

    Article  Google Scholar 

  • MacKay DM (1969) Information, mechanism and meaning. MIT Press, Cambridge, MA

    Google Scholar 

  • Magurran A (2004) Measuring biological diversity. Blackwell Publishing, New York

    Google Scholar 

  • Margulis L (1970) Origin of eukaryotic cells. Yale University Press, New Haven, CT

    Google Scholar 

  • Maturana H, Varela FJ (1980) Autopoiesis and cognition: the realization of the living. D. Reidel Publishing Company, Dordrecht (Translation of original: De Maquinas y seres vivos. Universitaria Santiago)

  • Maus C, Rybacki S, Uhrmacher AM (2011) Rule-based multi-level modeling of cell biological systems. BMC Syst Biol 5:166

    Article  Google Scholar 

  • McAllister J (2003) Effective complexity as a measure of information content. Philos Sci 70(2):302–307

    Article  Google Scholar 

  • McGill BJ (2011) Linking biodiversity patterns by autocorrelated random sampling. Am J Bot 98(3):481–502

    Article  Google Scholar 

  • Menconi G (2005) Sublinear growth of information in dna sequences. Bull Math Biol 67(4):737–759

    Article  Google Scholar 

  • Montoya J, Pimm SL, Solé RV (2006) Ecological networks and their fragility. Nature 442(7100):259–264

    Article  Google Scholar 

  • Mora C, Tittensor DP, Adl S, Simpson AGB, Worm B (2011) How many species are there on earth and in the ocean? PLoS Biol 9(8):e1001127. doi:10.1371/journal.pbio.1001127

  • Morowitz HJ (1992) Beginnings of cellular life. Yale University Press, New Haven, CT

    Google Scholar 

  • Neander K (1991) Functions as selected effects: a conceptual analysts defense. Philos Sci 58(2):168–184

    Article  Google Scholar 

  • Neander K (2011) Routledge encyclopedia of philosophy (Online). Routledge

  • Nekola J, White P (1999) The distance decay of similarity in biogeography and ecology. J Biogeogr 26(4):867–878

    Article  Google Scholar 

  • Norton B, Ulanowicz R (1992) Scale and biodiversity policy—a hierarchical approach. Ambio 21(3):244–249

    Google Scholar 

  • Orchard S, Hermjakob H, Apweiler R (2005) Annotating the human proteome. Mol Cell Proteomics 4(4):435–40

    Article  Google Scholar 

  • Orgel L, Crick F (1980) Selfish DNA: the ultimate parasite. Nature 284:604–607

    Article  Google Scholar 

  • Prigogine I (1977) Self-organization in non-equilibrium systems. Wiley, New York

    Google Scholar 

  • Prigogine I, Stengers I (1984) Order out of chaos: man’s new dialogue with nature. Flamingo Collins Publishing Group, London

  • Robertson M, Joyce G (2010) The origins of the rna world. Cold Spring Harbour Perspectives In Biology

  • Rodbell M (1995) Signal transduction: evolution of an idea. Biosci Rep 15:117–133

    Article  Google Scholar 

  • Salthe S (1985) Evolving hierarchical systems: their structure and representation. Columbia University Press, New York City

    Google Scholar 

  • Schneider TD (2000) Evolution of biological information. Nucleic Acids Res 28:2794–2799

    Google Scholar 

  • Schrödinger E (1944) What is life? The physical aspects of the living cell. http://home.att.net/p.caimi/schrodinger.html. Accessed online Oct 2012

  • Scott J, Carr W (1992) Subcellular localization of the type II cAMP-dependent protein kinase. Physiology 7:143–148

    Google Scholar 

  • Shannon C (1948) A mathematical theory of communication. Bell Syst Tech J 27(3,4):379–423, 623–656

    Google Scholar 

  • Smith E (2008) Thermodynamics of natural selection I: energy flow and the limits on organization. J Theor Biol 252(2):185–197

    Article  Google Scholar 

  • Smith E, Morowitz HJ (2004) Universality in intermediary metabolism. Proc Nat Acad Sci USA 101(36):13168–13173

    Article  Google Scholar 

  • Szostak JW (2003) Functional information: molecular messages. Nature 423(6941):689–689

    Article  Google Scholar 

  • Tuomisto H (2010) A diversity of beta diversities: straightening up a concept gone awry. Part 1: defining beta diversity as a function of alpha and gamma diversity. Ecography 33(1):2–22

    Article  Google Scholar 

  • Turing A (1936) On computable numbers, with an application to the entscheidungs problem. Proc Lond Math Soc 42:230–265

    Google Scholar 

  • Turing A (1952) The chemical basis for morphogenesis. Philos Trans R Soc Lond Ser B Biol Sci 237:37–72

    Article  Google Scholar 

  • Ulanowicz R (1980) An hypothesis on the development of natural communitiesl. J Theor Biol 85:223–245

    Article  Google Scholar 

  • Ulanowicz R, Baird D (1999) Nutrient controls on ecosystem dynamics: the chesapeake mesohaline community. J Mar Syst 19:159–172

    Article  Google Scholar 

  • Valentine J (1994) Late precambrian bilaterians: grades and clades. Proc Natl Acad Sci USA 91(15):6751–6757

    Article  Google Scholar 

  • Valentine J (2003a) Architectures of biological complexity. Integr Comp Biol 43(1):99–103

    Article  Google Scholar 

  • Valentine J (2003b) Cell types, cell type numbers, and body plan complexity. In: Hall B, Olson W (eds) Keywords and concepts in evolutionary developmental biology. Harvard University Press, Cambridge, pp 35–43

    Google Scholar 

  • Valentine J, Collins A, Meyer C (1994) Morphological complexity increase in metazoans. Paleobiology 20(2):131–142

    Google Scholar 

  • Veitia RA, Bottani S (2009) Whole genome duplications and a ‘function’ for junk DNA? Facts and hypotheses. Plos ONE 4(12):e8201. doi:10.1371/journal.pone.0008201

  • von Foerster H (1960) On self-organizing systems and their environments. In: Yovits M, Cameron S (eds) Self-organizing systems.. Pergamon Press, Oxford

    Google Scholar 

  • Wessler SR (2006) Transposable elements and the evolution of eukaryotic genomes. Proc Natl Acad Sci USA 103(47):17600–17601

    Article  Google Scholar 

  • Wicken JS (1979) The generation of complexity in evolution: a thermodynamic and information-theoretical discussion. J Theor Biol 77:349–365

    Article  Google Scholar 

  • Wiener N (1948) Cybernetics; or, control and communication in the animal and the machine. Wiley and Sons, New York

    Google Scholar 

  • Yockey H, Platzman R, Quastler H (eds) (1958) Symposium on information theory in biology (1956: Gatlinburg, Tenn.). Pergamon Press, New York

  • Zepik H, Blochliger E, Luisi P (2001) A chemical model of homeostasis. Angewandte Chemie Int Edition 40(1):199–202

    Article  Google Scholar 

  • Zhou J, Deng Y, Luo F, He Z, Tu Q, Zhi X (2010) Functional molecular ecological networks. MBio 1(4):e00169–10. doi:10.1128/mBio.00169-10

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Acknowledgments

This work was enhanced by very thoughtful and creative reviews by anonymous referees. It was supported by a Science Technology Research and Innovation for the Environment grant from the Environmental Protection Agency of the Republic of Ireland: 2007-PhD-SD-3. C.G. was partially supported by SNI membership 47907 of CONACyT, Mexico.

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Correspondence to Keith D. Farnsworth.

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Farnsworth, K.D., Nelson, J. & Gershenson, C. Living is Information Processing: From Molecules to Global Systems. Acta Biotheor 61, 203–222 (2013). https://doi.org/10.1007/s10441-013-9179-3

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Keywords

  • Complex system
  • Entropy
  • Biocomplexity
  • Evolution
  • Network